A survey of large language models for healthcare: from data, technology, and applications to accountability and ethics

Language Models are Few-Shot Learners

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Chain-Of-Thought Prompting Elicits Reasoning in Large Language Models

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Training language models to follow instructions with human feedback

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Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models

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Large language models encode clinical knowledge

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Training Language Models to Follow Instructions with Human Feedback

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LoRA: Low-Rank Adaptation of Large Language Models

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LXMERT: Learning Cross-Modality Encoder Representations from Transformers

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Domain-specific language model pretraining for biomedical natural language processing

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Don’t Stop Pretraining: Adapt Language Models to Domains and Tasks

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A Survey of Large Language Models

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A Survey of Large Language Models

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Large language models are zero-shot reasoners

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A survey on federated learning

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Toward expert-level medical question answering with large language models

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Recent Advances in Natural Language Processing via Large Pre-trained Language Models: A Survey

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Preparing a collection of radiology examinations for distribution and retrieval

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Evaluating the Feasibility of ChatGPT in Healthcare: An Analysis of Multiple Clinical and Research Scenarios

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Database resources of the National Center for Biotechnology Information

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Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations

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Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets

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Med-BERT: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction

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Structured information extraction from scientific text with large language models

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Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?

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Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?

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Algorithmic fairness in artificial intelligence for medicine and healthcare

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Generating Radiology Reports via Memory-driven Transformer

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A visual–language foundation model for pathology image analysis using medical twitter

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PadChest: A large chest x-ray image dataset with multi-label annotated reports

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PubMedQA: A Dataset for Biomedical Research Question Answering

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Testing and Evaluation of Health Care Applications of Large Language Models: A Systematic Review

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On the Automatic Generation of Medical Imaging Reports

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ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission

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ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge

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Galactica: A Large Language Model for Science

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Assessing the Accuracy and Reliability of AI-Generated Medical Responses: An Evaluation of the Chat-GPT Model

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BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models

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BEHRT: Transformer for Electronic Health Records

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LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day

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LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day

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Evaluating Object Hallucination in Large Vision-Language Models

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Disparities in Health Care and the Digital Divide

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Assessing the Utility of ChatGPT Throughout the Entire Clinical Workflow: Development and Usability Study

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A study of generative large language model for medical research and healthcare

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Exploring the Boundaries of Reality: Investigating the Phenomenon of Artificial Intelligence Hallucination in Scientific Writing Through ChatGPT References

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Self-Alignment Pretraining for Biomedical Entity Representations

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Large Language Models in Medicine: The Potentials and Pitfalls

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CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison

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Large language models could change the future of behavioral healthcare: a proposal for responsible development and evaluation

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LinkBERT: Pretraining Language Models with Document Links

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Translating radiology reports into plain language using ChatGPT and GPT-4 with prompt learning: results, limitations, and potential

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Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Health

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Large language models are few-shot clinical information extractors

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Artificial intelligence in health care: accountability and safety

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COVID-Twitter-BERT: A natural language processing model to analyse COVID-19 content on Twitter

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Text Classification via Large Language Models

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BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains

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MentalBERT: Publicly Available Pretrained Language Models for Mental Healthcare

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A Survey of Knowledge Enhanced Pre-Trained Language Models

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HuatuoGPT, Towards Taming Language Model to Be a Doctor

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ChatGPT goes to the operating room: evaluating GPT-4 performance and its potential in surgical education and training in the era of large language models

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Trialling a Large Language Model (ChatGPT) in General Practice With the Applied Knowledge Test: Observational Study Demonstrating Opportunities and Limitations in Primary Care

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MedDialog: Large-scale Medical Dialogue Datasets

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Pretrained Language Models for Biomedical and Clinical Tasks: Understanding and Extending the State-of-the-Art

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Thirty years of the International Banff Classification for Allograft Pathology: the past, present, and future of kidney transplant diagnostics

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Evaluating large language models on a highly-specialized topic, radiation oncology physics

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Red teaming ChatGPT via Jailbreaking: Bias, Robustness, Reliability and Toxicity

Zhuo, T. Y., Huang, Y., Chen, C., & Xing, Z. (2023) · arXiv · doi:10.48550/arxiv.2301.12867 · Cited by 164 · see citing works

Improving chest X-ray report generation by leveraging warm starting

Nicolson, A., Dowling, J., & Koopman, B. (2023) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2023.102633 · Cited by 161 · see citing works

Analysis of large-language model versus human performance for genetics questions

Duong, D., & Solomon, B. D. (2024) · European Journal of Human Genetics · doi:10.1038/s41431-023-01396-8 · Cited by 159 · see citing works

MedMCQA : A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering

Pal, A., Umapathi, L. K., & Sankarasubbu, M. (2022) · arXiv · doi:10.48550/arxiv.2203.14371 · Cited by 157 · see citing works

Clinical concept extraction using transformers

Yang, X., Bian, J., Hogan, W. R., & Wu, Y. (2020) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaa189 · Cited by 155 · see citing works

Zhongjing: Enhancing the Chinese Medical Capabilities of Large Language Model through Expert Feedback and Real-World Multi-Turn Dialogue

Yang, S., Zhao, H., Zhu, S., Zhou, G., Hongfei, X., Jia, Y., & Zan, H. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i17.29907 · Cited by 145 · see citing works

Measuring algorithmically infused societies

Wagner, C., Strohmaier, M., Olteanu, A., Kıcıman, E., Contractor, N., & Eliassi-Rad, T. (2021) · Nature · doi:10.1038/s41586-021-03666-1 · Cited by 144 · see citing works

