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An Empirical Study of Multi-Task Learning on BERT for Biomedical Text Mining

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Data Harmonization for Heterogeneous Datasets: A Systematic Literature Review

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Automatic ICD-10 Coding and Training System: Deep Neural Network Based on Supervised Learning

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

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Biolord-2023: Semantic textual representations fusing large language models and clinical knowledge graph insights

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A hybrid approach of Weighted Fine-Tuned BERT extraction with deep Siamese Bi – LSTM model for semantic text similarity identification

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A pre-trained BERT for Korean medical natural language processing

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The 2019 n2c2/OHNLP Track on Clinical Semantic Textual Similarity: Overview

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Measurement of Semantic Textual Similarity in Clinical Texts: Comparison of Transformer-Based Models

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Differential Privacy for Text Analytics via Natural Text Sanitization

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Pre-trained language models in medicine: A survey

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Predicting ICD-9 code groups with fuzzy similarity based supervised multi-label classification of unstructured clinical nursing notes

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Predicting Semantic Similarity Between Clinical Sentence Pairs Using Transformer Models: Evaluation and Representational Analysis

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A deep database of medical abbreviations and acronyms for natural language processing

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A survey for large language models in biomedicine

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Review: Privacy-Preservation in the Context of Natural Language Processing

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GPT-3 Models are Poor Few-Shot Learners in the Biomedical DomainPreprint

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Pre-trained Language Models in Biomedical Domain: A Systematic SurveyPreprint

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Evaluating sentence representations for biomedical text: Methods and experimental results

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MNIST Handwritten Digit Classification Based on Convolutional Neural Network with Hyperparameter Optimization

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A Customized Text Sanitization Mechanism with Differential Privacy

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Semantic Textual Similarity in Japanese Clinical Domain Texts Using BERT

Mutinda, F. W., Yada, S., Wakamiya, S., & Aramaki, E. (2021) · Methods of Information in Medicine · doi:10.1055/s-0041-1731390 · Cited by 30

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

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CharacterBERT: Reconciling ELMo and BERT for Word-Level Open-Vocabulary Representations From CharactersPreprint

Boukkouri, H. E., Ferret, O., Lavergne, T., Noji, H., Zweigenbaum, P., & Tsujii, J. (2020) · International Conference on Computational Linguistics · doi:10.48550/arxiv.2010.10392 · Cited by 189

GatorTron: A Large Language Model for Clinical Natural Language Processing

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Adapting Bidirectional Encoder Representations from Transformers (BERT) to Assess Clinical Semantic Textual Similarity: Algorithm Development and Validation Study

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Uncertainty Estimation and Reduction of Pre-trained Models for Text Regression

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Measuring semantic similarity of clinical trial outcomes using deep pre-trained language representations

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A Novel Approach for Semantic Extractive Text Summarization

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Deep learning with sentence embeddings pre-trained on biomedical corpora improves the performance of finding similar sentences in electronic medical records

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Family History Extraction From Synthetic Clinical Narratives Using Natural Language Processing: Overview and Evaluation of a Challenge Data Set and Solutions for the 2019 National NLP Clinical Challenges (n2c2)/Open Health Natural Language Processing (OHNLP) Competition

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Learning from Unlabelled Data for Clinical Semantic Textual Similarity

Wang, Y., Verspoor, K. M., & Baldwin, T. (2020) · Clinical Natural Language Processing Workshop (ClinicalNLP) · doi:10.18653/v1/2020.clinicalnlp-1.25 · Cited by 22

Oversampling effect in pretraining for bidirectional encoder representations from transformers (BERT) to localize medical BERT and enhance biomedical BERT

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Benchmarking Effectiveness and Efficiency of Deep Learning Models for Semantic Textual Similarity in the Clinical Domain: Validation Study

Chen, Q., Rankine, A., Peng, Y., Aghaarabi, E., & Lu, Z. (2021) · JMIR Medical Informatics · doi:10.2196/27386 · Cited by 21

A Pre-Training Technique to Localize Medical BERT and to Enhance Biomedical BERTPreprint

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Estimating redundancy in clinical text

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Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations

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The Potential of AI in Care Optimization: Insights from the User-Driven Co-Development of a Care Integration System

Schneider‐Kamp, A. (2021) · INQUIRY The Journal of Health Care Organization Provision and Financing · doi:10.1177/00469580211017992 · Cited by 20

Leveraging large language models to mimic domain expert labeling in unstructured text-based electronic healthcare records in non-english languages

Akbasli, I. T., Bırbılen, A. Z., & Tekşam, Ö. (2025) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-025-02871-6 · Cited by 18

Improving the robustness and accuracy of biomedical language models through adversarial training

Moradi, M., & Samwald, M. (2022) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2022.104114 · Cited by 18

Incorporating Domain Knowledge Into Language Models by Using Graph Convolutional Networks for Assessing Semantic Textual Similarity: Model Development and Performance Comparison

