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Citing this Article

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Published on 11.11.16 in Vol 4, No 4 (2016): Oct-Dec

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

Works citing "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"

Le Zheng, Yue Wang, Shiying Hao, Andrew Y Shin, Bo Jin, Anh D Ngo, Medina S Jackson-Browne, Daniel J Feller, Tianyun Fu, Karena Zhang, Xin Zhou, Chunqing Zhu, Dorothy Dai, Yunxian Yu, Gang Zheng, Yu-Ming Li, Doff B McElhinney, Devore S Culver, Shaun T Alfreds, Frank Stearns, Karl G Sylvester, Eric Widen, Xuefeng Bruce Ling

JMIR Med Inform 2016 (Nov 11); 4(4):e37 

According to Crossref, the following articles are citing this article (DOI 10.2196/medinform.6328):

(note that this is only a small subset of citations)

  1. Ye Q, Patel R, Khan U, Boren SA, Kim MS. 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)
    CrossRef
  2. Afzal N, Mallipeddi VP, Sohn S, Liu H, Chaudhry R, Scott CG, Kullo IJ, Arruda-Olson AM. Natural language processing of clinical notes for identification of critical limb ischemia. International Journal of Medical Informatics 2018;111:83
    CrossRef
  3. Moon S, Liu S, Scott CG, Samudrala S, Abidian MM, Geske JB, Noseworthy PA, Shellum JL, Chaudhry R, Ommen SR, Nishimura RA, Liu H, Arruda-Olson AM. Automated extraction of sudden cardiac death risk factors in hypertrophic cardiomyopathy patients by natural language processing. International Journal of Medical Informatics 2019;128:32
    CrossRef
  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 DS, Alfreds ST, Stearns F, Kanov L, Bhatia A, Sylvester KG, Widen E, McElhinney DB, Ling XB. 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
    CrossRef
  5. Hao S, Fu T, Wu Q, Jin B, Zhu C, Hu Z, Guo Y, Zhang Y, Yu Y, Fouts T, Ng P, Culver DS, Alfreds ST, Stearns F, Sylvester KG, Widen E, McElhinney DB, Ling XB. 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
    CrossRef
  6. Sheikhalishahi S, Miotto R, Dudley JT, Lavelli A, Rinaldi F, Osmani V. Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic Review. JMIR Medical Informatics 2019;7(2):e12239
    CrossRef
  7. Kersloot MG, Lau F, Abu-Hanna A, Arts DL, Cornet R. Automated SNOMED CT concept and attribute relationship detection through a web-based implementation of cTAKES. Journal of Biomedical Semantics 2019;10(1)
    CrossRef
  8. Hendrickx JO, van Gastel J, Leysen H, Martin B, Maudsley S, Michel MC. High-dimensionality Data Analysis of Pharmacological Systems Associated with Complex Diseases. Pharmacological Reviews 2020;72(1):191
    CrossRef
  9. Patel YR, Robbins JM, Kurgansky KE, Imran T, Orkaby AR, McLean RR, Ho Y, Cho K, Michael Gaziano J, Djousse L, Gagnon DR, Joseph J. Development and validation of a heart failure with preserved ejection fraction cohort using electronic medical records. BMC Cardiovascular Disorders 2018;18(1)
    CrossRef
  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
    CrossRef
  11. Yu C, Lin Y, Lin C, Lin S, Wu JL, 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
    CrossRef
  12. Duncan I, Fitzner K, Handmaker KE. Augmented Intelligence: Enhancing the Roles of Health Actuaries and Health Economists for Population Health Management. Population Health Management 2018;21(5):341
    CrossRef
  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 DB, Li Y, Culver DS, Alfreds ST, Stearns F, Sylvester KG, Widen E, Ling XB, Hu C. Defining and characterizing the critical transition state prior to the type 2 diabetes disease. PLOS ONE 2017;12(7):e0180937
    CrossRef