BioMegatron: Larger Biomedical Domain Language Model

Shin, H.-C., Zhang, Y., Bakhturina, E., Puri, R., Patwary, M. A., Shoeybi, M., & Mani, R. (2020) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2020.emnlp-main.379 · Cited by 142 · see citing works

BioBART: Pretraining and Evaluation of A Biomedical Generative Language Model

Yuan, H., Yuan, Z., Gan, R., Zhang, J., Xie, Y., & Yu, S. (2022) · Workshop on Biomedical Language Processing (BioNLP) · doi:10.18653/v1/2022.bionlp-1.9 · Cited by 142 · see citing works

Sources of Hallucination by Large Language Models on Inference Tasks

McKenna, N., Li, T., Cheng, L., Hosseini, M., Johnson, M., & Steedman, M. (2023) · Findings of the Association for Computational Linguistics: EMNLP 2023 · doi:10.18653/v1/2023.findings-emnlp.182 · Cited by 142 · see citing works

Bidirectional Representation Learning From Transformers Using Multimodal Electronic Health Record Data to Predict Depression

Meng, Y., Speier, W. F., Ong, M. K., & Arnold, C. W. (2021) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2021.3063721 · Cited by 137 · see citing works

Multiple Meta-model Quantifying for Medical Visual Question Answering

Do, T., Nguyen, B. X., Tjiputra, E., Tran, M. Q., Tran, Q. D., & Nguyen, A. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-87240-3_7 · Cited by 137 · see citing works

Are Large Pre-Trained Language Models Leaking Your Personal Information?

Huang, J., Shao, H., & Chang, K. C. (2022) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2022.findings-emnlp.148 · Cited by 135 · see citing works

Assessing the utility of ChatGPT throughout the entire clinical workflow

Rao, A., Pang, M., Kim, J., Kamineni, M., Lie, W., Prasad, A. K., Landman, A., Dreyer, K. J., & Succi, M. D. (2023) · doi:10.1101/2023.02.21.23285886 · Cited by 134 · see citing works

Evaluation of post-hoc interpretability methods in time-series classification

Turbé, H., Bjelogrlic, M., Lovis, C., & Mengaldo, G. (2023) · Nature Machine Intelligence · doi:10.1038/s42256-023-00620-w · Cited by 130 · see citing works

Deep Learning Techniques on Text Classification Using Natural Language Processing (NLP) In Social Healthcare Network: A Comprehensive Survey

Lavanya, P., & Sasikala, E. (2021) · doi:10.1109/icspc51351.2021.9451752 · Cited by 120 · see citing works

Word Embedding and WordNet Based Metaphor Identification and Interpretation

Mao, R., Lin, C., & Guérin, F. (2018) · Annual Meeting of the Association for Computational Linguistics (ACL) · doi:10.18653/v1/p18-1113 · Cited by 118 · see citing works

BioELECTRA:Pretrained Biomedical text Encoder using Discriminators

Kanakarajan, K. R., Kundumani, B., & Sankarasubbu, M. (2021) · Workshop on Biomedical Language Processing (BioNLP) · doi:10.18653/v1/2021.bionlp-1.16 · Cited by 118 · see citing works

MedAlpaca -- An Open-Source Collection of Medical Conversational AI Models and Training DataPreprint

Han, T., Adams, L. C., Papaioannou, J.-M., Grundmann, P., Oberhauser, T., Figueroa, A., Löser, A., Truhn, D., & Bressem, K. K. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2304.08247 · Cited by 117 · see citing works

CODER: Knowledge-infused cross-lingual medical term embedding for term normalization

Yuan, Z. P., Zhao, Z., Sun, H., Li, J., Wang, F., & Yu, S. (2022) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2021.103983 · Cited by 115 · see citing works

HuaTuo: Tuning LLaMA Model with Chinese Medical Knowledge

Wang, H., Liu, C., Xi, N., Qiang, Z., Zhao, S., Qin, B., & Liu, T. (2023) · arXiv · doi:10.48550/arxiv.2304.06975 · Cited by 115 · see citing works

On the Summarization of Consumer Health Questions

Abacha, A. B., & Demner-Fushman, D. (2019) · Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/p19-1215 · Cited by 114 · see citing works

Med-Flamingo: a Multimodal Medical Few-shot LearnerPreprint

Moor, M., Huang, Q., Wu, S., Yasunaga, M., Zakka, C., Dalmia, Y., Reis, E. P., Rajpurkar, P., & Leskovec, J. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2307.15189 · Cited by 111 · see citing works

Evaluating the use of large language model in identifying top research questions in gastroenterology

Lahat, A., Shachar, E., Avidan, B., Shatz, Z., Glicksberg, B. S., & Klang, E. (2023) · Scientific Reports · doi:10.1038/s41598-023-31412-2 · Cited by 111 · see citing works

Bidirectional Representation Learning From Transformers Using Multimodal Electronic Health Record Data to Predict Depression

Meng, Y., Speier, W. F., Ong, M. K., & Arnold, C. W. (2021) · eScholarship (California Digital Library) · Cited by 109 · see citing works

BioBERTpt - A Portuguese Neural Language Model for Clinical Named Entity Recognition

Schneider, E. T. R., de Souza, J. V. A., Knafou, J., Oliveira, L. E. S. E., Copara, J., Gumiel, Y. B., de Oliveira, L. F. A., Paraíso, E. C., Teodoro, D., & Barra, C. M. C. M. (2020) · Clinical Natural Language Processing Workshop (ClinicalNLP) · doi:10.18653/v1/2020.clinicalnlp-1.7 · Cited by 104 · see citing works

Text classification models for the automatic detection of nonmedical prescription medication use from social media

Al-Garadi, M. A., Yang, Y., Cai, H., Ruan, Y., O’Connor, K., Gonzalez‐Hernandez, G., Perrone, J., & Sarker, A. (2021) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-021-01394-0 · Cited by 104 · see citing works

BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairsPreprint

Zhang, S., Xu, Y., Usuyama, N., Xu, H., Bagga, J., Tinn, R., Preston, S., Rao, R. P. N., Wei, M., Valluri, N., et al. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2303.00915 · Cited by 102 · see citing works

MedICaT: A Dataset of Medical Images, Captions, and Textual References

Subramanian, S., Wang, L. L., Bogin, B., Mehta, S., van Zuylen, M., Parasa, S., Singh, S., Gardner, M., & Hajishirzi, H. (2020) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2020.findings-emnlp.191 · Cited by 94 · see citing works

Improving Biomedical Pretrained Language Models with Knowledge

Yuan, Z. P., Liu, Y., Tan, C., Huang, S., & Huang, F. (2021) · Workshop on Biomedical Language Processing (BioNLP) · doi:10.18653/v1/2021.bionlp-1.20 · Cited by 94 · see citing works

Impact of accountability, training, and human factors on the use of artificial intelligence in healthcare: Exploring the perceptions of healthcare practitioners in the US

Choudhury, A., & Asan, O. (2022) · Human Factors in Healthcare · doi:10.1016/j.hfh.2022.100021 · Cited by 93 · see citing works

A Survey of Knowledge Enhanced Pre-trained Language Models

Yang, J. K., Hu, X., Xiao, G., & Shen, Y. (2024) · ACM Transactions on Asian and Low-Resource Language Information Processing · doi:10.1145/3631392 · Cited by 89 · see citing works

Question-driven summarization of answers to consumer health questions

Savery, M. E., Abacha, A. B., Gayen, S., & Demner‐Fushman, D. (2020) · Scientific Data · doi:10.1038/s41597-020-00667-z · Cited by 88 · see citing works

The promise and peril of using a large language model to obtain clinical information: ChatGPT performs strongly as a fertility counseling tool with limitations

Chervenak, J., Lieman, H., Blanco-Breindel, M., & Jindal, S. (2023) · Fertility and Sterility · doi:10.1016/j.fertnstert.2023.05.151 · Cited by 87 · see citing works

ChatCAD+: Toward a Universal and Reliable Interactive CAD Using LLMs

Zhao, Z., Wang, S., Gu, J., Zhu, Y., Mei, L., Zhuang, Z., Cui, Z., Wang, Q., & Shen, D. G. (2024) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2024.3398350 · Cited by 83 · see citing works

DoctorGLM: Fine-tuning your Chinese Doctor is not a Herculean Task

Xiong, H., Wang, S., Zhu, Y., Zhao, Z., Liu, Y., Huang, L., Wang, Q., & Shen, D. (2023) · arXiv · doi:10.48550/arxiv.2304.01097 · Cited by 81 · see citing works

Conceptualized Representation Learning for Chinese Biomedical Text MiningPreprint

Zhang, N., Jia, Q., Yin, K., Liang, D., Gao, F., & Hua, N. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2008.10813 · Cited by 80 · see citing works

BioALBERT: A Simple and Effective Pre-trained Language Model for Biomedical Named Entity Recognition

Naseem, U., Khushi, M., Reddy, V. L., Rajendran, S., Razzak, I., & Kim, J. (2021) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn52387.2021.9533884 · Cited by 79 · see citing works

A Comparison of ChatGPT and Fine-Tuned Open Pre-Trained Transformers (OPT) Against Widely Used Sentiment Analysis Tools: Sentiment Analysis of COVID-19 Survey Data

Lossio-Ventura, J. A., Weger, R., Lee, A. Y., Guinee, E. P., Chung, J. Y., Atlas, L. Y., Linos, E., & Pereira, F. (2023) · JMIR Mental Health · doi:10.2196/50150 · Cited by 77 · see citing works

Has multimodal learning delivered universal intelligence in healthcare? A comprehensive survey

Lin, Q., Zhu, Y., Mei, X., Huang, L., Ma, J., He, K., Peng, Z., Cambria, E., & Feng, M. (2024) · Information Fusion · doi:10.1016/j.inffus.2024.102795 · Cited by 76 · see citing works

ChatCAD: Interactive Computer-Aided Diagnosis on Medical Image using Large Language ModelsPreprint

Wang, S., Zhao, Z., Ouyang, X., Wang, Q., & Shen, D. G. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2302.07257 · Cited by 74 · see citing works

Explainable Metaphor Identification Inspired by Conceptual Metaphor Theory

Ge, M., Mao, R., & Cambria, E. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v36i10.21313 · Cited by 73 · see citing works

SKIER: A Symbolic Knowledge Integrated Model for Conversational Emotion Recognition

Li, W., Zhu, L., Mao, R., & Cambria, E. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v37i11.26541 · Cited by 73 · see citing works

Highly accurate classification of chest radiographic reports using a deep learning natural language model pre-trained on 3.8 million text reports

Bressem, K. K., Adams, L. C., Gaudin, R., Troeltzsch, D., Hamm, B., Makowski, M. R., Schuele, C. Y., Vahldiek, J. L., & Niehues, S. M. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa668 · Cited by 70 · see citing works

HealAI: A Healthcare LLM for Effective Medical Documentation

Goyal, S., Rastogi, E., Rajagopal, S. P., Yuan, D., Zhao, F., Chintagunta, J., Naik, G., & Ward, J. (2024) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/3616855.3635739 · Cited by 70 · see citing works

Benchmarking for biomedical natural language processing tasks with a domain specific ALBERT

Naseem, U., Dunn, A. G., Khushi, M., & Kim, J. (2022) · BMC Bioinformatics · doi:10.1186/s12859-022-04688-w · Cited by 68 · see citing works

