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

Natural Language Processing (692) Tools, Programs and Algorithms (266) Diabetes-specific EHR Improvements (33) Patient Experiences with Diabetes Technology (32)

Published on in Vol 4, No 4 (2016): Oct-Dec

Web-based Real-Time Case Finding for the Population Health Management of Patients With Diabetes Mellitus: A Prospective Validation of the Natural Language Processing–Based Algorithm With Statewide Electronic Medical Records

Web-based Real-Time Case Finding for the Population Health Management of Patients With Diabetes Mellitus: A Prospective Validation of the Natural Language Processing–Based Algorithm With Statewide Electronic Medical Records

Web-based Real-Time Case Finding for the Population Health Management of Patients With Diabetes Mellitus: A Prospective Validation of the Natural Language Processing–Based Algorithm With Statewide Electronic Medical Records

Authors of this article:

Le Zheng1, 2 Author Orcid Image ;   Yue Wang2, 3 Author Orcid Image ;   Shiying Hao2 Author Orcid Image ;   Andrew Y Shin2 Author Orcid Image ;   Bo Jin4 Author Orcid Image ;   Anh D Ngo4 Author Orcid Image ;   Medina S Jackson-Browne4 Author Orcid Image ;   Daniel J Feller4 Author Orcid Image ;   Tianyun Fu4 Author Orcid Image ;   Karena Zhang2 Author Orcid Image ;   Xin Zhou5 Author Orcid Image ;   Chunqing Zhu4 Author Orcid Image ;   Dorothy Dai4 Author Orcid Image ;   Yunxian Yu6 Author Orcid Image ;   Gang Zheng3 Author Orcid Image ;   Yu-Ming Li5 Author Orcid Image ;   Doff B McElhinney2 Author Orcid Image ;   Devore S Culver7 Author Orcid Image ;   Shaun T Alfreds7 Author Orcid Image ;   Frank Stearns4 Author Orcid Image ;   Karl G Sylvester2 Author Orcid Image ;   Eric Widen4 Author Orcid Image ;   Xuefeng Bruce Ling2, 6 Author Orcid Image
Article Authors Cited by (40) Tweetations (2) Metrics

