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

Reviews (62) Clinical Information and Decision Making (901) Decision Support for Health Professionals (734) Electronic Health Records (781) Natural Language Processing (487)

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 (174) Tweetations (37) Metrics

Journals

  1. Retson T, Eghtedari M. Computer-Aided Detection/Diagnosis in Breast Imaging: A Focus on the Evolving FDA Regulations for Using Software as a Medical Device. Current Radiology Reports 2020;8(6) View
  2. Yang Z, Dehmer M, Yli-Harja O, Emmert-Streib F. Combining deep learning with token selection for patient phenotyping from electronic health records. Scientific Reports 2020;10(1) View
  3. Goto T, Hara K, Hashimoto K, Soeno S, Shirakawa T, Sonoo T, Nakamura K. Validation of chief complaints, medical history, medications, and physician diagnoses structured with an integrated emergency department information system in Japan: the Next Stage ER system. Acute Medicine & Surgery 2020;7(1) View
  4. Leiter R, Santus E, Jin Z, Lee K, Yusufov M, Chien I, Ramaswamy A, Moseley E, Qian Y, Schrag D, Lindvall C. Deep Natural Language Processing to Identify Symptom Documentation in Clinical Notes for Patients With Heart Failure Undergoing Cardiac Resynchronization Therapy. Journal of Pain and Symptom Management 2020;60(5):948 View
  5. Lanzone J, Cenci C, Tombini M, Ricci L, Tufo T, Piccioli M, Marrelli A, Mecarelli O, Assenza G. Glimpsing the Impact of COVID19 Lock-Down on People With Epilepsy: A Text Mining Approach. Frontiers in Neurology 2020;11 View
  6. Hahn U, Oleynik M. Medical Information Extraction in the Age of Deep Learning. Yearbook of Medical Informatics 2020;29(01):208 View
  7. Tan Y, Bacchi S, Casson R, Selva D, Chan W. Triaging ophthalmology outpatient referrals with machine learning: A pilot study. Clinical & Experimental Ophthalmology 2020;48(2):169 View
  8. Chen X, Xie H, Cheng G, Poon L, Leng M, Wang F. Trends and Features of the Applications of Natural Language Processing Techniques for Clinical Trials Text Analysis. Applied Sciences 2020;10(6):2157 View
  9. Agaronnik N, Lindvall C, El-Jawahri A, He W, Iezzoni L. Challenges of Developing a Natural Language Processing Method With Electronic Health Records to Identify Persons With Chronic Mobility Disability. Archives of Physical Medicine and Rehabilitation 2020;101(10):1739 View
  10. Wu S, Roberts K, Datta S, Du J, Ji Z, Si Y, Soni S, Wang Q, Wei Q, Xiang Y, Zhao B, Xu H. Deep learning in clinical natural language processing: a methodical review. Journal of the American Medical Informatics Association 2020;27(3):457 View
  11. Carrell D, Malin B, Cronkite D, Aberdeen J, Clark C, Li M, Bastakoty D, Nyemba S, Hirschman L. Resilience of clinical text de-identified with “hiding in plain sight” to hostile reidentification attacks by human readers. Journal of the American Medical Informatics Association 2020;27(9):1374 View
  12. Gonem S, Janssens W, Das N, Topalovic M. Applications of artificial intelligence and machine learning in respiratory medicine. Thorax 2020;75(8):695 View
  13. Pilozzi A, Huang X. Overcoming Alzheimer’s Disease Stigma by Leveraging Artificial Intelligence and Blockchain Technologies. Brain Sciences 2020;10(3):183 View
  14. 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
  15. Shull J. Digital Health and the State of Interoperable Electronic Health Records. JMIR Medical Informatics 2019;7(4):e12712 View
  16. Gao S, Alawad M, Schaefferkoetter N, Penberthy L, Wu X, Durbin E, Coyle L, Ramanathan A, Tourassi G, Reddi H. Using case-level context to classify cancer pathology reports. PLOS ONE 2020;15(5):e0232840 View