Structured information extraction from complex scientific text with fine-tuned large language models

Dunn, A., Dagdelen, J., Walker, N., Lee, S., Rosen, A. S., Ceder, G., Persson, K., & Jain, A. (2022) · arXiv · doi:10.48550/arxiv.2212.05238 · Cited by 67 · see citing works

A medical question answering system using large language models and knowledge graphs

Guo, Q., Cao, S., & Zhang, Y. (2022) · International Journal of Intelligent Systems · doi:10.1002/int.22955 · Cited by 65 · see citing works

Virtual prompt pre-training for prototype-based few-shot relation extraction

He, K., Huang, Y., Mao, R., Gong, T., Li, C., & Cambria, E. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.118927 · Cited by 65 · see citing works

A clinical specific BERT developed using a huge Japanese clinical text corpus

Kawazoe, Y., Shibata, D., Shinohara, E., Aramaki, E., & Ohe, K. (2021) · PLoS ONE · doi:10.1371/journal.pone.0259763 · Cited by 62 · see citing works

Me-LLaMA: Foundation Large Language Models for Medical ApplicationsPreprint

Xie, Q., Chen, Q., Chen, A., Cheng, P., Hu, Y., Lin, F., Peng, X., Huang, J., Zhang, J., Keloth, V. K., et al. (2024) · Research Square · doi:10.21203/rs.3.rs-4240043/v1 · Cited by 62 · see citing works

Medical Text Classification Using Hybrid Deep Learning Models with Multihead Attention

Prabhakar, S. K., & Won, D.-O. (2021) · Computational Intelligence and Neuroscience · doi:10.1155/2021/9425655 · Cited by 61 · see citing works

Clinical XLNet: Modeling Sequential Clinical Notes and Predicting Prolonged Mechanical Ventilation

Huang, K., Singh, A., Chen, S., Moseley, E. T., Deng, C.-Y., George, N. R., & Lindvall, C. (2020) · Clinical Natural Language Processing Workshop (ClinicalNLP) · doi:10.18653/v1/2020.clinicalnlp-1.11 · Cited by 57 · see citing works

Automated Lay Language Summarization of Biomedical Scientific Reviews

Guo, Y., Qiu, W., Wang, Y., & Cohen, T. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i1.16089 · Cited by 54 · see citing works

ABioNER: A BERT‐Based Model for Arabic Biomedical Named‐Entity Recognition

Boudjellal, N., Zhang, H., Khan, A., Ahmad, A., Naseem, R., Shang, J., & Dai, L. (2021) · Complexity · doi:10.1155/2021/6633213 · Cited by 54 · see citing works

ClinicalGPT: Large Language Models Finetuned with Diverse Medical Data and Comprehensive Evaluation

Wang, G., Yang, G., Du, Z., Fan, L., & Li, X. (2023) · arXiv · doi:10.48550/arxiv.2306.09968 · Cited by 53 · see citing works

Enhancing Clinical BERT Embedding using a Biomedical Knowledge Base

Hao, B., Zhu, H., & Paschalidis, I. C. (2020) · International Conference on Computational Linguistics · doi:10.18653/v1/2020.coling-main.57 · Cited by 51 · see citing works

Proceedings of the 20th Workshop on Biomedical Language Processing

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Proceedings of the 3rd Clinical Natural Language Processing Workshop

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MedGPT: Medical Concept Prediction from Clinical NarrativesPreprint

Kraljević, Ž., Shek, A., Bean, D. M., Bendayan, R., Teo, J., & Dobson, R. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2107.03134 · Cited by 49 · see citing works

Contextualized French Language Models for Biomedical Named Entity Recognition

Copara, J., Knafou, J., Naderi, N., Moro, C. M. C., Ruch, P., & Teodoro, D. (2020) · ArODES (HES-SO (https://www.hes-so.ch/)) · Cited by 46 · see citing works

Preliminary Study on the Knowledge Graph Construction of Chinese Ancient History and Culture

Liu, S., Yang, H., Li, J., & Kolmanič, S. (2020) · Information · doi:10.3390/info11040186 · Cited by 46 · see citing works

Cloud-based intelligent self-diagnosis and department recommendation service using Chinese medical BERT

Wang, J., Zhang, G., Wang, W., Ka, Z., & Sheng, Y. (2021) · Journal of Cloud Computing Advances Systems and Applications · doi:10.1186/s13677-020-00218-2 · Cited by 45 · see citing works

Evaluation of ChatGPT on Biomedical Tasks: A Zero-Shot Comparison with Fine-Tuned Generative Transformers

Jahan, I., Laskar, M. T. R., Peng, C., & Huang, J. X. (2023) · Workshop on Biomedical Language Processing (BioNLP) · doi:10.18653/v1/2023.bionlp-1.30 · Cited by 45 · see citing works

Detecting Causal Language Use in Science Findings

Yu, B., Li, Y., & Wang, J. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · doi:10.18653/v1/d19-1473 · Cited by 40 · see citing works

Inexpensive Domain Adaptation of Pretrained Language Models: Case Studies on Biomedical NER and Covid-19 QA

Poerner, N., Waltinger, U., & Schütze, H. (2020) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2020.findings-emnlp.134 · Cited by 40 · see citing works

MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for MedicinePreprint

Xie, Y., Zhou, C., Gao, L., Wu, J., Li, X., Zhou, H.-Y., Liu, S., Xing, L., Zou, J., Xie, C., et al. (2024) · arXiv (Cornell University) · doi:10.48550/arxiv.2408.02900 · Cited by 37 · see citing works