Chang, D., Lin, E. C., Brandt, C., & Taylor, R. A. (2021) · JMIR Medical Informatics · doi:10.2196/23101 · Cited by 18

Evaluating the Utility of Model Configurations and Data Augmentation on Clinical Semantic Textual Similarity

Wang, Y., Liu, F., Verspoor, K. M., & Baldwin, T. (2020) · Workshop on Biomedical Language Processing (BioNLP) · doi:10.18653/v1/2020.bionlp-1.11 · Cited by 16

Quality assessment of functional status documentation in EHRs across different healthcare institutions

Fu, S., Vassilaki, M., Ibrahim, O. A., Petersen, R. C., Pagali, S., St Sauver, J., Moon, S., Wang, L., Fan, J. W., Liu, H., et al. (2022) · Frontiers in Digital Health · doi:10.3389/fdgth.2022.958539 · Cited by 15

BioLORD: Learning Ontological Representations from Definitions for Biomedical Concepts and their Textual Descriptions

Remy, F., Demuynck, K., & Demeester, T. (2022) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2022.findings-emnlp.104 · Cited by 23

Pre-training technique to localize medical BERT and enhance biomedical BERTPreprint

Wada, S., Takeda, T., Manabe, S., Konishi, S., Kamohara, J., & Matsumura, Y. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2005.07202 · Cited by 32

Semantic Textual Similarity Analysis of Clinical Text in the Era of LLM

Feng, Y. (2024) · IEEE Conference on Artificial Intelligence (CAI) · doi:10.1109/cai59869.2024.00227 · Cited by 15

Unsupervised Event Graph Representation and Similarity Learning on Biomedical Literature

Frisoni, G., Moro, G., Carlassare, G., & Carbonaro, A. (2021) · Sensors · doi:10.3390/s22010003 · Cited by 14

TAGS: Towards Automated Classification of Unstructured Clinical Nursing Notes

Gangavarapu, T., Jayasimha, A., Krishnan, G. S., & Kamath, S. S. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-23281-8_16 · Cited by 14

Using Character-Level and Entity-Level Representations to Enhance Bidirectional Encoder Representation From Transformers-Based Clinical Semantic Textual Similarity Model: ClinicalSTS Modeling Study

Xiong, Y., Chen, S., Chen, Q., Yan, J., & Tang, B. (2020) · JMIR Medical Informatics · doi:10.2196/23357 · Cited by 11

Quantifying semantic similarity of clinical evidence in the biomedical literature to facilitate related evidence synthesis

Hassanzadeh, H., Nguyen, A. N., & Verspoor, K. M. (2019) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2019.103321 · Cited by 12

A Comparative Analysis of Temporal Long Text Similarity: Application to Financial Documents

Rawte, V., Gupta, A., & Zaki, M. J. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-66981-2_7 · Cited by 11

Selected articles from the BioCreative/OHNLP challenge 2018

Liu, S., Wang, Y., & Liu, H. (2019) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-019-0994-6 · Cited by 10

Querying Across Genres for Medical Claims in News

Zuo, C., Acharya, N., & Banerjee, R. (2020) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2020.emnlp-main.139 · Cited by 10

Leveraging Grammatical Roles for Measuring Semantic Similarity Between Texts

Atabuzzaman, M., Shajalal, M., Ahmed, M. E., Afjal, M. I., & Aono, M. (2021) · IEEE Access · doi:10.1109/access.2021.3074747 · Cited by 10

A text style transfer system for reducing the physician–patient expertise gap: An analysis with automatic and human evaluations

Bacco, L., Dell’Orletta⋄, F., Lai, H., Merone, M., & Nissim, M. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.120874 · Cited by 9

MedCPT: Contrastive Pre-trained Transformers with Large-scale PubMed Search Logs for Zero-shot Biomedical Information RetrievalPreprint

Jin, Q., Kim, W., Chen, Q., Comeau, D. C., Yeganova, L. E., Wilbur, W. J., & Lu, Z. (2023) · PubMed Central · doi:10.48550/arxiv.2307.00589 · Cited by 9

Evaluating semantic textual similarity in clinical sentences using deep learning and sentence embeddings

Antunes, R., Silva, J., & Matos, S. (2020) · ACM Symposium on Applied Computing · doi:10.1145/3341105.3373987 · Cited by 8

Knowledge-Guided Efficient Representation Learning for Biomedical Domain

Jha, K., Xun, G., Du, N., & Zhang, A. (2021) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3447548.3467118 · Cited by 7

Boosting Adverse Drug Event Normalization on Social Media: General-Purpose Model Initialization and Biomedical Semantic Text Similarity Benefit Zero-Shot Linking in Informal Contexts

Remy, F., Scaboro, S., & Portelli, B. (2023) · International Workshop on Natural Language Processing for Social Media (SocialNLP) · doi:10.18653/v1/2023.socialnlp-1.6 · Cited by 8

