Published on in Vol 4, No 2 (2018): Apr-Jun
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/9361, first published
.
Journals
- Chen T, Wu M, Li H. A general approach for improving deep learning-based medical relation extraction using a pre-trained model and fine-tuning. Database 2019;2019 View
- Li F, Yu H. An investigation of single-domain and multidomain medication and adverse drug event relation extraction from electronic health record notes using advanced deep learning models. Journal of the American Medical Informatics Association 2019;26(7):646 View
- Tang Y, Yang J, Ang P, Dorajoo S, Foo B, Soh S, Tan S, Tham M, Ye Q, Shek L, Sung C, Tung A. Detecting adverse drug reactions in discharge summaries of electronic medical records using Readpeer. International Journal of Medical Informatics 2019;128:62 View
- Alimova I, Tutubalina E. Multiple features for clinical relation extraction: A machine learning approach. Journal of Biomedical Informatics 2020;103:103382 View
- Spasic I, Nenadic G. Clinical Text Data in Machine Learning: Systematic Review. JMIR Medical Informatics 2020;8(3):e17984 View
- Liu S, Nie W, Gao D, Yang H, Yan J, Hao T. Clinical quantitative information recognition and entity-quantity association from Chinese electronic medical records. International Journal of Machine Learning and Cybernetics 2021;12(1):117 View
- Crowson M, Hamour A, Lin V, Chen J, Chan T. Machine learning for pattern detection in cochlear implant FDA adverse event reports. Cochlear Implants International 2020;21(6):313 View
- Dandala B, Joopudi V, Devarakonda M. Adverse Drug Events Detection in Clinical Notes by Jointly Modeling Entities and Relations Using Neural Networks. Drug Safety 2019;42(1):135 View
- Yoon D, Jang J, Choi B, Kim T, Han C. Discovering hidden information in biosignals from patients using artificial intelligence. Korean Journal of Anesthesiology 2020;73(4):275 View
- Siefridt C, Grosjean J, Lefebvre T, Rollin L, Darmoni S, Schuers M. Evaluation of automatic annotation by a multi-terminological concepts extractor within a corpus of data from family medicine consultations. International Journal of Medical Informatics 2020;133:104009 View
- Young J, Conover M, Jonsson Funk M. Measurement Error and Misclassification in Electronic Medical Records: Methods to Mitigate Bias. Current Epidemiology Reports 2018;5(4):343 View
- Chen J, Lalor J, Liu W, Druhl E, Granillo E, Vimalananda V, Yu H. Detecting Hypoglycemia Incidents Reported in Patients’ Secure Messages: Using Cost-Sensitive Learning and Oversampling to Reduce Data Imbalance. Journal of Medical Internet Research 2019;21(3):e11990 View
- Jin Y, Li F, Vimalananda V, Yu H. Automatic Detection of Hypoglycemic Events From the Electronic Health Record Notes of Diabetes Patients: Empirical Study. JMIR Medical Informatics 2019;7(4):e14340 View
- Li F, Liu W, Yu H. Extraction of Information Related to Adverse Drug Events from Electronic Health Record Notes: Design of an End-to-End Model Based on Deep Learning. JMIR Medical Informatics 2018;6(4):e12159 View
- Christopoulou F, Tran T, Sahu S, Miwa M, Ananiadou S. Adverse drug events and medication relation extraction in electronic health records with ensemble deep learning methods. Journal of the American Medical Informatics Association 2020;27(1):39 View
- Li R, Yin C, Yang S, Qian B, Zhang P. Marrying Medical Domain Knowledge With Deep Learning on Electronic Health Records: A Deep Visual Analytics Approach. Journal of Medical Internet Research 2020;22(9):e20645 View
- Decker B, Hill C, Baldassano S, Khankhanian P. Can antiepileptic efficacy and epilepsy variables be studied from electronic health records? A review of current approaches. Seizure 2021;85:138 View
- Shen Y, Hsia T, Hsu C. RETRACTED ARTICLE: Analysis of Electronic Health Records Based on Deep Learning with Natural Language Processing. Arabian Journal for Science and Engineering 2023;48(2):2597 View
- Wang B, Liu F, Deveaux L, Ash A, Gosh S, Li X, Rundensteiner E, Cottrell L, Adderley R, Stanton B. Adolescent HIV-related behavioural prediction using machine learning: a foundation for precision HIV prevention. AIDS 2021;35(Supplement 1):S75 View
- Mitra A, Rawat B, McManus D, Yu H. Relation Classification for Bleeding Events From Electronic Health Records Using Deep Learning Systems: An Empirical Study. JMIR Medical Informatics 2021;9(7):e27527 View
- Percha B. Modern Clinical Text Mining: A Guide and Review. Annual Review of Biomedical Data Science 2021;4(1):165 View
- Teramoto K, Takeda T, Mihara N, Shimai Y, Manabe S, Kuwata S, Kondoh H, Matsumura Y. Detecting Adverse Drug Events Through the Chronological Relationship Between the Medication Period and the Presence of Adverse Reactions From Electronic Medical Record Systems: Observational Study. JMIR Medical Informatics 2021;9(11):e28763 View
- de Oliveira J, da Costa C, Antunes R. Data structuring of electronic health records: a systematic review. Health and Technology 2021;11(6):1219 View
- Bose P, Srinivasan S, Sleeman W, Palta J, Kapoor R, Ghosh P. A Survey on Recent Named Entity Recognition and Relationship Extraction Techniques on Clinical Texts. Applied Sciences 2021;11(18):8319 View
- Fernandes M, Valizadeh N, Alabsi H, Quadri S, Tesh R, Bucklin A, Sun H, Jain A, Brenner L, Ye E, Ge W, Collens S, Lin S, Das S, Robbins G, Zafar S, Mukerji S, Brandon Westover M. Classification of neurologic outcomes from medical notes using natural language processing. Expert Systems with Applications 2023;214:119171 View
- Shingjergji K, Celebi R, Scholtes J, Dumontier M. Relation extraction from DailyMed structured product labels by optimally combining crowd, experts and machines. Journal of Biomedical Informatics 2021;122:103902 View
- Sanyal J, Rubin D, Banerjee I. A weakly supervised model for the automated detection of adverse events using clinical notes. Journal of Biomedical Informatics 2022;126:103969 View
- Ramachandran G, Lybarger K, Liu Y, Mahajan D, Liang J, Tsou C, Yetisgen M, Uzuner Ö. Extracting medication changes in clinical narratives using pre-trained language models. Journal of Biomedical Informatics 2023;139:104302 View
- Yang L, Huang X, Wang J, Yang X, Ding L, Li Z, Li J. Identifying stroke-related quantified evidence from electronic health records in real-world studies. Artificial Intelligence in Medicine 2023;140:102552 View
- Deimazar G, Sheikhtaheri A. Machine learning models to detect and predict patient safety events using electronic health records: A systematic review. International Journal of Medical Informatics 2023;180:105246 View
- He F, Zhang L, Qu W, Teng C, Xie D. Research on Construction of Knowledge Graph of Intestinal Cells. Journal of Artificial Intelligence for Medical Sciences 2020;1(1-2):15 View
- Tong L, Shi W, Isgut M, Zhong Y, Lais P, Gloster L, Sun J, Swain A, Giuste F, Wang M. Integrating Multi-Omics Data With EHR for Precision Medicine Using Advanced Artificial Intelligence. IEEE Reviews in Biomedical Engineering 2024;17:80 View
- Litvinova O, Yeung A, Hammerle F, Mickael M, Matin M, Kletecka-Pulker M, Atanasov A, Willschke H. Digital Technology Applications in the Management of Adverse Drug Reactions: Bibliometric Analysis. Pharmaceuticals 2024;17(3):395 View
- Xu J, Xi X, Chen J, Sheng V, Ma J, Cui Z. A Survey of Deep Learning for Electronic Health Records. Applied Sciences 2022;12(22):11709 View
- Zhao Z, Liu Y, Lv D, Li R, Yu X, Mao D. Extraction of entity relationships serving the field of agriculture food safety regulation. International Journal of Machine Learning and Cybernetics 2024;15(12):6077 View
- Farnoush A, Sedighi-Maman Z, Rasoolian B, Heath J, Fallah B. Prediction of adverse drug reactions using demographic and non-clinical drug characteristics in FAERS data. Scientific Reports 2024;14(1) View
- Wang J, Dao J, Zhang Y, Xu D, Zhang X. Heterogeneous federated distillation with mutual information maximization for medical relation extraction. Information Sciences 2025;698:121759 View
Books/Policy Documents
- Mendonca E, Tachinardi U. Personalized and Precision Medicine Informatics. View
- Sagar Imambi S, Mandhala V, Naaz M. Smart Technologies in Data Science and Communication. View
- Liu F, Weng C, Yu H. Clinical Research Informatics. View
- Selmi I, Kabachi N, Ben Abdallah S, Ghedira Guegan C, Baazaoui H. Advanced Information Networking and Applications. View
- de Dios E, Ali M, Gu I, Vecchio T, Ge C, Jakola A. Machine Learning in Clinical Neuroscience. View