  17. Miotto R, Percha B, Glicksberg B, Lee H, Cruz L, Dudley J, Nabeel I. Identifying Acute Low Back Pain Episodes in Primary Care Practice From Clinical Notes: Observational Study. JMIR Medical Informatics 2020;8(2):e16878 View
  18. Lanzer J, Leuschner F, Kramann R, Levinson R, Saez-Rodriguez J. Big Data Approaches in Heart Failure Research. Current Heart Failure Reports 2020;17(5):213 View
  19. Schaaf J, Prokosch H, Boeker M, Schaefer J, Vasseur J, Storf H, Sedlmayr M. Interviews with experts in rare diseases for the development of clinical decision support system software - a qualitative study. BMC Medical Informatics and Decision Making 2020;20(1) View
  20. Uddin M, Wang Y, Woodbury-Smith M. Artificial intelligence for precision medicine in neurodevelopmental disorders. npj Digital Medicine 2019;2(1) View
  21. Baxter S, Klie A, Radha Saseendrakumar B, Ye G, Hogarth M. Text Processing for Detection of Fungal Ocular Involvement in Critical Care Patients: Cross-Sectional Study. Journal of Medical Internet Research 2020;22(8):e18855 View
  22. Ilan Y. Second-Generation Digital Health Platforms: Placing the Patient at the Center and Focusing on Clinical Outcomes. Frontiers in Digital Health 2020;2 View
  23. Shen F, Liu S, Fu S, Wang Y, Henry S, Uzuner O, Liu H. 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. JMIR Medical Informatics 2021;9(1):e24008 View
  24. Brundage M, Sexton T, Hodkiewicz M, Dima A, Lukens S. Technical language processing: Unlocking maintenance knowledge. Manufacturing Letters 2021;27:42 View
  25. Solarte Pabón O, Torrente M, Provencio M, Rodríguez-Gonzalez A, Menasalvas E. Integrating Speculation Detection and Deep Learning to Extract Lung Cancer Diagnosis from Clinical Notes. Applied Sciences 2021;11(2):865 View
  26. Grothen A, Tennant B, Wang C, Torres A, Bloodgood Sheppard B, Abastillas G, Matatova M, Warner J, Rivera D. Application of Artificial Intelligence Methods to Pharmacy Data for Cancer Surveillance and Epidemiology Research: A Systematic Review. JCO Clinical Cancer Informatics 2020;(4):1051 View
  27. Viani N, Botelle R, Kerwin J, Yin L, Patel R, Stewart R, Velupillai S. A natural language processing approach for identifying temporal disease onset information from mental healthcare text. Scientific Reports 2021;11(1) View
  28. Thompson C, Jin A, Luft H, Lichtensztajn D, Allen L, Liang S, Schumacher B, Gomez S. Population-Based Registry Linkages to Improve Validity of Electronic Health Record–Based Cancer Research. Cancer Epidemiology, Biomarkers & Prevention 2020;29(4):796 View
  29. Goh K, Wang L, Yeow A, Poh H, Li K, Yeow J, Tan G. Artificial intelligence in sepsis early prediction and diagnosis using unstructured data in healthcare. Nature Communications 2021;12(1) View
  30. Wang C, Han J, Fang S, Lai Y. Ambulatory Phonation Monitoring With Wireless Microphones Based on the Speech Energy Envelope: Algorithm Development and Validation. JMIR mHealth and uHealth 2020;8(12):e16746 View
  31. Del Rio-Bermudez C, Medrano I, Yebes L, Poveda J. Towards a symbiotic relationship between big data, artificial intelligence, and hospital pharmacy. Journal of Pharmaceutical Policy and Practice 2020;13(1) View
  32. Liu H, Zhang Z, Xu Y, Wang N, Huang Y, Yang Z, Jiang R, Chen H. Use of BERT (Bidirectional Encoder Representations from Transformers)-Based Deep Learning Method for Extracting Evidences in Chinese Radiology Reports: Development of a Computer-Aided Liver Cancer Diagnosis Framework. Journal of Medical Internet Research 2021;23(1):e19689 View
  33. Silva J, Almeida J, Matos S. Extraction of Family History Information From Clinical Notes: Deep Learning and Heuristics Approach. JMIR Medical Informatics 2020;8(12):e22898 View