LitSense 2.0: AI-powered biomedical information retrieval with sentence and passage level knowledge discovery

Yeganova, L. E., Kim, W. B., Tian, S., Comeau, D. C., Wilbur, W. J., & Lu, Z. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf417 · Cited by 8

Effective Crowd-Annotation of Participants, Interventions, and Outcomes in the Text of Clinical Trial Reports

Zlabinger, M., Sabou, M., Hofstätter, S., & Hanbury, A. (2020) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2020.findings-emnlp.274 · Cited by 7

Comparing large language models and text embedding models for automated classification of textual, semantic, and critical changes in radiology reports

Lindholz, M., Burdenski, A., Ruppel, R. R., Schulze‐Weddige, S., Baumgärtner, G. L., Schobert, I. T., Haack, A.-M., Eminovic, S., Milnik, A., Hamm, C. A., et al. (2025) · European Journal of Radiology · doi:10.1016/j.ejrad.2025.112316 · Cited by 8

Supporting Complaints Investigation for Nursing and Midwifery Regulatory Agencies

Lertvittayakumjorn, P., Petej, I., Gao, Y., Krishnamurthy, Y., van der Gaag, A., Jago, R., & Stathis, K. (2021) · Annual Meeting of the Association for Computational Linguistics: System Demonstrations (ACL Demo) · doi:10.18653/v1/2021.acl-demo.10 · Cited by 7

HESML: a real-time semantic measures library for the biomedical domain with a reproducible survey

Lastra-Díaz, J. J., Lara-Clares, A., & García-Serrano, A. M. (2022) · BMC Bioinformatics · doi:10.1186/s12859-021-04539-0 · Cited by 6

EARA: Improving Biomedical Semantic Textual Similarity with Entity-Aligned Attention and Retrieval Augmentation

Xiong, Y., Yang, X., Liu, L., Wong, K., Chen, Q., Xiang, Y., & Tang, B. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.586 · Cited by 4

A Study of the State of the Art Approaches and Datasets for Multilingual Natural Language Inference

Renjit, S., & Idicula, S. M. (2024) · Neural Processing Letters · doi:10.1007/s11063-024-11673-2 · Cited by 5

EMS-BERT: A Pre-Trained Language Representation Model for the Emergency Medical Services (EMS) Domain

Rahman, M. A., Preum, S. M., Williams, R. D., Alemzadeh, H., & Stankovic, J. A. (2023) · IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies · doi:10.1145/3580252.3586978 · Cited by 5

Automatic consistency assurance for literature-based gene ontology annotation

Chen, J., Geard, N. L., Zobel, J., & Verspoor, K. M. (2021) · BMC Bioinformatics · doi:10.1186/s12859-021-04479-9 · Cited by 5

Beyond belief: a cross-genre study on perception and validation of health information online

Zuo, C., Mathur, K., Kela, D., Faramarzi, N. S., & Banerjee, R. (2022) · International Journal of Data Science and Analytics · doi:10.1007/s41060-022-00310-7 · Cited by 5

Compositional Zero-Shot Domain Transfer with Text-to-Text Models

Liu, F., Liu, Q., Bannur, S., Pérez‐García, F., Usuyama, N., Zhang, S., Naumann, T., Nori, A., Poon, H., Alvarez-Valle, J., et al. (2023) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00585 · Cited by 7

A survey on large language models from general purpose to medical applications: Datasets, methodologies, and evaluations

Wang, J., Ning, H., Peng, Y., Wei, Q., Tesfai, D., Mao, W., Zhu, T., & Huang, R. (2026) · Neurocomputing · doi:10.1016/j.neucom.2026.132914 · Cited by 21

Efficient multi-task learning with instance selection for biomedical NLP

Bonfigli, A., Bacco, L., Pecchia, L., Merone, M., & Dell’Orletta⋄, F. (2025) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2025.110050 · Cited by 4

Coherence-based Modeling of Clinical Concepts Inferred from Heterogeneous Clinical Notes for ICU Patient Risk Stratification

Gangavarapu, T., Krishnan, G. S., & Kamath, S. S. (2019) · Conference on Computational Natural Language Learning · doi:10.18653/v1/k19-1095 · Cited by 4

Protocol for a reproducible experimental survey on biomedical sentence similarity

Lara-Clares, A., Lastra-Díaz, J. J., & García-Serrano, A. M. (2021) · PLoS ONE · doi:10.1371/journal.pone.0248663 · Cited by 4

Sentence Embedding Generation Framework Based on Kullback–Leibler Divergence Optimization and RoBERTa Knowledge Distillation

Han, J., & Yang, L. (2024) · Mathematics · doi:10.3390/math12243990 · Cited by 5

Domain and Language adaptive pre-training of BERT models for Korean-English bilingual clinical text analysis

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