The unified medical language system (UMLS): integrating biomedical terminology

Gene Ontology: tool for the unification of biology

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The Unified Medical Language System

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RefSeq and LocusLink: NCBI gene-centered resources

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GenBank

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MGD: the Mouse Genome Database

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The Representation of Meaning in the UMLS

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PubMed: bridging the information gap.

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Neurofibromatosis 2.

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MGD (Mouse Genome Database)

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OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders

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Mining electronic health records: towards better research applications and clinical care

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Big data and machine learning algorithms for health-care delivery

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Unifying Large Language Models and Knowledge Graphs: A Roadmap

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

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Knowledge Enhanced Contextual Word Representations

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COVID-19 risk and outcomes in patients with substance use disorders: analyses from electronic health records in the United States

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Network-based approach to prediction and population-based validation of in silico drug repurposing

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A Systematic Review of Automatic Question Generation for Educational Purposes

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Building a knowledge graph to enable precision medicine

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Deep learning in mental health outcome research: a scoping review

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Target identification among known drugs by deep learning from heterogeneous networks

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DrugCentral: online drug compendium

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Large language models are few-shot clinical information extractors

Agrawal, M., Hegselmann, S., Lang, H., Kim, Y., & Sontag, D. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/2022.emnlp-main.130 · Cited by 358 · see citing works

Natural Language Processing in Oncology: A Review

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COVID‐19 and dementia: Analyses of risk, disparity, and outcomes from electronic health records in the US

Wang, Q., Davis, P. B., Gurney, M. E., & Xu, R. (2021) · Alzheimer's & Dementia · doi:10.1002/alz.12296 · Cited by 257 · see citing works

Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT

Smit, A., Jain, S., Rajpurkar, P., Pareek, A., Ng, A., & Lungren, M. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2020.emnlp-main.117 · Cited by 262 · see citing works

CancerMine: a literature-mined resource for drivers, oncogenes and tumor suppressors in cancer

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Knowledge-enhanced visual-language pre-training on chest radiology images

Zhang, X., Wu, C., Zhang, Y., Xie, W., & Wang, Y. (2023) · Nature Communications · doi:10.1038/s41467-023-40260-7 · Cited by 207 · see citing works

A genome-wide systems analysis reveals strong link between colorectal cancer and trimethylamine N-oxide (TMAO), a gut microbial metabolite of dietary meat and fat

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Criteria2Query: a natural language interface to clinical databases for cohort definition

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Data Evaluation and Enhancement for Quality Improvement of Machine Learning

Chen, H., Chen, J., & Ding, J. (2021) · IEEE Transactions on Reliability · doi:10.1109/tr.2021.3070863 · Cited by 166 · see citing works

Identification of disease treatment mechanisms through the multiscale interactome

Ruiz, C., Zitnik, M., & Leskovec, J. (2021) · Nature Communications · doi:10.1038/s41467-021-21770-8 · Cited by 172 · see citing works

A medical multimodal large language model for future pandemics

Liu, F., Zhu, T., Wu, X., Yang, B., You, C., Wang, C., Lu, L., Liu, Z., Zheng, Y., Sun, X., et al. (2023) · npj Digital Medicine · doi:10.1038/s41746-023-00952-2 · Cited by 155 · see citing works

The Cosmos Collaborative: A Vendor-Facilitated Electronic Health Record Data Aggregation Platform

Tarabichi, Y., Frees, A., Honeywell, S., Huang, C., Naidech, A. M., Moore, J. H., & Kaelber, D. C. (2021) · ACI Open · doi:10.1055/s-0041-1731004 · Cited by 139 · see citing works

CogStack - experiences of deploying integrated information retrieval and extraction services in a large National Health Service Foundation Trust hospital

Jackson, R., Kartoglu, I., Stringer, C., Gorrell, G., Roberts, A., Song, X., Wu, H., Agrawal, A., Lui, K., Groza, T., et al. (2018) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-018-0623-9 · Cited by 134 · see citing works

Language models are an effective representation learning technique for electronic health record data

Steinberg, E., Jung, K., Fries, J. A., Corbin, C. K., Pfohl, S. R., & Shah, N. H. (2021) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2020.103637 · Cited by 132 · see citing works

Pharos 2023: an integrated resource for the understudied human proteome

Kelleher, K. J., Sheils, T. K., Mathias, S. L., Yang, J. J., Metzger, V. T., Siramshetty, V. B., Nguyen, D.-T., Jensen, L. J., Vidović, D., Schürer, S. C., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkac1033 · Cited by 137 · see citing works

Adverse drug events: database construction and in silico prediction

Cheng, F., Li, W., Wang, X., Zhou, Y., Wu, Z., Shen, J., & Tang, Y. (2013) · Journal of Chemical Information and Modeling · doi:10.1021/ci4000079 · Cited by 124 · see citing works