  34. García-García E, González-Romero G, Martín-Pérez E, Zapata Cornejo E, Escobar-Aguilar G, Cárdenas Bonnet M. Real-World Data and Machine Learning to Predict Cardiac Amyloidosis. International Journal of Environmental Research and Public Health 2021;18(3):908 View
  35. Kim Y, Lee J, Choi S, Lee J, Kim J, Seok J, Joo H. Validation of deep learning natural language processing algorithm for keyword extraction from pathology reports in electronic health records. Scientific Reports 2020;10(1) View
  36. Yang H, Kuang L, Xia F. Multimodal temporal-clinical note network for mortality prediction. Journal of Biomedical Semantics 2021;12(1) View
  37. Tayefi M, Ngo P, Chomutare T, Dalianis H, Salvi E, Budrionis A, Godtliebsen F. Challenges and opportunities beyond structured data in analysis of electronic health records. WIREs Computational Statistics 2021;13(6) View
  38. Lee E, Torous J, De Choudhury M, Depp C, Graham S, Kim H, Paulus M, Krystal J, Jeste D. Artificial Intelligence for Mental Health Care: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 2021;6(9):856 View
  39. Park H, Song M, Lee E, Seo B, Choi C. An Attention Model With Transfer Embeddings to Classify Pneumonia-Related Bilingual Imaging Reports: Algorithm Development and Validation. JMIR Medical Informatics 2021;9(5):e24803 View
  40. Solomon M, Tabada G, Allen A, Sung S, Go A. Large-scale identification of aortic stenosis and its severity using natural language processing on electronic health records. Cardiovascular Digital Health Journal 2021;2(3):156 View
  41. Veiga R, Schuler-Faccini L, França G, Andrade R, Teixeira M, Costa L, Paixão E, Costa M, Barreto M, Oliveira J, Oliveira W, Cardim L, Rodrigues M. Classification algorithm for congenital Zika Syndrome: characterizations, diagnosis and validation. Scientific Reports 2021;11(1) View
  42. Klappe E, van Putten F, de Keizer N, Cornet R. Contextual property detection in Dutch diagnosis descriptions for uncertainty, laterality and temporality. BMC Medical Informatics and Decision Making 2021;21(1) View
  43. Caufield J, Sigdel D, Fu J, Choi H, Guevara-Gonzalez V, Wang D, Ping P. Cardiovascular informatics: building a bridge to data harmony. Cardiovascular Research 2022;118(3):732 View
  44. Locke S, Bashall A, Al-Adely S, Moore J, Wilson A, Kitchen G. Natural language processing in medicine: A review. Trends in Anaesthesia and Critical Care 2021;38:4 View
  45. Turchin A, Florez Builes L. Using Natural Language Processing to Measure and Improve Quality of Diabetes Care: A Systematic Review. Journal of Diabetes Science and Technology 2021;15(3):553 View
  46. Lee H, Kang J, Yeo J. Medical Specialty Recommendations by an Artificial Intelligence Chatbot on a Smartphone: Development and Deployment. Journal of Medical Internet Research 2021;23(5):e27460 View
  47. Staples J, Wiksyk B, Liu G, Desai S, Walraven C, Sutherland J. External validation of the modified LACE +, LACE +, and LACE scores to predict readmission or death after hospital discharge. Journal of Evaluation in Clinical Practice 2021;27(6):1390 View
  48. Alkaitis M, Agrawal M, Riely G, Razavi P, Sontag D. Automated NLP Extraction of Clinical Rationale for Treatment Discontinuation in Breast Cancer. JCO Clinical Cancer Informatics 2021;(5):550 View
  49. Li X, Han J, Zhang S, Chen K, Zhao L, He Y, Liu S. Artificial Intelligence for Screening Chinese Electronic Medical Record and Biobank Information. Biopreservation and Biobanking 2021;19(5):386 View