Journals

  1. Ye Q, Patel R, Khan U, Boren S, Kim M. Evaluation of provider documentation patterns as a tool to deliver ongoing patient‐centred diabetes education and support. International Journal of Clinical Practice 2020;74(3) View
  2. Afzal N, Mallipeddi V, Sohn S, Liu H, Chaudhry R, Scott C, Kullo I, Arruda-Olson A. Natural language processing of clinical notes for identification of critical limb ischemia. International Journal of Medical Informatics 2018;111:83 View
  3. Moon S, Liu S, Scott C, Samudrala S, Abidian M, Geske J, Noseworthy P, Shellum J, Chaudhry R, Ommen S, Nishimura R, Liu H, Arruda-Olson A. Automated extraction of sudden cardiac death risk factors in hypertrophic cardiomyopathy patients by natural language processing. International Journal of Medical Informatics 2019;128:32 View
  4. Guo Y, Zheng G, Fu T, Hao S, Ye C, Zheng L, Liu M, Xia M, Jin B, Zhu C, Wang O, Wu Q, Culver D, Alfreds S, Stearns F, Kanov L, Bhatia A, Sylvester K, Widen E, McElhinney D, Ling X. Assessing Statewide All-Cause Future One-Year Mortality: Prospective Study With Implications for Quality of Life, Resource Utilization, and Medical Futility. Journal of Medical Internet Research 2018;20(6):e10311 View
  5. Hao S, Fu T, Wu Q, Jin B, Zhu C, Hu Z, Guo Y, Zhang Y, Yu Y, Fouts T, Ng P, Culver D, Alfreds S, Stearns F, Sylvester K, Widen E, McElhinney D, Ling X. Estimating One-Year Risk of Incident Chronic Kidney Disease: Retrospective Development and Validation Study Using Electronic Medical Record Data From the State of Maine. JMIR Medical Informatics 2017;5(3):e21 View
  6. Sheikhalishahi S, Miotto R, Dudley J, Lavelli A, Rinaldi F, Osmani V. Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic Review. JMIR Medical Informatics 2019;7(2):e12239 View
  7. Kersloot M, Lau F, Abu-Hanna A, Arts D, Cornet R. Automated SNOMED CT concept and attribute relationship detection through a web-based implementation of cTAKES. Journal of Biomedical Semantics 2019;10(1) View
  8. Hendrickx J, van Gastel J, Leysen H, Martin B, Maudsley S, Michel M. High-dimensionality Data Analysis of Pharmacological Systems Associated with Complex Diseases. Pharmacological Reviews 2020;72(1):191 View
  9. Patel Y, Robbins J, Kurgansky K, Imran T, Orkaby A, McLean R, Ho Y, Cho K, Michael Gaziano J, Djousse L, Gagnon D, Joseph J. Development and validation of a heart failure with preserved ejection fraction cohort using electronic medical records. BMC Cardiovascular Disorders 2018;18(1) View
  10. Nguyen H, Agu E, Tulu B, Strong D, Mombini H, Pedersen P, Lindsay C, Dunn R, Loretz L. Machine learning models for synthesizing actionable care decisions on lower extremity wounds. Smart Health 2020;18:100139 View
  11. Yu C, Lin Y, Lin C, Lin S, Wu J, Chang S. Development of an Online Health Care Assessment for Preventive Medicine: A Machine Learning Approach. Journal of Medical Internet Research 2020;22(6):e18585 View
  12. Duncan I, Fitzner K, Handmaker K. Augmented Intelligence: Enhancing the Roles of Health Actuaries and Health Economists for Population Health Management. Population Health Management 2018;21(5):341 View
  13. Jin B, Liu R, Hao S, Li Z, Zhu C, Zhou X, Chen P, Fu T, Hu Z, Wu Q, Liu W, Liu D, Yu Y, Zhang Y, McElhinney D, Li Y, Culver D, Alfreds S, Stearns F, Sylvester K, Widen E, Ling X, Hu C. Defining and characterizing the critical transition state prior to the type 2 diabetes disease. PLOS ONE 2017;12(7):e0180937 View
  14. Chen X, Xie H, Wang F, Liu Z, Xu J, Hao T. A bibliometric analysis of natural language processing in medical research. BMC Medical Informatics and Decision Making 2018;18(S1) View
  15. Wi C, Sohn S, Rolfes M, Seabright A, Ryu E, Voge G, Bachman K, Park M, Kita H, Croghan I, Liu H, Juhn Y. Application of a Natural Language Processing Algorithm to Asthma Ascertainment. An Automated Chart Review. American Journal of Respiratory and Critical Care Medicine 2017;196(4):430 View
  16. Shim H, Ailshire J, Zelinski E, Crimmins E. The Health and Retirement Study: Analysis of Associations Between Use of the Internet for Health Information and Use of Health Services at Multiple Time Points. Journal of Medical Internet Research 2018;20(5):e200 View
  17. Bloomgarden Z. Use of online information in diabetes. Journal of Diabetes 2020;12(4):268 View