Redundancy in electronic health record corpora: analysis, impact on text mining performance and mitigation strategies

Cohen, R., Elhadad, M., & Elhadad, N. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-10 · Cited by 121 · see citing works

Co-design of human-centered, explainable AI for clinical decision support

Panigutti, C., Beretta, A., Fadda, D., Giannotti, F., Pedreschi, D., Perotti, A., & Rinzivillo, S. (2023) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3587271 · Cited by 127 · see citing works

AMELIE speeds Mendelian diagnosis by matching patient phenotype and genotype to primary literature

Birgmeier, J., Haeussler, M., Deisseroth, C. A., Steinberg, E. H., Jagadeesh, K. A., Ratner, A. J., Guturu, H., Wenger, A. M., Diekhans, M. E., Stenson, P. D., et al. (2020) · Science Translational Medicine · doi:10.1126/scitranslmed.aau9113 · Cited by 118 · see citing works

Biomedical and clinical English model packages for the Stanza Python NLP library

Zhang, Y., Zhang, Y., Qi, P., Manning, C. D., & Langlotz, C. P. (2021) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocab090 · Cited by 112 · see citing works

Large-scale identification of patients with cerebral aneurysms using natural language processing

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CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT

Smit, A., Jain, S., Rajpurkar, P., Pareek, A., Ng, A. Y., & Lungren, M. P. (2020) · arXiv · doi:10.48550/arxiv.2004.09167 · Cited by 103 · see citing works

Systematic Review of Approaches to Preserve Machine Learning Performance in the Presence of Temporal Dataset Shift in Clinical Medicine

Guo, L. L., Pfohl, S. R., Fries, J., Posada, J., Fleming, S. L., Aftandilian, C., Shah, N., & Sung, L. (2021) · Applied Clinical Informatics · doi:10.1055/s-0041-1735184 · Cited by 96 · see citing works

DrugCentral 2023 extends human clinical data and integrates veterinary drugs

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Comparison of machine learning classifiers for influenza detection from emergency department free-text reports

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Machine learning to support social media empowered patients in cancer care and cancer treatment decisions

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Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings

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Standards in healthcare data

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Identifying relations of medications with adverse drug events using recurrent convolutional neural networks and gradient boosting

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Improving reference prioritisation with PICO recognition.

Brockmeier, A. J., Ju, M., Przybyła, P., & Ananiadou, S. (2019) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-019-0992-8 · Cited by 62 · see citing works

Accelerating clinical evidence synthesis with large language models

Wang, Z., Cao, L., Danek, B., Jin, Q., Lu, Z., & Sun, J. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01840-7 · Cited by 69 · see citing works

A clinical trials corpus annotated with UMLS entities to enhance the access to evidence-based medicine.

Campillos-Llanos, L., Valverde-Mateos, A., Capllonch-Carrión, A., & Moreno-Sandoval, A. (2021) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-021-01395-z · Cited by 65 · see citing works

Semantic Web meets Integrative Biology: a survey

Chen, H., Yu, T., & Chen, J. Y. (2013) · Briefings in Bioinformatics · doi:10.1093/bib/bbs014 · Cited by 65 · see citing works

Identifying scientific artefacts in biomedical literature: The Evidence Based Medicine use case.

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MCN: A comprehensive corpus for medical concept normalization

Luo, Y.-F., Sun, W., & Rumshisky, A. (2019) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2019.103132 · Cited by 62 · see citing works

Crowdsourcing Ground Truth for Medical Relation Extraction

Dumitrache, A., Aroyo, L., & Welty, C. (2018) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3152889 · Cited by 60 · see citing works

Cross-modal Clinical Graph Transformer for Ophthalmic Report Generation

Li, M., Cai, W., Verspoor, K., Pan, S., Liang, X., & Chang, X. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52688.2022.02000 · Cited by 60 · see citing works

A National, Semantic-Driven, Three-Pillar Strategy to Enable Health Data Secondary Usage Interoperability for Research Within the Swiss Personalized Health Network: Methodological Study

Gaudet-Blavignac, C., Raisaro, J. L., Touré, V., Österle, S., Crameri, K., & Lovis, C. (2021) · JMIR Medical Informatics · doi:10.2196/27591 · Cited by 54 · see citing works

Quantifying the reasoning abilities of LLMs on clinical cases

Qiu, P., Wu, C., Liu, S., Fan, Y., Zhao, W., Chen, Z., Gu, H., Peng, C., Zhang, Y., Wang, Y., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-64769-1 · Cited by 53 · see citing works