  50. Hu D, Zhang H, Li S, Wang Y, Wu N, Lu X. Automatic Extraction of Lung Cancer Staging Information From Computed Tomography Reports: Deep Learning Approach. JMIR Medical Informatics 2021;9(7):e27955 View
  51. Zhan X, Humbert-Droz M, Mukherjee P, Gevaert O. Structuring clinical text with AI: Old versus new natural language processing techniques evaluated on eight common cardiovascular diseases. Patterns 2021;2(7):100289 View
  52. Enriquez J, Chu Y, Pudakalakatti S, Hsieh K, Salmon D, Dutta P, Millward N, Lurie E, Millward S, McAllister F, Maitra A, Sen S, Killary A, Zhang J, Jiang X, Bhattacharya P, Shams S. Hyperpolarized Magnetic Resonance and Artificial Intelligence: Frontiers of Imaging in Pancreatic Cancer. JMIR Medical Informatics 2021;9(6):e26601 View
  53. Shah V, Chillakuru Y, Rybkin A, Seo Y, Vu T, Sohn J. Algorithmic Prediction of Delayed Radiology Turn-Around-Time during Non-Business Hours. Academic Radiology 2022;29(5):e82 View
  54. Asada M, Gunasekaran N, Miwa M, Sasaki Y. Representing a Heterogeneous Pharmaceutical Knowledge-Graph with Textual Information. Frontiers in Research Metrics and Analytics 2021;6 View
  55. Almeida J, Silva J, Matos S, Oliveira J. A two-stage workflow to extract and harmonize drug mentions from clinical notes into observational databases. Journal of Biomedical Informatics 2021;120:103849 View
  56. Bagheri A, Groenhof T, Asselbergs F, Haitjema S, Bots M, Veldhuis W, de Jong P, Oberski D, Liu A. Automatic Prediction of Recurrence of Major Cardiovascular Events: A Text Mining Study Using Chest X-Ray Reports. Journal of Healthcare Engineering 2021;2021:1 View
  57. Carrillo-Larco R, Castillo-Cara M, Lovón-Melgarejo J. Government plans in the 2016 and 2021 Peruvian presidential elections: A natural language processing analysis of the health chapters. Wellcome Open Research 2021;6:177 View
  58. Foo L, Ng W, Lim G, Tan T, Ang M, Ting D. Artificial intelligence in myopia: current and future trends. Current Opinion in Ophthalmology 2021;32(5):413 View
  59. Carrillo-Larco R, Castillo-Cara M, Lovón-Melgarejo J. Government plans in the 2016 and 2021 Peruvian presidential elections: A natural language processing analysis of the health chapters. Wellcome Open Research 2022;6:177 View
  60. Sarker A, Al-Garadi M, Yang Y, Choi J, Quyyumi A, Martin G. Defining Patient-Oriented Natural Language Processing: A New Paradigm for Research and Development to Facilitate Adoption and Use by Medical Experts. JMIR Medical Informatics 2021;9(9):e18471 View
  61. Nagamine T, Gillette B, Kahoun J, Burghaus R, Lippert J, Saxena M. Data-driven identification of heart failure disease states and progression pathways using electronic health records. Scientific Reports 2022;12(1) View
  62. Zhang H, Zhang J, Ni W, Jiang Y, Liu K, Sun D, Li J. Transformer- and Generative Adversarial Network–Based Inpatient Traditional Chinese Medicine Prescription Recommendation: Development Study. JMIR Medical Informatics 2022;10(5):e35239 View
  63. Wang L, Zhang Y, Chignell M, Shan B, Sheehan K, Razak F, Verma A. Boosting Delirium Identification Accuracy With Sentiment-Based Natural Language Processing: Mixed Methods Study. JMIR Medical Informatics 2022;10(12):e38161 View
  64. Tamang S, Humbert-Droz M, Gianfrancesco M, Izadi Z, Schmajuk G, Yazdany J. Practical Considerations for Developing Clinical Natural Language Processing Systems for Population Health Management and Measurement. JMIR Medical Informatics 2023;11:e37805 View
  65. Bayramli I, Castro V, Barak-Corren Y, Madsen E, Nock M, Smoller J, Reis B. Predictive structured–unstructured interactions in EHR models: A case study of suicide prediction. npj Digital Medicine 2022;5(1) View