Transformers for Clinical Coding in Spanish

López-García, G., Jerez, J. M., Ribelles, N., Alba, E., & Veredas, F. J. (2021) · IEEE Access · doi:10.1109/access.2021.3080085 · Cited by 36 · see citing works

Read, Diagnose and Chat: Towards Explainable and Interactive LLMs-Augmented Depression Detection in Social MediaPreprint

Qin, W., Chen, Z., Wang, L., Lan, Y., Ren, W., & Hong, R. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2305.05138 · Cited by 35 · see citing works

Qilin-Med: Multi-stage Knowledge Injection Advanced Medical Large Language ModelPreprint

Ye, Q., Liu, J., Chong, D., Zhou, P., Hua, Y., Liu, F., Cao, M., Wang, Z., Cheng, X., Zhu, L., et al. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2310.09089 · Cited by 35 · see citing works

Semantic matching in machine reading comprehension: An empirical study

Liu, Q., Mao, R., Geng, X., & Cambria, E. (2022) · Information Processing & Management · doi:10.1016/j.ipm.2022.103145 · Cited by 34 · see citing works

PROMISE: A pre-trained knowledge-infused multimodal representation learning framework for medication recommendation

Wu, J., Yu, X., He, K., Gao, Z., & Gong, T. (2024) · Information Processing & Management · doi:10.1016/j.ipm.2024.103758 · Cited by 34 · see citing works

BiMediX: Bilingual Medical Mixture of Experts LLM

Pieri, S., Mullappilly, S. S., Khan, F. S., Anwer, R. M., Khan, S., Baldwin, T., & Cholakkal, H. (2024) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2024.findings-emnlp.989 · Cited by 34 · see citing works

Understanding the patient perspective of epilepsy treatment through text mining of online patient support groups

He, K., Hong, N., Lapalme‐Remis, S., Lan, Y., Huang, M. S., Li, C., & Yao, L. (2019) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2019.02.002 · Cited by 33 · see citing works

Modified Bidirectional Encoder Representations From Transformers Extractive Summarization Model for Hospital Information Systems Based on Character-Level Tokens (AlphaBERT): Development and Performance Evaluation

Chen, Y.-P., Chen, Y.-P., Lin, J.-J., Huang, C., & Lai, F. (2020) · JMIR Medical Informatics · doi:10.2196/17787 · Cited by 33 · see citing works

Named Entity Recognition in Spanish Biomedical Literature: Short Review and Bert Model

Akhtyamova, L. (2020) · Conference of Open Innovations Association (FRUCT) · doi:10.23919/fruct48808.2020.9087359 · Cited by 33 · see citing works

GatorTron: A Large Language Model for Clinical Natural Language Processing

Yang, X., PourNejatian, N., Shin, H. C., Smith, K. E., Parisien, C., Compas, C., Martin, C., Flores, M. G., Zhang, Y., Magoc, T., et al. (2022) · doi:10.1101/2022.02.27.22271257 · Cited by 33 · see citing works

Feature-Weighted Counterfactual-Based Explanation for Bankruptcy Prediction

Cho, S. H., & Shin, K.-S. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.119390 · Cited by 32 · see citing works

CancerLLM: a large language model in cancer domain

Li, M., Zhan, Z., Huang, J., Yeung, J., Ding, K., Blaes, A. H., Johnson, S., Liu, H., Xu, H., & Zhang, R. (2026) · npj Digital Medicine · doi:10.1038/s41746-026-02441-8 · Cited by 32 · see citing works

JMLR: Joint Medical LLM and Retrieval Training for Enhancing Reasoning and Professional Question Answering CapabilityPreprint

Wang, J., Yang, Z., Yao, Z., & Yu, H. Z. (2024) · arXiv (Cornell University) · doi:10.48550/arxiv.2402.17887 · Cited by 32 · see citing works

GenCompareSum: a hybrid unsupervised summarization method using salience

Bishop, J. A., Xie, Q., & Ananiadou, S. (2022) · Workshop on Biomedical Natural Language Processing · doi:10.18653/v1/2022.bionlp-1.22 · Cited by 31 · see citing works

Leveraging remote behavioral health interventions to improve medical outcomes and reduce costs.

Pande, R. L., Morris, M., Peters, A., Spettell, C. M., Feifer, R. A., & Gillis, W. (2015) · PubMed · Cited by 31 · see citing works

Testing Contextualized Word Embeddings to Improve NER in Spanish Clinical Case Narratives

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Identification of Semantically Similar Sentences in Clinical Notes: Iterative Intermediate Training Using Multi-Task Learning

Mahajan, D., Poddar, A., Liang, J. J., Lin, Y.-T. R., Prager, J. M., Suryanarayanan, P., Raghavan, P., & Tsou, C.-H. (2020) · JMIR Medical Informatics · doi:10.2196/22508 · Cited by 29 · see citing works

Construction of Genealogical Knowledge Graphs From Obituaries: Multitask Neural Network Extraction System

He, K., Yao, L., Zhang, J., Li, Y., & Li, C. (2021) · Journal of Medical Internet Research · doi:10.2196/25670 · Cited by 29 · see citing works

BioFLAIR: Pretrained Pooled Contextualized Embeddings for Biomedical Sequence Labeling TasksPreprint

Sharma, S., & Daniel, R. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1908.05760 · Cited by 28 · see citing works

How Ready are Pre-trained Abstractive Models and LLMs for Legal Case Judgement Summarization?