  18. Guetterman T, Chang T, DeJonckheere M, Basu T, Scruggs E, Vydiswaran V. Augmenting Qualitative Text Analysis with Natural Language Processing: Methodological Study. Journal of Medical Internet Research 2018;20(6):e231 View
  19. Wang X, Zhang Y, Hao S, Zheng L, Liao J, Ye C, Xia M, Wang O, Liu M, Weng C, Duong S, Jin B, Alfreds S, Stearns F, Kanov L, Sylvester K, Widen E, McElhinney D, Ling X. Prediction of the 1-Year Risk of Incident Lung Cancer: Prospective Study Using Electronic Health Records from the State of Maine. Journal of Medical Internet Research 2019;21(5):e13260 View
  20. Lee S, Doktorchik C, Martin E, D'Souza A, Eastwood C, Shaheen A, Naugler C, Lee J, Quan H. Electronic Medical Record–Based Case Phenotyping for the Charlson Conditions: Scoping Review. JMIR Medical Informatics 2021;9(2):e23934 View
  21. Sai Prashanthi G, Deva A, Vadapalli R, Das A. Automated Categorization of Systemic Disease and Duration From Electronic Medical Record System Data Using Finite-State Machine Modeling: Prospective Validation Study. JMIR Formative Research 2020;4(12):e24490 View
  22. 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
  23. Chen X, Cheng G, Wang F, Tao X, Xie H, Xu L. Machine and cognitive intelligence for human health: systematic review. Brain Informatics 2022;9(1) View
  24. Kuo H, Hao S, Jin B, Chou C, Han Z, Chang L, Huang Y, Hwa K, Whitin J, Sylvester K, Reddy C, Chubb H, Ceresnak S, Kanegaye J, Tremoulet A, Burns J, McElhinney D, Cohen H, Ling X. Single center blind testing of a US multi-center validated diagnostic algorithm for Kawasaki disease in Taiwan. Frontiers in Immunology 2022;13 View
  25. Pethani F, Dunn A. Natural language processing for clinical notes in dentistry: A systematic review. Journal of Biomedical Informatics 2023;138:104282 View
  26. Wang S, Song F, Qiao Q, Liu Y, Chen J, Ma J. A Comparative Study of Natural Language Processing Algorithms Based on Cities Changing Diabetes Vulnerability Data. Healthcare 2022;10(6):1119 View
  27. Montoto C, Gisbert J, Guerra I, Plaza R, Pajares Villarroya R, Moreno Almazán L, López Martín M, Domínguez Antonaya M, Vera Mendoza I, Aparicio J, Martínez V, Tagarro I, Fernandez-Nistal A, Canales L, Menke S, Gomollón F. Evaluation of Natural Language Processing for the Identification of Crohn Disease–Related Variables in Spanish Electronic Health Records: A Validation Study for the PREMONITION-CD Project. JMIR Medical Informatics 2022;10(2):e30345 View
  28. 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
  29. Abu Lekham L, Wang Y, Hey E, Khasawneh M. Multi-label text mining to identify reasons for appointments to drive population health analytics at a primary care setting. Neural Computing and Applications 2022;34(17):14971 View
  30. Ling X, Kuo H, Hao S, Jin B, Chou C, Han Z, Chang L, Huang Y, Hwa K, Sylvester K, Reddy C, Chubb H, Ceresnak S, Kanegaye J, Tremoulet A, Burns J, McElhinney D, Cohen H, whitin J. Single Center Blind Testing of a Us Multi-Center Validated Diagnostic Algorithm for Kawasaki Disease in Asia. SSRN Electronic Journal 2022 View
  31. Towler L, Bondaronek P, Papakonstantinou T, Amlôt R, Chadborn T, Ainsworth B, Yardley L. Applying machine-learning to rapidly analyze large qualitative text datasets to inform the COVID-19 pandemic response: comparing human and machine-assisted topic analysis techniques. Frontiers in Public Health 2023;11 View
  32. Borna S, Maniaci M, Haider C, Maita K, Torres-Guzman R, Avila F, Lunde J, Coffey J, Demaerschalk B, Forte A. Artificial Intelligence Models in Health Information Exchange: A Systematic Review of Clinical Implications. Healthcare 2023;11(18):2584 View
  33. Petit-Jean T, Gérardin C, Berthelot E, Chatellier G, Frank M, Tannier X, Kempf E, Bey R. Collaborative and privacy-enhancing workflows on a clinical data warehouse: an example developing natural language processing pipelines to detect medical conditions. Journal of the American Medical Informatics Association 2024;31(6):1280 View
  34. Guo Q, Fu B, Tian Y, Xu S, Meng X. Recent progress in artificial intelligence and machine learning for novel diabetes mellitus medications development. Current Medical Research and Opinion 2024;40(9):1483 View

Books/Policy Documents

  1. Buchlak Q, Esmaili N, Bennett C, Farrokhi F. Machine Learning in Clinical Neuroscience. View
  2. Manaka T, van Zyl T, Kar D. Artificial Intelligence Research. View