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Theme Issue 2024: 25 Years of Digital Health Excellence (56) Digital Health Reviews (1852) Clinical Informatics (1470) Big Data (319) Advanced Data Analytics in eHealth (241) Evaluation and Research Methodology for mHealth (259) Machine Learning (2273) Artificial Intelligence (2416) Generative Language Models Including ChatGPT (859)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/59792, first published .
Generative AI Models in Time-Varying Biomedical Data: Scoping Review

Generative AI Models in Time-Varying Biomedical Data: Scoping Review

Generative AI Models in Time-Varying Biomedical Data: Scoping Review

Authors of this article:

Rosemary He1, 2 Author Orcid Image ;   Varuni Sarwal1, 2 Author Orcid Image ;   Xinru Qiu3 Author Orcid Image ;   Yongwen Zhuang4 Author Orcid Image ;   Le Zhang5 Author Orcid Image ;   Yue Liu6 Author Orcid Image ;   Jeffrey Chiang2, 7 Author Orcid Image
Article Authors Cited by (15) Tweetations Metrics

Journals

  1. Tungal A, Singh K, Singh P, Rehman A, Sood S, Kant V, Kumar A, Hussen S, Hamam H. Recurrent neural network-based automated early detection of pandemic-prone diseases through symptoms analysis. Discover Social Science and Health 2025;5(1) View
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  3. Han F, Huang X, Wang X, Chen Y, Lu C, Li S, Lu L, Zhang D. Artificial Intelligence in Orthopedic Surgery: Current Applications, Challenges, and Future Directions. MedComm 2025;6(7) View
  4. Beltramin D, Bousquet C. Foundation Models for Generative AI in Time-Series Forecasting. Journal of Medical Internet Research 2025;27:e76964 View
  5. He R, Chiang J. Authors’ Reply: Foundation Models for Generative AI in Time-Series Forecasting. Journal of Medical Internet Research 2025;27:e79772 View
  6. da Silva R, Pazin-Filho A. The incremental value of unstructured data via natural language processing in machine learning-based COVID-19 mortality prediction: a comparative study. BMC Medical Informatics and Decision Making 2025;25(1) View
  7. Alshammari A, Mahdi M, Hirotsu T, Morishita M, Hatakeyama H, di Luccio E. Beyond Binary: A Machine Learning Framework for Interpreting Organismal Behavior in Cancer Diagnostics. Biomedicines 2025;13(10):2409 View
  8. Lecca M, Bianco S. Common issues and human intervention in object detection from handcrafted features to deep learning: discussion. Journal of the Optical Society of America A 2025;42(12):1977 View
  9. Mahmood H, Alamgir Z, Javed S, Karim S, Awais M. Federated Generative Models in Medical Imaging: Current Advances, Challenges, and Future Directions. IEEE Access 2026;14:5197 View
  10. Bottussi A, Wieruszewski P, Bignami E, Swol J, Buda K, Cheungpasitporn W, Elmadhoun O, D’Andria Ursoleo J. Can algorithms come to the rescue of a failing heart? Machine learning, artificial intelligence, and decision-making in cardiogenic shock. Journal of Anesthesia, Analgesia and Critical Care 2026;6(1) View
  11. Al-Smadi F, Al-Smadi S, Xie X, Abudourusuli X, Ouyang L, Zeng R, Du L, Liao Y, Mi B, Liu G. Artificial intelligence and robotic technologies redefining precision and personalization in orthopedic surgery: a narrative review. Frontiers in Bioengineering and Biotechnology 2026;14 View
  12. Myśliwiec A, Bartusik-Aebisher D, Xavierselvan M, Paul A, Aebisher D. Deep Learning and Cardiovascular Diseases: An Updated Narrative Review. Journal of Clinical Medicine 2026;15(8):3053 View
  13. LI R, GE J, ZHANG X, ZHANG Y, CHEN D, TAO C. