This paper is in the following e-collection/theme issue:

Reviews (67) Clinical Information and Decision Making (1040) Decision Support for Health Professionals (853) Electronic Health Records (838) Natural Language Processing (535)

Published on in Vol 7 , No 2 (2019) :Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12239, first published .
Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic Review

Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic Review

Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic Review

Authors of this article:

Seyedmostafa Sheikhalishahi 1, 2 Author Orcid Image ;   Riccardo Miotto 3 Author Orcid Image ;   Joel T Dudley 3 Author Orcid Image ;   Alberto Lavelli 4 Author Orcid Image ;   Fabio Rinaldi 5 Author Orcid Image ;   Venet Osmani 2 Author Orcid Image
Article Authors Cited by (187) Tweetations (40) Metrics

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  115. Zhang X, Gavaldà R, Baixeries J. Interpretable prediction of mortality in liver transplant recipients based on machine learning. Computers in Biology and Medicine 2022;151:106188 View
  116. Yeung C, Beck T, Posma J. MetaboListem and TABoLiSTM: Two Deep Learning Algorithms for Metabolite Named Entity Recognition. Metabolites 2022;12(4):276 View
  117. Leis A, Casadevall D, Albanell J, Posso M, Macià F, Castells X, Ramírez-Anguita J, Martínez Roldán J, Furlong L, Sanz F, Ronzano F, Mayer M. Exploring the Association of Cancer and Depression in Electronic Health Records: Combining Encoded Diagnosis and Mining Free-Text Clinical Notes. JMIR Cancer 2022;8(3):e39003 View
  118. Auwerx C, Sadler M, Reymond A, Kutalik Z. From pharmacogenetics to pharmaco-omics: Milestones and future directions. Human Genetics and Genomics Advances 2022;3(2):100100 View
  119. Segura T, Medrano I, Collazo S, Maté C, Sguera C, Del Rio-Bermudez C, Casero H, Salcedo I, García-García J, Alcahut-Rodríguez C, Aquino J, Casadevall D, Donaire D, Marin-Corral J, Menke S, Polo N, Taberna M. Symptoms timeline and outcomes in amyotrophic lateral sclerosis using artificial intelligence. Scientific Reports 2023;13(1) View
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  121. Xie F, Mercado C, Kim S, Yu W, Zheng C, Getahun D, Jacobsen S, Chen W. Identifying Spontaneous Abortion from Clinical Notes within a Large Integrated Healthcare System. SN Computer Science 2022;3(4) View
  122. Chang R, Shing J, Erves J, Du L, Koyama T, Deppen S, Rentuza A, McAfee C, Stroebel C, Cates J, Harnack L, Andrews D, Bramblett R, Hull P. Measurement of provider fidelity to immunization guidelines: a mixed-methods study on the feasibility of documenting patient refusals of the human papillomavirus vaccine. BMC Medical Informatics and Decision Making 2022;22(1) View
  123. Fang A, Hu J, Zhao W, Feng M, Fu J, Feng S, Lou P, Ren H, Chen X. Extracting clinical named entity for pituitary adenomas from Chinese electronic medical records. BMC Medical Informatics and Decision Making 2022;22(1) View
  124. Ayad A, Hallawa A, Peine A, Martin L, Fazlic L, Dartmann G, Marx G, Schmeink A. Predicting Abnormalities in Laboratory Values of Patients in the Intensive Care Unit Using Different Deep Learning Models: Comparative Study. JMIR Medical Informatics 2022;10(8):e37658 View
  125. BuHamra S, Almutairi A, Buhamrah A, Almadani S, Alibrahim Y. An NLP tool for data extraction from electronic health records: COVID-19 mortalities and comorbidities. Frontiers in Public Health 2022;10 View
  126. Lim J, Hong M, Lam W, Zhang Z, Teo Z, Liu Y, Ng W, Foo L, Ting D. Novel technical and privacy-preserving technology for artificial intelligence in ophthalmology. Current Opinion in Ophthalmology 2022;33(3):174 View
  127. Jantscher M, Gunzer F, Kern R, Hassler E, Tschauner S, Reishofer G. Information extraction from German radiological reports for general clinical text and language understanding. Scientific Reports 2023;13(1) View
  128. Han P, Fu S, Kolis J, Hughes R, Hallstrom B, Carvour M, Maradit-Kremers H, Sohn S, Vydiswaran V. Multicenter Validation of Natural Language Processing Algorithms for the Detection of Common Data Elements in Operative Notes for Total Hip Arthroplasty: Algorithm Development and Validation. JMIR Medical Informatics 2022;10(8):e38155 View
  129. Zhou L, Liu S, Li C, Sun Y, Zhang Y, Li Y, Yuan H, Sun Y, Xu F, Li Y, Ahmed M. Natural Language Processing Algorithms for Normalizing Expressions of Synonymous Symptoms in Traditional Chinese Medicine. Evidence-Based Complementary and Alternative Medicine 2021;2021:1 View
  130. Valdés Sanz N, García-Layana A, Colas T, Moriche M, Montero Moreno M, Ciprandi G. Clinical Characterization of Inpatients with Acute Conjunctivitis: A Retrospective Analysis by Natural Language Processing and Machine Learning. Applied Sciences 2022;12(23):12352 View
  131. Gumiel Y, Silva e Oliveira L, Claveau V, Grabar N, Paraiso E, Moro C, Carvalho D. Temporal Relation Extraction in Clinical Texts. ACM Computing Surveys 2022;54(7):1 View
  132. Roussinov D, Conkie A, Patterson A, Sainsbury C. Predicting Clinical Events Based on Raw Text: From Bag-of-Words to Attention-Based Transformers. Frontiers in Digital Health 2022;3 View
  133. Ning J, Hashmi M. Natural Language Processing Technology Used in Artificial Intelligence Scene of Law for Human Behavior. Wireless Communications and Mobile Computing 2022;2022:1 View
  134. Nishioka S, Watanabe T, Asano M, Yamamoto T, Kawakami K, Yada S, Aramaki E, Yajima H, Kizaki H, Hori S, Yang J. Identification of hand-foot syndrome from cancer patients’ blog posts: BERT-based deep-learning approach to detect potential adverse drug reaction symptoms. PLOS ONE 2022;17(5):e0267901 View
  135. Kenei J, Opiyo E. Semantic modeling and visualization of semantic groups of clinical text documents. International Journal of Information Technology 2022;14(5):2585 View
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  137. Obeid J, Khalifa A, Xavier B, Bou-Daher H, Rockey D. An AI Approach for Identifying Patients With Cirrhosis. Journal of Clinical Gastroenterology 2023;57(1):82 View
  138. Zafari H, Langlois S, Zulkernine F, Kosowan L, Singer A. AI in predicting COPD in the Canadian population. Biosystems 2022;211:104585 View
  139. Hom J, Nikowitz J, Ottesen R, Niland J. Facilitating clinical research through automation: Combining optical character recognition with natural language processing. Clinical Trials 2022;19(5):504 View
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  143. Mayes E, Gehlbach J, Jeziorczak P, Wooldridge A. Machine Learning to Operationalize Team Cognition: A Case Study of Patient Handoffs. Human Factors in Healthcare 2023:100036 View
  144. Wan C, Ge X, Wang J, Zhang X, Yu Y, Hu J, Liu Y, Ma H. Identification and Impact Analysis of Family History of Psychiatric Disorder in Mood Disorder Patients With Pretrained Language Model. Frontiers in Psychiatry 2022;13 View
  145. Sammani A, Jansen M, de Vries N, de Jonge N, Baas A, te Riele A, Asselbergs F, Oerlemans M. Automatic Identification of Patients With Unexplained Left Ventricular Hypertrophy in Electronic Health Record Data to Improve Targeted Treatment and Family Screening. Frontiers in Cardiovascular Medicine 2022;9 View
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  147. Gao S, Alawad M, Young M, Gounley J, Schaefferkoetter N, Yoon H, Wu X, Durbin E, Doherty J, Stroup A, Coyle L, Tourassi G. Limitations of Transformers on Clinical Text Classification. IEEE Journal of Biomedical and Health Informatics 2021;25(9):3596 View
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  151. Huang J, Walsh C. Electronic Medical Records. Gastrointestinal Endoscopy Clinics of North America 2023;33(2):267 View
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Books/Policy Documents

  1. Khoroshevsky V, Efimenko V, Efimenko I. Artificial Intelligence. View
  2. Dal Pont T, Sabo I, Hübner J, Rover A. Intelligent Systems. View
  3. De Freitas J, Glicksberg B, Johnson K, Miotto R. Machine Learning in Cardiovascular Medicine. View
  4. Kubassova O, Shaikh F, Melus C, Mahler M. Precision Medicine and Artificial Intelligence. View
  5. Almeida J, Silva J, Sierra A, Matos S, Oliveira J. Biomedical Engineering Systems and Technologies. View
  6. Moylett S. Big Data in Psychiatry #x0026; Neurology. View
  7. Das N, Topalovic M, Janssens W. Artificial Intelligence in Medicine. View
  8. Sousa R, Oliveira D, Durães D, Neto C, Machado J. Artificial Intelligence XXXIX. View
  9. Hochheiser H, Verma A. Mental Health Informatics. View
  10. Kocbek P, Gosak L, Musović K, Stiglic G. Artificial Intelligence in Medicine. View
  11. Das N, Topalovic M, Janssens W. Artificial Intelligence in Medicine. View
  12. Kumar Attar R, Komal . Artificial Intelligence for Innovative Healthcare Informatics. View
  13. Jungkunz M, Köngeter A, Winkler E, Mehlis K, Schickhardt C. Datenreiche Medizin und das Problem der Einwilligung. View
  14. Saghazadeh A, Rezaei N. Handbook of Cancer and Immunology. View
  15. Pokhriyal P, Chavda V, Pathak M. Bioinformatics Tools for Pharmaceutical Drug Product Development. View
  16. Tyagi N, Bhushan B. Enabling Technologies for Effective Planning and Management in Sustainable Smart Cities. View
  17. Liu Z, Zhang J, Hou Y, Zhang X, Li G, Xiang Y. Health Information Processing. View
  18. Guazzo A, Longato E, Fadini G, Morieri M, Sparacino G, Di Camillo B. Machine Learning, Optimization, and Data Science. View