Biomedical data, computational methods and tools for evaluating disease–disease associations

Xiang, J., Zhang, J., Zhao, Y., Wu, F.-X., & Li, M. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac006 · Cited by 49 · see citing works

Ontologies and Knowledge Graphs in Oncology Research

Silva, M. C., Eugénio, P., Faria, D., & Pesquita, C. (2022) · Cancers · doi:10.3390/cancers14081906 · Cited by 46 · see citing works

A Novel System for Extractive Clinical Note Summarization using

Liang, J., Tsou, C.-H., & Poddar, A. (2019) · Proceedings of the 2nd Clinical Natural Language Processing Workshop · doi:10.18653/v1/w19-1906 · Cited by 44 · see citing works

A review of the explainability and safety of conversational agents for mental health to identify avenues for improvement

Sarkar, S., Gaur, M., Chen, L. K., Garg, M., & Srivastava, B. (2023) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2023.1229805 · Cited by 38 · see citing works

Towards Visual Dialog for Radiology

Kovaleva, O., Shivade, C., Kashyap, S., Kanjaria, K., Wu, J., Ballah, D., Coy, A., Karargyris, A., Guo, Y., Beymer, D. B., et al. (2020) · Proceedings of the 19th SIGBioMed Workshop on Biomedical Language Processing · doi:10.18653/v1/2020.bionlp-1.6 · Cited by 38 · see citing works

Designing a virtual patient dialogue system based on terminology-rich resources: Challenges and evaluation

Campillos-Llanos, L., Thomas, C., Bilinski, É., Zweigenbaum, P., & Rosset, S. (2020) · Natural Language Engineering · doi:10.1017/s1351324919000329 · Cited by 34 · see citing works

Predicting Clinical Outcomes Across Changing Electronic Health Record Systems

Gong, J. J., Naumann, T., Szolovits, P., & Guttag, J. V. (2017) · Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining · doi:10.1145/3097983.3098064 · Cited by 34 · see citing works

Modeling Heterogeneous Hierarchies with Relation-specific Hyperbolic Cones

Bai, Y., Ying, R., Ren, H., & Leskovec, J. (2021) · arXiv · doi:10.48550/arxiv.2110.14923 · Cited by 31 · see citing works

The Disease Portals, disease-gene annotation and the RGD disease ontology at the Rat Genome Database

Hayman, G. T., Laulederkind, S. J. F., Smith, J. R., Wang, S.-J., Petri, V., Nigam, R., Tutaj, M., De Pons, J., Dwinell, M. R., & Shimoyama, M. (2016) · Database · doi:10.1093/database/baw034 · Cited by 27 · see citing works

A registry for Dravet syndrome: The Italian experience

Balestrini, S., Doccini, V., Giometto, S., Lucenteforte, E., De Masi, S., Giarola, E., Brambilla, I., Pieroni, F., Perulli, M., Battaglia, D., et al. (2023) · Epilepsia Open · doi:10.1002/epi4.12730 · Cited by 21 · see citing works

A proteomic platform to identify off-target proteins associated with therapeutic modalities that induce protein degradation or gene silencing

Liu, X., Zhang, Y., Ward, L. D., Yan, Q., Bohnuud, T., Hernandez, R., Lao, S., Yuan, J., & Fan, F. (2021) · Scientific Reports · doi:10.1038/s41598-021-95354-3 · Cited by 21 · see citing works

Sociodemographic data and APOE-ε4 augmentation for MRI-based detection of amnestic mild cognitive impairment using deep learning systems

Pelka, O., Friedrich, C. M., Nensa, F., Mönninghoff, C., Bloch, L., Jöckel, K.-H., Schramm, S., Sanchez Hoffmann, S., Winkler, A., Weimar, C., et al. (2020) · PLoS ONE · doi:10.1371/journal.pone.0236868 · Cited by 22 · see citing works

A natural language processing pipeline to synthesize patient-generated notes toward improving remote care and chronic disease management: a cystic fibrosis case study

Hussain, S.-A., Sezgin, E., Krivchenia, K., Luna, J., Rust, S., & Huang, Y. (2021) · JAMIA Open · doi:10.1093/jamiaopen/ooab084 · Cited by 20 · see citing works

Agitation prevalence in people with dementia in Australian residential aged care facilities: findings from machine learning of electronic health records

Zhu, Y., Song, T., Zhang, Z., Deng, C., Alkhalaf, M., Li, W., Yin, M., Chang, H. C. (., & Yu, P. (2022) · Journal of Gerontological Nursing · doi:10.3928/00989134-20220309-01 · Cited by 18 · see citing works

Ascle—A Python Natural Language Processing Toolkit for Medical Text Generation: Development and Evaluation Study