Deroy, A., Ghosh, K., & Ghosh, S. (2023) · arXiv · doi:10.48550/arxiv.2306.01248 · Cited by 27 · see citing works

ELECTRAMed: a new pre-trained language representation model for biomedical NLPPreprint

Miolo, G., Mantoan, G., & Orsenigo, C. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2104.09585 · Cited by 26 · see citing works

COMETA: A Corpus for Medical Entity Linking in the Social Media

Basaldella, M., Liu, F., Shareghi, E., & Collier, N. (2020) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2020.emnlp-main.253 · Cited by 24 · see citing works

MISS: A Generative Pre-training and Fine-Tuning Approach for Med-VQA

Chen, J., Yang, D., Jiang, Y., Lei, Y., & Zhang, L. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72353-7_22 · Cited by 23 · see citing works

Automatic Multi-Label Prompting: Simple and Interpretable Few-Shot Classification

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Aloe: A Family of Fine-tuned Open Healthcare LLMsPreprint

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Polaris: A Safety-focused LLM Constellation Architecture for Healthcare

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OphGLM: Training an Ophthalmology Large Language-and-Vision Assistant based on Instructions and DialoguePreprint

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Path to Medical AGI: Unify Domain-specific Medical LLMs with the Lowest CostPreprint

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OncoGPT: A Medical Conversational Model Tailored with Oncology Domain Expertise on a Large Language Model Meta-AI (LLaMA)Preprint

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KART: Parameterization of Privacy Leakage Scenarios from Pre-trained Language ModelsPreprint

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Multi-Atlas Brain Network Classification Through Consistency Distillation and Complementary Information Fusion

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Contrasformer: A Brain Network Contrastive Transformer for Neurodegenerative Condition Identification

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Large Language Models in Healthcare and Medical Applications: A Review

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Enabling large language models for real-world materials discovery

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Explainable Artificial Intelligence: A Perspective on Drug Discovery

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Comparing Diagnostic Accuracy of Clinical Professionals and Large Language Models: Systematic Review and Meta-Analysis

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A comprehensive survey of Vision–Language Models: Pretrained models, fine-tuning, prompt engineering, adapters, and benchmark datasets

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Harnessing the potential of multimodal EHR data: A comprehensive survey of clinical predictive modeling for intelligent healthcare

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Large Language Models in Genomics—A Perspective on Personalized Medicine

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Safety of a large language model-based clinical decision support system in African primary healthcare

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Large Language Model Symptom Identification From Clinical Text: Multicenter Study

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A Systematic Review of Large Language Models in Mental Health: Opportunities, Challenges, and Future Directions

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An Evaluation of Large Language Models for Supplementing a Food Extrusion Dataset

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Enhancing Clinical Decision Support and EHR Insights through LLMs and the Model Context Protocol: An Open-Source MCP-FHIR Framework

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Cross-Modal Knowledge Diffusion-Based Generation for Difference-Aware Medical VQA

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LLM4DEU: Fine Tuning Large Language Model for Medical Diagnosis in Outpatient and Emergency Department Visits of Neurosurgery

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Trending Applications of Large Language Models: A User Perspective Survey

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Generalist models in medical image segmentation: A survey and performance comparison with task-specific approaches

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PhenoDP: leveraging deep learning for phenotype-based case reporting, disease ranking, and symptom recommendation

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A survey for wearable sensors empowering smart healthcare in the era of large language models

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On the Vulnerability of LLM/VLM-Controlled Robotics

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EH-Benchmark: Ophthalmic hallucination benchmark and agent-driven top-down traceable reasoning workflow

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The eye as a window to systemic health: A survey of retinal imaging from classical techniques to oculomics

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A survey on electronic health record driven multimodal representation learning

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Evaluating Large Language Models in Cardiology: A Comparative Study of ChatGPT, Claude, and Gemini

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Integrating statistical design and inference: A roadmap for robust and trustworthy medical AI

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Generative multimodal large language models in mental health care: Applications, opportunities, and challenges

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Do ethical AI principles matter to users? A large-scale analysis of user sentiment and satisfaction

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Implicit bias in safety-aligned large language models: A multi-faceted evaluation of clinical decision-making and health equity

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Empathy by Design: Aligning Large Language Models for Healthcare Dialogue

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ToPoFM: Topology-Guided Pathology Foundation Model for High-Resolution Pathology Image Synthesis With Cellular-Level Control

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Metamorphic Testing for Robustness and Fairness Evaluation of LLM-based Automated ICD Coding Applications

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Incorporating Large Vision Model Distillation and Fuzzy Perception for Improving Disease Diagnosis

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Personalized News Recommendation Towards the Era of LLMs: Review and Prospect

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Multi-Agent Retrieval Augmented Generation for Clinical Decision Support: A Systematic Review and Integrative Conceptual Framework

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Institutionalizing convergence education for medical artificial intelligence

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Validating large language models against manual information extraction from case reports of drug-induced parkinsonism in patients with schizophrenia spectrum and mood disorders: a proof of concept study

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Visible light human activity recognition driven by generative language model

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TAKECare: A temporal-hierarchical framework with knowledge fusion for personalized clinical predictive modeling

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A LangChain-based pipeline for one-shot synthetic text generation using generative pre-trained transformers in palliative care research

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Large Language Models for Explainable Medical Text Summarization: A Systematic Literature Review

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Responsible AI in healthcare: Mitigating hallucinations and enhancing multimodal fusion - based reasoning in medical imaging

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Incorporating Molecular Knowledge in Large Language Models via Multimodal Modeling

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Correctness Coverage Evaluation for Medical Multiple-Choice Question Answering Based on the Enhanced Conformal Prediction Framework

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Foundation Model for Medical Imaging: A Comprehensive Review

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Exploring the Commercial Trajectories of LLMs: Business Models and Advertising Perspectives

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PGmark : Enhancing text quality in language model watermarking via probability guidance

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A Comparative Study of Decoding Strategies in Medical Text Generation

Presacan, O., Nik, A., Thambawita, V. L., Ionescu, B., & Riegler, M. A. (2026) · Lecture notes in computer science · doi:10.1007/978-981-95-6957-1_1 · Cited by 2 · see citing works

Assessing open LLMs’ ability to identify biomedical taxonomic relationships: A SNOMED CT-based experimental evaluation

Serrano, J. D. A., Caño-Marín, E., & Sicilia, M. (2026) · Knowledge-Based Systems · doi:10.1016/j.knosys.2026.115882 · Cited by 2 · see citing works

Exploring Human-Machine Dynamics: How Do Users Understand and Adapt to the Moral Risks in Healthcare Generative AI Chatbots?

