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

Artificial Intelligence (1409) Clinical Informatics (1045) Clinical Information and Decision Making (1426) Decision Support for Health Professionals (1203) Electronic Health Records (1067) Machine Learning (1491) Visualization in eHealth (60) Heart Failure Self-Management (154)

Published on in Vol 22, No 9 (2020): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/20645, first published .
Marrying Medical Domain Knowledge With Deep Learning on Electronic Health Records: A Deep Visual Analytics Approach

Marrying Medical Domain Knowledge With Deep Learning on Electronic Health Records: A Deep Visual Analytics Approach

Marrying Medical Domain Knowledge With Deep Learning on Electronic Health Records: A Deep Visual Analytics Approach

Authors of this article:

Rui Li1 Author Orcid Image ;   Changchang Yin1 Author Orcid Image ;   Samuel Yang1, 2 Author Orcid Image ;   Buyue Qian3 Author Orcid Image ;   Ping Zhang1 Author Orcid Image
Article Authors Cited by (24) Tweetations (8) Metrics

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  1. Afzal M, Hussain M, Hussain J, Bang J, Lee S. COVID-19 Knowledge Resource Categorization and Tracking: Conceptual Framework Study. Journal of Medical Internet Research 2021;23(6):e29730 View
  2. Deng L, Chen L, Yang T, Liu M, Li S, Jiang T. Constructing High-Fidelity Phenotype Knowledge Graphs for Infectious Diseases With a Fine-Grained Semantic Information Model: Development and Usability Study. Journal of Medical Internet Research 2021;23(6):e26892 View
  3. Fang H, Tan N, Tan W, Oei R, Lee M, Hsu W. Patient similarity analytics for explainable clinical risk prediction. BMC Medical Informatics and Decision Making 2021;21(1) View
  4. Haymond S, McCudden C. Rise of the Machines: Artificial Intelligence and the Clinical Laboratory. The Journal of Applied Laboratory Medicine 2021;6(6):1640 View
  5. Penso M, Solbiati S, Moccia S, Caiani E. Decision Support Systems in HF based on Deep Learning Technologies. Current Heart Failure Reports 2022;19(2):38 View
  6. Ooge J, Stiglic G, Verbert K. Explaining artificial intelligence with visual analytics in healthcare. WIREs Data Mining and Knowledge Discovery 2022;12(1) View
  7. Carvalho R, Morgado A, Andrade C, Nedelcu T, Carreiro A, Vasconcelos M. Integrating Domain Knowledge into Deep Learning for Skin Lesion Risk Prioritization to Assist Teledermatology Referral. Diagnostics 2021;12(1):36 View
  8. Oei R, Hsu W, Lee M, Tan N. Using similar patients to predict complication in patients with diabetes, hypertension, and lipid disorder: a domain knowledge-infused convolutional neural network approach. Journal of the American Medical Informatics Association 2023;30(2):273 View
  9. van der Linden S, Sevastjanova R, Funk M, El-Assady M. MediCoSpace : Visual Decision-Support for Doctor-Patient Consultations using Medical Concept Spaces from EHRs. ACM Transactions on Management Information Systems 2023;14(2):1 View
  10. Zhang H, Wang X, Liu J, Zhang L, Ji L. Chinese named entity recognition method for the finance domain based on enhanced features and pretrained language models. Information Sciences 2023;625:385 View
  11. La Rosa B, Blasilli G, Bourqui R, Auber D, Santucci G, Capobianco R, Bertini E, Giot R, Angelini M. State of the Art of Visual Analytics for eXplainable Deep Learning. Computer Graphics Forum 2023;42(1):319 View
  12. Oberste L, Heinzl A. User-Centric Explainability in Healthcare: A Knowledge-Level Perspective of Informed Machine Learning. IEEE Transactions on Artificial Intelligence 2023;4(4):840 View
  13. Yang Z, Lin Y, Xu Y, Hu J, Dong S. Interpretable Disease Prediction via Path Reasoning over medical knowledge graphs and admission history. Knowledge-Based Systems 2023;281:111082 View
  14. Huang Z, Witschard D, Kucher K, Kerren A. VA + Embeddings STAR: A State‐of‐the‐Art Report on the Use of Embeddings in Visual Analytics. Computer Graphics Forum 2023;42(3):539 View
  15. Islam M, Akter S, Islam L, Razzak I, Wang X, Xu G. Strategies for evaluating visual analytics systems: A systematic review and new perspectives. Information Visualization 2024;23(1):84 View
  16. Miranda O, Fan P, Qi X, Wang H, Brannock M, Kosten T, Ryan N, Kirisci L, Wang L. DeepBiomarker2: Prediction of Alcohol and Substance Use Disorder Risk in Post-Traumatic Stress Disorder Patients Using Electronic Medical Records and Multiple Social Determinants of Health. Journal of Personalized Medicine 2024;14(1):94 View
  17. Oss Boll H, Amirahmadi A, Ghazani M, Morais W, Freitas E, Soliman A, Etminani F, Byttner S, Recamonde-Mendoza M. Graph neural networks for clinical risk prediction based on electronic health records: A survey. Journal of Biomedical Informatics 2024;151:104616 View
  18. Petmezas G, Papageorgiou V, Vassilikos V, Pagourelias E, Tsaklidis G, Katsaggelos A, Maglaveras N. Recent advancements and applications of deep learning in heart failure: Α systematic review. Computers in Biology and Medicine 2024;176:108557 View
  19. Li Z, Liu X, Tang Z, Jin N, Zhang P, Eadon M, Song Q, Chen Y, Su J. TrajVis: a visual clinical decision support system to translate artificial intelligence trajectory models in the precision management of chronic kidney disease. Journal of the American Medical Informatics Association 2024;31(11):2474 View
  20. Salih A, Galazzo I, Gkontra P, Rauseo E, Lee A, Lekadir K, Radeva P, Petersen S, Menegaz G. A review of evaluation approaches for explainable AI with applications in cardiology. Artificial Intelligence Review 2024;57(9) View
  21. Gao W, Rong F, Shao L, Deng Z, Xiao D, Zhang R, Chen C, Gong Z, Niu Z, Li F, Wei W, Ma L. Enhancing ophthalmology medical record management with multi-modal knowledge graphs. Scientific Reports 2024;14(1) View
  22. Horton A. Causal Economic Machine Learning (CEML): “Human AI”. AI 2024;5(4):1893 View
  23. ŞAHiN E, Arslan N, Özdemir D. Unlocking the black box: an in-depth review on interpretability, explainability, and reliability in deep learning. Neural Computing and Applications 2024 View
  24. Shen Y, Yu J, Zhou J, Hu G. 25 years of evolution and hurdles in electronic health records and interoperability in medical research: a comprehensive review (Preprint). Journal of Medical Internet Research 2024 View