  66. Maclagan L, Abdalla M, Harris D, Stukel T, Chen B, Candido E, Swartz R, Iaboni A, Jaakkimainen R, Bronskill S. Can Patients with Dementia Be Identified in Primary Care Electronic Medical Records Using Natural Language Processing?. Journal of Healthcare Informatics Research 2023;7(1):42 View
  67. Santana B, Campos R, Amorim E, Jorge A, Silvano P, Nunes S. A survey on narrative extraction from textual data. Artificial Intelligence Review 2023 View
  68. Pethani F, Dunn A. Natural language processing for clinical notes in dentistry: A systematic review. Journal of Biomedical Informatics 2023;138:104282 View
  69. Rajaram A, Patel N, Hickey Z, Wolfrom B, Newbigging J. Perspectives of undergraduate and graduate medical trainees on documenting clinical notes: Implications for medical education and informatics. Health Informatics Journal 2022;28(2):146045822210934 View
  70. Oubenali N, Messaoud S, Filiot A, Lamer A, Andrey P. Visualization of medical concepts represented using word embeddings: a scoping review. BMC Medical Informatics and Decision Making 2022;22(1) View
  71. Mugisha C, Paik I. Comparison of Neural Language Modeling Pipelines for Outcome Prediction From Unstructured Medical Text Notes. IEEE Access 2022;10:16489 View
  72. Chiavi D, Haag C, Chan A, Kamm C, Sieber C, Stanikić M, Rodgers S, Pot C, Kesselring J, Salmen A, Rapold I, Calabrese P, Manjaly Z, Gobbi C, Zecca C, Walther S, Stegmayer K, Hoepner R, Puhan M, von Wyl V. The Real-World Experiences of Persons With Multiple Sclerosis During the First COVID-19 Lockdown: Application of Natural Language Processing. JMIR Medical Informatics 2022;10(11):e37945 View
  73. Pan H, Bakalov V, Cox L, Engle M, Erickson S, Feolo M, Guo Y, Huggins W, Hwang S, Kimura M, Krzyzanowski M, Levy J, Phillips M, Qin Y, Williams D, Ramos E, Hamilton C. Identifying Datasets for Cross-Study Analysis in dbGaP using PhenX. Scientific Data 2022;9(1) View
  74. Singleton J, Li C, Akpunonu P, Abner E, Kucharska-Newton A. Using natural language processing to identify opioid use disorder in electronic health record data. International Journal of Medical Informatics 2023;170:104963 View
  75. Bacco L, Russo F, Ambrosio L, D’Antoni F, Vollero L, Vadalà G, Dell’Orletta F, Merone M, Papalia R, Denaro V. Natural language processing in low back pain and spine diseases: A systematic review. Frontiers in Surgery 2022;9 View
  76. Beck T, Shorter T, Hu Y, Li Z, Sun S, Popovici C, McQuibban N, Makraduli F, Yeung C, Rowlands T, Posma J. Auto-CORPus: A Natural Language Processing Tool for Standardizing and Reusing Biomedical Literature. Frontiers in Digital Health 2022;4 View
  77. Wyatt J, Booth G, Goldman A. Natural Language Processing and Its Use in Orthopaedic Research. Current Reviews in Musculoskeletal Medicine 2021;14(6):392 View
  78. Lu Z, Sim J, Wang J, Forrest C, Krull K, Srivastava D, Hudson M, Robison L, Baker J, Huang I. Natural Language Processing and Machine Learning Methods to Characterize Unstructured Patient-Reported Outcomes: Validation Study. Journal of Medical Internet Research 2021;23(11):e26777 View
  79. Oyebode O, Orji R. Identifying adverse drug reactions from patient reviews on social media using natural language processing. Health Informatics Journal 2023;29(1):146045822211367 View
  80. Schwartz J, Tseng E, Maruthur N, Rouhizadeh M. Identification of Prediabetes Discussions in Unstructured Clinical Documentation: Validation of a Natural Language Processing Algorithm. JMIR Medical Informatics 2022;10(2):e29803 View
  81. Narayanan S, S.S. M, Ramesh M, Rangan P, Rajan S. Deep contextual multi-task feature fusion for enhanced concept, negation and speculation detection from clinical notes. Informatics in Medicine Unlocked 2022;34:101109 View