Yang, Y., Qi, J., & Ji, X. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2683905 · Cited by 2 · see citing works

Multi-agent Assessment Generation System for SBIRT Training in Nursing

Godbole, M. S., Garg, A., Seo, J. H., Thai, L., Kroll, N. P., Weston, C., Bruce, C., & Wells-Beede, E. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-93508-4_2 · Cited by 2 · see citing works

MotionAnimate: Animate human images with pose motion for vivid and temporally consistent video generation

Wang, R., Wang, S., Gong, R., Cai, C., Gao, J., Wang, W., Liu, W., & Yap, K. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.103559 · Cited by 2 · see citing works

Learning to Diagnose Privately: DP-Powered LLMs for Radiology Report Classification

Bhattacharjee, P., Tian, F., Rubin, G. D., Lo, J. Y.-C., Merchant, N. C., Hanson, H. A., Gounley, J. P., & Tandon, R. (2026) · IEEE Access · doi:10.1109/access.2026.3679277 · Cited by 2 · see citing works

Benchmarking LLM-based Information Extraction Tools for Medical DocumentsPreprint

Yu, A., Weile, J., & Courtot, M. (2026) · medRxiv · doi:10.64898/2026.01.19.26344287 · Cited by 2 · see citing works

Enhancing Patient Intake Process in Mental Health Consultations Using RAG-Driven Chatbot

Shayaninasab, M., Zahoor, M., & Yalçın, Ö. N. (2024) · International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) · doi:10.1109/aciiw63320.2024.00053 · Cited by 1 · see citing works

Fine-Tuning LLMs for Anesthesiology via Compositional Data Generation

Li, Y., Zhan, Y., Yu, B., Wang, Z., Zhang, C., Zhu, D., Zhou, C., Zhou, B., Ding, L., Liu, W., et al. (2025) · IEEE Transactions on Emerging Topics in Computational Intelligence · doi:10.1109/tetci.2025.3567602 · Cited by 1 · see citing works

External Retrievals or Internal Priors? From RAG to Epitome-Augmented Generation by Fuzzy Selection

He, K., Xu, J., Lin, Q., Wang, W., Gao, Z., Wu, J., Huang, Y., & Feng, M. (2025) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2025.3581205 · Cited by 1 · see citing works

An Embodied AR Navigation Agent: Integrating BIM with Retrieval-Augmented Generation for Language Guidance

Yang, H.-K., Hsiao, T.-C., Oka, R., Nishino, R., Tofukuji, S., & Kobori, N. (2025) · Proceedings - International Symposium on Mixed and Augmented Reality, ISMAR · doi:10.1109/ismar67309.2025.00150 · Cited by 1 · see citing works

Learning to Follow Domain-specific Instruction with Verifiable Rewards

Huang, S., Liu, Y., Qi, J., Yang, H., Luan, Z., & Qian, D. (2025) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn64981.2025.11228901 · Cited by 1 · see citing works

Ethical challenges in scene understanding for public health AI

Qi, Y., & Zhao, Z. (2025) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1685813 · Cited by 1 · see citing works

Multiple Confabulations Found in Bioinformatics Tasks Carried Out by Several Free Large Language Models

Forero, D. A. (2026) · Current Genomics · doi:10.2174/0113892029403403260112075225 · Cited by 1 · see citing works

Detecting cyber employment fraud in platform-based space: A multi-agent large language model approach

Quan, S., Wu, L., Ye, X., Lee, C., Li, W., & Liu, C. (2026) · Journal of Criminal Justice · doi:10.1016/j.jcrimjus.2026.102692 · Cited by 1 · see citing works

CGX: OCR-enhanced knowledge graph retrieval for explainable heart failure analysis

Nguyen, D. T., Le, A. N., Trinh, B. T., Vu, D. B., & Nguyen, H. N. (2026) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2026.105089 · Cited by 1 · see citing works

Review of Language Models in the Financial Domain

Wagh, A., & Mavle, A. (2024) · Intelligent Systems and Machine Learning Conference (ISML) · doi:10.1109/isml60050.2024.11007354 · Cited by 1 · see citing works

KPVG: Knowledge-prompted vision-genomics model for cancer survival prediction in whole slide images

Shi, J., Li, C., Zheng, Y., & Fu, H. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.103660 · Cited by 1 · see citing works

Knowledge intensive agents

Liu, Z., Huang, P., Xu, Z., Li, X., Liu, S., Peng, C., Xin, H., Yan, Y., Wang, S., Han, X., et al. (2026) · AI Open · doi:10.1016/j.aiopen.2026.02.002 · Cited by 1 · see citing works

A large-language-model-guided progressive error-correction framework for structured process modeling

Xu, R., Fang, H., Fang, W., Wang, F., & Zhao, C. (2026) · Expert Systems with Applications · doi:10.1016/j.eswa.2026.131998 · Cited by 1 · see citing works

ChatPreference: a large language model for customer preference understanding in the apparel industry

Cheng, Y., Li, H., Zhao, Z., & Huang, G. Q. (2026) · Journal of Engineering Design · doi:10.1080/09544828.2026.2655935 · Cited by 1 · see citing works

