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

Preprints (earlier versions) of this paper are available at, 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


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  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
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  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
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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;3:100036 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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  158. Kodeboina M, Piayda K, Jenniskens I, Vyas P, Chen S, Pesigan R, Ferko N, Patel B, Dobrin A, Habib J, Franke J. Challenges and Burdens in the Coronary Artery Disease Care Pathway for Patients Undergoing Percutaneous Coronary Intervention: A Contemporary Narrative Review. International Journal of Environmental Research and Public Health 2023;20(9):5633 View
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  162. Jeon E, Kim A, Lee J, Heo H, Lee H, Woo K. Developing a Classification Algorithm for Prediabetes Risk Detection From Home Care Nursing Notes. CIN: Computers, Informatics, Nursing 2023;41(7):539 View
  163. Sajdeya R, Mardini M, Tighe P, Ison R, Bai C, Jugl S, Hanzhi G, Zandbiglari K, Adiba F, Winterstein A, Pearson T, Cook R, Rouhizadeh M. Developing and validating a natural language processing algorithm to extract preoperative cannabis use status documentation from unstructured narrative clinical notes. Journal of the American Medical Informatics Association 2023;30(8):1418 View
  164. Sheikhalishahi S, Bhattacharyya A, Celi L, Osmani V. An interpretable deep learning model for time-series electronic health records: Case study of delirium prediction in critical care. Artificial Intelligence in Medicine 2023;144:102659 View
  165. Kusa W, Mendoza Ó, Knoth P, Pasi G, Hanbury A. Effective matching of patients to clinical trials using entity extraction and neural re-ranking. Journal of Biomedical Informatics 2023;144:104444 View
  166. Alkhalaf M, Zhang Z, Chang H, Wei W, Yin M, Deng C, Yu P. Malnutrition and its contributing factors for older people living in residential aged care facilities: Insights from natural language processing of aged care records. Technology and Health Care 2023;31(6):2267 View
  167. Garriga R, Buda T, Guerreiro J, Omaña Iglesias J, Estella Aguerri I, Matić A. Combining clinical notes with structured electronic health records enhances the prediction of mental health crises. Cell Reports Medicine 2023;4(11):101260 View
  168. Lee K, Liu Z, Chandran U, Kalsekar I, Laxmanan B, Higashi M, Jun T, Ma M, Li M, Mai Y, Gilman C, Wang T, Ai L, Aggarwal P, Pan Q, Oh W, Stolovitzky G, Schadt E, Wang X. Detecting Ground Glass Opacity Features in Patients With Lung Cancer: Automated Extraction and Longitudinal Analysis via Deep Learning–Based Natural Language Processing. JMIR AI 2023;2:e44537 View
  169. 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-Cubero J, Fanjul V, Marín-Corral J, Cequier Á, SAVANA Research Group . Impact of Advanced Age on the Incidence of Major Adverse Cardiovascular Events in Patients with Type 2 Diabetes Mellitus and Stable Coronary Artery Disease in a Real-World Setting in Spain. Journal of Clinical Medicine 2023;12(16):5218 View
  170. Magoc T, Allen K, McDonnell C, Russo J, Cummins J, Vest J, Harle C. Generalizability and portability of natural language processing system to extract individual social risk factors. International Journal of Medical Informatics 2023;177:105115 View
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  172. Serna García G, Al Khalaf R, Invernici F, Ceri S, Bernasconi A. CoVEffect: interactive system for mining the effects of SARS-CoV-2 mutations and variants based on deep learning. GigaScience 2022;12 View
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  174. Mäkitie A, Alabi R, Ng S, Takes R, Robbins K, Ronen O, Shaha A, Bradley P, Saba N, Nuyts S, Triantafyllou A, Piazza C, Rinaldo A, Ferlito A. Artificial Intelligence in Head and Neck Cancer: A Systematic Review of Systematic Reviews. Advances in Therapy 2023;40(8):3360 View
  175. Gala D, Makaryus A. The Utility of Language Models in Cardiology: A Narrative Review of the Benefits and Concerns of ChatGPT-4. International Journal of Environmental Research and Public Health 2023;20(15):6438 View
  176. Shelest-Szumilas O, Wozniak M. The Fears and Hopes of Ukrainian Migrant Workers in Poland in the Pandemic Era. Journal of International Migration and Integration 2023;24(4):1957 View
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  178. De Rosario H, Pitarch-Corresa S, Pedrosa I, Vidal-Pedrós M, de Otto-López B, García-Mieres H, Álvarez-Rodríguez L. Applications of Natural Language Processing for the Management of Stroke Disorders: Scoping Review. JMIR Medical Informatics 2023;11:e48693 View
  179. Harrison J, Yala A, Mikhael P, Roldan J, Ciprani D, Michelakos T, Bolm L, Qadan M, Ferrone C, Fernandez-del Castillo C, Lillemoe K, Santus E, Hughes K. Successful Development of a Natural Language Processing Algorithm for Pancreatic Neoplasms and Associated Histologic Features. Pancreas 2023;52(4):e219 View
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  182. Ali H. Generative Pre‐Trained Transformer 4 in healthcare: Challenges, opportunities, and recommendations. Medicine Advances 2023;1(2):163 View
  183. Loscertales J, Abrisqueta-Costa P, Gutierrez A, Hernández-Rivas J, Andreu-Lapiedra R, Mora A, Leiva-Farré C, López-Roda M, Callejo-Mellén Á, Álvarez-García E, García-Marco J. Real-World Evidence on the Clinical Characteristics and Management of Patients with Chronic Lymphocytic Leukemia in Spain Using Natural Language Processing: The SRealCLL Study. Cancers 2023;15(16):4047 View
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  194. Jiang Y, Pang P, Wong D, Kan H. Natural Language Processing Adoption in Governments and Future Research Directions: A Systematic Review. Applied Sciences 2023;13(22):12346 View
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  199. Fass O, Rogers B, Gyawali C. Artificial Intelligence Tools for Improving Manometric Diagnosis of Esophageal Dysmotility. Current Gastroenterology Reports 2024;26(4):115 View
  200. Panahi S, Mayo J, Kennedy E, Christensen L, Kamineni S, Sagiraju H, Cooper T, Tate D, Rupper R, Pugh M. Identifying clinical phenotypes of frontotemporal dementia in post-9/11 era veterans using natural language processing. Frontiers in Neurology 2024;15 View
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  202. Eyre H, Alba P, Gibson C, Gatsby E, Lynch K, Patterson O, DuVall S. Bridging information gaps in menopause status classification through natural language processing. JAMIA Open 2024;7(1) 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
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