  82. Araki K, Matsumoto N, Togo K, Yonemoto N, Ohki E, Xu L, Hasegawa Y, Satoh D, Takemoto R, Miyazaki T. Developing Artificial Intelligence Models for Extracting Oncologic Outcomes from Japanese Electronic Health Records. Advances in Therapy 2023;40(3):934 View
  83. Yan M, Gustad L, Nytrø Ø. Sepsis prediction, early detection, and identification using clinical text for machine learning: a systematic review. Journal of the American Medical Informatics Association 2022;29(3):559 View
  84. Murphy R, Klopotowska J, de Keizer N, Jager K, Leopold J, Dongelmans D, Abu-Hanna A, Schut M, Qamar U. Adverse drug event detection using natural language processing: A scoping review of supervised learning methods. PLOS ONE 2023;18(1):e0279842 View
  85. Linder J, Bastarache L, Hughey J, Peterson J. The Role of Electronic Health Records in Advancing Genomic Medicine. Annual Review of Genomics and Human Genetics 2021;22(1):219 View
  86. Hunter B, Reis S, Campbell D, Matharu S, Ratnakumar P, Mercuri L, Hindocha S, Kalsi H, Mayer E, Glampson B, Robinson E, Al-Lazikani B, Scerri L, Bloch S, Lee R. Development of a Structured Query Language and Natural Language Processing Algorithm to Identify Lung Nodules in a Cancer Centre. Frontiers in Medicine 2021;8 View
  87. Wong J, Prieto-Alhambra D, Rijnbeek P, Desai R, Reps J, Toh S. Applying Machine Learning in Distributed Data Networks for Pharmacoepidemiologic and Pharmacovigilance Studies: Opportunities, Challenges, and Considerations. Drug Safety 2022;45(5):493 View
  88. 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
  89. Dashtian H, Murthy D, Kong G. An Exploration of e-Cigarette–Related Search Items on YouTube: Network Analysis. Journal of Medical Internet Research 2022;24(1):e30679 View
  90. Levy J, Vattikonda N, Haudenschild C, Christensen B, Vaickus L. Comparison of machine-learning algorithms for the prediction of Current Procedural Terminology (CPT) codes from pathology reports. Journal of Pathology Informatics 2022;13:100165 View
  91. Wu H, Wang M, Wu J, Francis F, Chang Y, Shavick A, Dong H, Poon M, Fitzpatrick N, Levine A, Slater L, Handy A, Karwath A, Gkoutos G, Chelala C, Shah A, Stewart R, Collier N, Alex B, Whiteley W, Sudlow C, Roberts A, Dobson R. A survey on clinical natural language processing in the United Kingdom from 2007 to 2022. npj Digital Medicine 2022;5(1) View
  92. Su Q, Cheng G, Huang J. A review of research on eligibility criteria for clinical trials. Clinical and Experimental Medicine 2023 View
  93. Carrillo-Larco R, Castillo-Cara M, Lovón-Melgarejo J. Government plans in the 2016 and 2021 Peruvian presidential elections: A natural language processing analysis of the health chapters. Wellcome Open Research 2021;6:177 View
  94. Goldman A, Kathrins M. Optimized Use of the Electronic Health Record and Other Clinical Resources to Enhance the Management of Hypogonadal Men. Endocrinology and Metabolism Clinics of North America 2022;51(1):217 View
  95. Seinen T, Fridgeirsson E, Ioannou S, Jeannetot D, John L, Kors J, Markus A, Pera V, Rekkas A, Williams R, Yang C, van Mulligen E, Rijnbeek P. Use of unstructured text in prognostic clinical prediction models: a systematic review. Journal of the American Medical Informatics Association 2022;29(7):1292 View
  96. Carrillo-Larco R, Castillo-Cara M, Lovón-Melgarejo J. Government plans in the 2016 and 2021 Peruvian presidential elections: A natural language processing analysis of the health chapters. Wellcome Open Research 2021;6:177 View