  14. Chen X, Xie H, Wang FL, 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)
    CrossRef
  15. Wi C, Sohn S, Rolfes MC, Seabright A, Ryu E, Voge G, Bachman KA, Park MA, Kita H, Croghan IT, Liu H, Juhn YJ. 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
    CrossRef
  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
    CrossRef
  17. . Use of online information in diabetes. Journal of Diabetes 2020;12(4):268
    CrossRef
  18. Guetterman TC, Chang T, DeJonckheere M, Basu T, Scruggs E, Vydiswaran VV. Augmenting Qualitative Text Analysis with Natural Language Processing: Methodological Study. Journal of Medical Internet Research 2018;20(6):e231
    CrossRef
  19. Wang X, Zhang Y, Hao S, Zheng L, Liao J, Ye C, Xia M, Wang O, Liu M, Weng CH, Duong SQ, Jin B, Alfreds ST, Stearns F, Kanov L, Sylvester KG, Widen E, McElhinney DB, Ling XB. 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
    CrossRef
  20. Lee S, Doktorchik C, Martin EA, D'Souza AG, Eastwood C, Shaheen AA, 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
    CrossRef
  21. Sai Prashanthi G, Deva A, Vadapalli R, Das AV. 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
    CrossRef
  22. Turchin A, Florez Builes LF. 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
    CrossRef
  23. Chen X, Cheng G, Wang FL, Tao X, Xie H, Xu L. Machine and cognitive intelligence for human health: systematic review. Brain Informatics 2022;9(1)
    CrossRef
  24. Kuo H, Hao S, Jin B, Chou CJ, Han Z, Chang L, Huang Y, Hwa K, Whitin JC, Sylvester KG, Reddy CD, Chubb H, Ceresnak SR, Kanegaye JT, Tremoulet AH, Burns JC, McElhinney D, Cohen HJ, Ling XB. Single center blind testing of a US multi-center validated diagnostic algorithm for Kawasaki disease in Taiwan. Frontiers in Immunology 2022;13
    CrossRef
  25. Pethani F, Dunn AG. Natural language processing for clinical notes in dentistry: A systematic review. Journal of Biomedical Informatics 2023;138:104282
    CrossRef
  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
    CrossRef
  27. Montoto C, Gisbert JP, Guerra I, Plaza R, Pajares Villarroya R, Moreno Almazán L, López Martín MDC, 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
    CrossRef
  28. Wang L, Zhang Y, Chignell M, Shan B, Sheehan KA, Razak F, Verma A. Boosting Delirium Identification Accuracy With Sentiment-Based Natural Language Processing: Mixed Methods Study. JMIR Medical Informatics 2022;10(12):e38161
    CrossRef
  29. Abu Lekham L, Wang Y, Hey E, Khasawneh MT. 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
    CrossRef
  30. Ling XB, Kuo H, Hao S, Jin B, Chou CJ, Han Z, Chang L, Huang Y, Hwa K, Sylvester KG, Reddy CD, Chubb H, Ceresnak SR, Kanegaye JT, Tremoulet A, Burns J, McElhinney D, Cohen HJ, whitin J. Single Center Blind Testing of a Us Multi-Center Validated Diagnostic Algorithm for Kawasaki Disease in Asia. SSRN Electronic Journal 2022;
    CrossRef
  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
    CrossRef
  32. Borna S, Maniaci MJ, Haider CR, Maita KC, Torres-Guzman RA, Avila FR, Lunde JJ, Coffey JD, Demaerschalk BM, Forte AJ. Artificial Intelligence Models in Health Information Exchange: A Systematic Review of Clinical Implications. Healthcare 2023;11(18):2584
    CrossRef
  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;
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/medinform.6328):

  1. Buchlak QD, Esmaili N, Bennett C, Farrokhi F. Machine Learning in Clinical Neuroscience. 2022. Chapter 32:277
    CrossRef
  2. Manaka T, van Zyl T, Kar D. Artificial Intelligence Research. 2022. Chapter 4:46
    CrossRef