Yang, R., Zeng, Q., You, K., Qiao, Y., Huang, L., Hsieh, C.-C., Rosand, B., Goldwasser, J., Dave, A., Keenan, T., et al. (2024) · Journal of Medical Internet Research · doi:10.2196/60601 · Cited by 16 · see citing works

Text classification models for assessing the completeness of randomized controlled trial publications based on CONSORT reporting guidelines

Jiang, L., Lan, M., Menke, J. D., Vorland, C. J., & Kilicoglu, H. (2024) · Scientific Reports · doi:10.1038/s41598-024-72130-7 · Cited by 18 · see citing works

Developing a knowledge base to support the annotation of ultrasound images of ectopic pregnancy

Dhombres, F., Maurice, P., Friszer, S., Guilbaud, L., Lelong, N., Khoshnood, B., Charlet, J., Perrot, N., Jauniaux, E., Jurkovic, D., et al. (2017) · Journal of Biomedical Semantics · doi:10.1186/s13326-017-0117-1 · Cited by 14 · see citing works

An auditable and source-verified framework for clinical AI decision support: integrating retrieval-augmented generation with data provenance

Alu, F. F., & Oluwadare, S. (2026) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2026.1737532 · Cited by 13 · see citing works

Quantifying and filtering knowledge generated by literature based discovery

Preiss, J., & Stevenson, M. (2017) · BMC Bioinformatics · doi:10.1186/s12859-017-1641-9 · Cited by 11 · see citing works

CCS Explorer: Relevance Prediction, Extractive Summarization, and Named Entity Recognition from Clinical Cohort Studies.

Al-Hussaini, I., Nakajima An, D., Lee, A. J., Bi, S., & Mitchell, C. S. (2022) · 2022 IEEE International Conference on Big Data (Big Data) · doi:10.1109/bigdata55660.2022.10020807 · Cited by 10 · see citing works

AI Medical School Tutor: Modelling and Implementation

Afzal, S., Dhamecha, T. I., Gagnon, P., Nayak, A., Shah, A., Carlstedt-Duke, J., Pathak, S., Mondal, S., Gugnani, A., Zary, N., et al. (2020) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-59137-3_13 · Cited by 10 · see citing works

Simulation of undiagnosed patients with novel genetic conditions

Alsentzer, E., Finlayson, S. G., Li, M. M., Undiagnosed Diseases Network, Kobren, S. N., & Kohane, I. S. (2023) · Nature Communications · doi:10.1038/s41467-023-41980-6 · Cited by 10 · see citing works

A distantly supervised dataset for automated data extraction from diagnostic studies.

Norman, C., Leeflang, M., Spijker, R., Kanoulas, E., & Névéol, A. (2019) · Proceedings of the 18th BioNLP Workshop and Shared Task · doi:10.18653/v1/w19-5012 · Cited by 9 · see citing works

An Interoperable UMLS Terminology Service Using FHIR

Saripalle, R., Sookhak, M., & Haghparast, M. (2020) · Future Internet · doi:10.3390/fi12110199 · Cited by 8 · see citing works

README: Bridging Medical Jargon and Lay Understanding for Patient Education through Data-Centric NLP

Yao, Z., Kantu, N. S., Wei, G., Tran, H., Duan, Z., Kwon, S., Yang, Z., & Yu, H. (2024) · Findings of the Association for Computational Linguistics: EMNLP 2024 · doi:10.18653/v1/2024.findings-emnlp.737 · Cited by 8 · see citing works

Multimodal convolutional neural networks for the prediction of acute kidney injury in the intensive care

van Slobbe, R., Herrmannova, D., Boeke, D. J., Lima-Walton, E. S., Abu-Hanna, A., & Vagliano, I. (2025) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2025.105815 · Cited by 7 · see citing works

Investigating the impact of weakly supervised data on text mining models of publication transparency: a case study on randomized controlled trials

Hoang, L., Jiang, L., & Kilicoglu, H. (2021) · doi:10.1101/2021.09.14.21263586 · Cited by 5 · see citing works

Automated stratification of trauma injury severity across multiple body regions using multi-modal, multi-class machine learning models

Gao, J., Chen, G., O’Rourke, A. P., Caskey, J., Carey, K. A., Oguss, M., Stey, A., Dligach, D., Miller, T., Mayampurath, A., et al. (2024) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocae071 · Cited by 5 · see citing works

Data Organisation for Efficient Pattern Retrieval: Indexing, Storage, and Access Structures

Koukaras, P., & Tjortjis, C. (2025) · Big Data and Cognitive Computing · doi:10.3390/bdcc9100258 · Cited by 3 · see citing works

Joint extraction of entity and relation based on fine-tuning BERT for long biomedical literatures

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