  97. Xie F, Khadka N, Fassett M, Chiu V, Avila C, Shi J, Yeh M, Kawatkar A, Mensah N, Sacks D, Getahun D. Identification of Preterm Labor Evaluation Visits and Extraction of Cervical Length Measures from Electronic Health Records Within a Large Integrated Health Care System: Algorithm Development and Validation. JMIR Medical Informatics 2022;10(9):e37896 View
  98. 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
  99. Lareyre F, Behrendt C, Chaudhuri A, Ayache N, Delingette H, Raffort J. Big Data and Artificial Intelligence in Vascular Surgery: Time for Multidisciplinary Cross-Border Collaboration. Angiology 2022;73(8):697 View
  100. Zanotto B, Beck da Silva Etges A, dal Bosco A, Cortes E, Ruschel R, De Souza A, Andrade C, Viegas F, Canuto S, Luiz W, Ouriques Martins S, Vieira R, Polanczyk C, André Gonçalves M. Stroke Outcome Measurements From Electronic Medical Records: Cross-sectional Study on the Effectiveness of Neural and Nonneural Classifiers. JMIR Medical Informatics 2021;9(11):e29120 View
  101. Peng J, Xu D, Lee R, Xu S, Zhou Y, Wang K. Expediting knowledge acquisition by a web framework for Knowledge Graph Exploration and Visualization (KGEV): case studies on COVID-19 and Human Phenotype Ontology. BMC Medical Informatics and Decision Making 2022;22(S2) View
  102. Joyce C, Markossian T, Nikolaides J, Ramsey E, Thompson H, Rojas J, Sharma B, Dligach D, Oguss M, Cooper R, Afshar M. The Evaluation of a Clinical Decision Support Tool Using Natural Language Processing to Screen Hospitalized Adults for Unhealthy Substance Use: Protocol for a Quasi-Experimental Design. JMIR Research Protocols 2022;11(12):e42971 View
  103. Uthman O, Court R, Enderby J, Al-Khudairy L, Nduka C, Mistry H, Melendez-Torres G, Taylor-Phillips S, Clarke A. Increasing comprehensiveness and reducing workload in a systematic review of complex interventions using automated machine learning. Health Technology Assessment 2022:1 View
  104. Cuenca-Zaldívar J, Torrente-Regidor M, Martín-Losada L, Fernández-De-Las-Peñas C, Florencio L, Sousa P, Palacios-Ceña D. Exploring Sentiment and Care Management of Hospitalized Patients During the First Wave of the COVID-19 Pandemic Using Electronic Nursing Health Records: Descriptive Study. JMIR Medical Informatics 2022;10(5):e38308 View
  105. González-Juanatey C, Anguita-Sánchez M, Barrios V, Núñez-Gil I, Gómez-Doblas J, García-Moll X, Lafuente-Gormaz C, Rollán-Gómez M, Peral-Disdier V, Martínez-Dolz L, Rodríguez-Santamarta M, Viñolas-Prat X, Soriano-Colomé T, Muñoz-Aguilera R, Plaza I, Curcio-Ruigómez A, Orts-Soler E, Segovia J, Fanjul V, Cequier Á. Major Adverse Cardiovascular Events in Coronary Type 2 Diabetic Patients: Identification of Associated Factors Using Electronic Health Records and Natural Language Processing. Journal of Clinical Medicine 2022;11(20):6004 View
  106. Bhattacharya M, Bhat S, Tripathy S, Bansal A, Choudhary M. Improving biomedical named entity recognition through transfer learning and asymmetric tri-training. Procedia Computer Science 2023;218:2723 View
  107. Ruckdeschel J, Riley M, Parsatharathy S, Chamarthi R, Rajagopal C, Hsu H, Mangold D, Driscoll C. Unstructured Data Are Superior to Structured Data for Eliciting Quantitative Smoking History From the Electronic Health Record. JCO Clinical Cancer Informatics 2023;(7) View
  108. Siegersma K, Evers M, Bots S, Groepenhoff F, Appelman Y, Hofstra L, Tulevski I, Somsen G, den Ruijter H, Spruit M, Onland-Moret N. Development of a Pipeline for Adverse Drug Reaction Identification in Clinical Notes: Word Embedding Models and String Matching. JMIR Medical Informatics 2022;10(1):e31063 View
  109. Horng H, Steinkamp J, Kahn C, Cook T. Ensemble Approaches to Recognize Protected Health Information in Radiology Reports. Journal of Digital Imaging 2022;35(6):1694 View