Boundary-Aware Collaborative Mixture-of-Experts Architecture for Fetal Brain Anatomical Segmentation

Li, J., Gao, Z., Chen, G., Lin, Q., Wang, C., & Li, K. (2026) · IEEE Transactions on Consumer Electronics · doi:10.1109/tce.2026.3683680 · Cited by 1 · see citing works

AI in Psychotherapy: Opportunities and Risks

Neacşu, V. (2026) · Behavioral Sciences · doi:10.3390/bs16050676 · Cited by 1 · see citing works

BiSSM-CL: Enhanced multimodal emotion recognition in conversation with bidirectional state space model and collaborative learning

Li, F., Wang, M., Yang, Y., Zhang, F., Chen, Z., & Li, H. (2026) · Information Fusion · doi:10.1016/j.inffus.2026.104455 · Cited by 1 · see citing works

Intelligent documentation in medical education: can AI replace manual case logging?

Khan, N. I., Cleland, K., Filkov, V., & Goldman, R. E. (2026) · JAMIA Open · doi:10.1093/jamiaopen/ooag067 · Cited by 1 · see citing works

BigOrthoATD.Net: A scalable and adaptable distributed deep learning framework for multi-class orthopedic classification across imaging modalities in low-resourced settings

Alwzwazy, H. A., Alzubaidi, L., Zhao, Z., Crawford, R., Alnaseri, O., Jurdak, R., & Gu, Y. (2026) · Neural Networks · doi:10.1016/j.neunet.2026.109190 · Cited by 1 · see citing works

Applications of DeepSeek in Medicine: Bibliometric Analysis and Scoping Review

Zhang, H., Wang, D., Xu, Y., Han, S., & Wang, G. (2026) · Journal of Medical Internet Research · doi:10.2196/93354 · Cited by 1 · see citing works

A Large Language Model Pipeline for Stroke Staging Using Electronical Medical Records

Luo, X., Liu, Y., Yk, M., Li, C., Yao, M., Xiang, H., Qin, X., Liu, J., Zhan, X., Zhang, C., et al. (2026) · Journal of Evidence-Based Medicine · doi:10.1111/jebm.70159 · Cited by 1 · see citing works

MV-MoE: A multi-view mixture-of-expert tuning method for medical LLMs

Zhang, W., Yan, Y., Wang, J., Wu, X., Yuan, C., & Ruan, T. (2026) · Expert Systems with Applications · doi:10.1016/j.eswa.2026.133593 · Cited by 1 · see citing works

A survey of LLM reasoning in healthcare and medicine: Individual modeling and collaborative agents

Lin, Q., Xiao, L., Pu, B., Shi, K., Du, Y., Xu, J., He, K., Zhao, S., Zhang, J., Cambria, E., et al. (2026) · Information Fusion · doi:10.1016/j.inffus.2026.104827 · Cited by 1 · see citing works

Optimized Deep Learning for Multi-Class Retinal Disease Classification Using ResNet-101

Babu, K. S., Saranya, G., Santhoshkumar, K., Babu, T., Thirumala, M. V., & Venkatareddy, D. (2024) · IEEE International Conference for Women in Computing (InCoWoCo) · doi:10.1109/incowoco64194.2024.10863808

CLPCare: Bootstrapping Multimodal Large Language Models for Ultrasound Cleft Lip and Palate Recognition and Analysis

Wang, J., Luo, G., Yan, H., Huang, S., Liao, Z., Zhang, S., Wu, J., He, X., & Chen, L. (2024) · IEEE Smart World Congress (SWC) · doi:10.1109/swc62898.2024.00153

Comparative Analysis and Evaluation of Well-Being Activity-Infused Fine-Tuned Language Models with Benchmark Models

Mohammed, H. H., Kiss, G. H., Serrano, J. A., & Lindseth, F. (2025) · doi:10.1109/cihm64979.2025.10969481

Experimentos en apertura y consciencia: modificando aspectos de personalidad con MML y prompting

Meza, I., García, I. V., & Castro, O. R. G. (2025) · TIES Revista de Tecnología e Innovación en Educación Superior · doi:10.22201/dgtic.26832968e.2025.12.74

Fine-Tuning Large Language Models With Behavioral Alignment for Depression Detection

Ning, X., Sun, H., Yu, D., Yang, C., Fang, R., Fan, L., Lin, Q., & Zhu, Y. (2025) · IEEE Intelligent Systems · doi:10.1109/mis.2025.3584888

A Survey on Using Large Language Models in Healthcare

(2025) · International Journal of Science and Engineering Applications · doi:10.7753/ijsea1406.1001 · Cited by 2 · see citing works

Large Language Models in Healthcare and Medical Applications: A Review

Maity, S., & Saikia, M. J. (2025) · Bioengineering · doi:10.3390/bioengineering12060631 · Cited by 249 · see citing works

Large language models in healthcare and medical domain: A reviewPreprint

Nazi, Z. A., & Peng, W. (2023) · Informatics · doi:10.48550/arxiv.2401.06775 · Cited by 551 · see citing works

Applications and Future Prospects of Large Language Models in Healthcare

Zilin, C. H. E. N., Zhu, F., Yuxin, L. U. O., ZHANG, W., & Long, L. U. (2025) · DOAJ (DOAJ: Directory of Open Access Journals) · doi:10.12014/j.issn.1002-0772.2025.12.07

The Role of Language Models in Modern Healthcare: A Comprehensive ReviewPreprint

Khalid, A., Khalid, A., & Khalid, U. (2024) · arXiv (Cornell University) · doi:10.48550/arxiv.2409.16860 · Cited by 3 · see citing works