  110. Carrillo-Larco R, Castillo-Cara M, Lovón-Melgarejo J. Government plans in the 2016 and 2021 Peruvian presidential elections: A natural language processing analysis of the health chapters. Wellcome Open Research 2022;6:177 View
  111. Greve K, Ni Y, Bailes A, Vargus‐Adams J, Miley A, Aronow B, McMahon M, Kurowski B, Mitelpunkt A. Gross motor function prediction using natural language processing in cerebral palsy. Developmental Medicine & Child Neurology 2023;65(1):100 View
  112. Ma Y, Flaherty M. Using Symptoms and Healthcare Encounters to Capture a Rare Disease: A Study of Clinical Notes of the Alpha‐Gal Meat Allergy. Proceedings of the Association for Information Science and Technology 2021;58(1):273 View
  113. Noori A, Magdamo C, Liu X, Tyagi T, Li Z, Kondepudi A, Alabsi H, Rudmann E, Wilcox D, Brenner L, Robbins G, Moura L, Zafar S, Benson N, Hsu J, R Dickson J, Serrano-Pozo A, Hyman B, Blacker D, Westover M, Mukerji S, Das S. Development and Evaluation of a Natural Language Processing Annotation Tool to Facilitate Phenotyping of Cognitive Status in Electronic Health Records: Diagnostic Study. Journal of Medical Internet Research 2022;24(8):e40384 View
  114. Binsfeld Gonçalves L, Nesic I, Obradovic M, Stieltjes B, Weikert T, Bremerich J. Natural Language Processing and Graph Theory: Making Sense of Imaging Records in a Novel Representation Frame. JMIR Medical Informatics 2022;10(12):e40534 View
  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
  120. Somani S, Yoffie S, Teng S, Havaldar S, Nadkarni G, Zhao S, Glicksberg B. Development and validation of techniques for phenotyping ST-elevation myocardial infarction encounters from electronic health records. JAMIA Open 2021;4(3) View
  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
  136. Wi S, Goldhoff P, Fuller L, Grewal K, Wentzensen N, Clarke M, Lorey T. Using Natural Language Processing to Improve Discrete Data Capture From Interpretive Cervical Biopsy Diagnoses at a Large Health Care Organization. Archives of Pathology & Laboratory Medicine 2023;147(2):222 View
  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
  140. Le T, Noumeir R, Rambaud J, Sans G, Jouvet P. Detecting of a Patient's Condition From Clinical Narratives Using Natural Language Representation. IEEE Open Journal of Engineering in Medicine and Biology 2022;3:142 View
  141. Houssein E, Mohamed R, Ali A. Machine Learning Techniques for Biomedical Natural Language Processing: A Comprehensive Review. IEEE Access 2021;9:140628 View
  142. Krittanawong C, Johnson K, Choi E, Kaplin S, Venner E, Murugan M, Wang Z, Glicksberg B, Amos C, Schatz M, Tang W. Artificial Intelligence and Cardiovascular Genetics. Life 2022;12(2):279 View
  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
  146. Calleja Panero J, de la Poza G, Hidalgo L, Aguilera Sancho-Tello M, Torras X, Santos de Lamadrid R, Maté C, Sánchez Antolín G. Patient journey of individuals tested for HCV in Spain: LiverTAI, a retrospective analysis of EHRs through natural language processing. Gastroenterología y Hepatología 2022 View
  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
  148. Woersching J, Van Cleave J, Egleston B, Ma C, Haber J, Chyun D. Data Quality of Automated Comorbidity Lists in Patients With Mental Health and Substance Use Disorders. CIN: Computers, Informatics, Nursing 2022;40(7):497 View
  149. 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
  150. Ben Miled Z, Dexter P, Grout R, Boustani M. Feature engineering from medical notes: A case study of dementia detection. Heliyon 2023:e14636 View

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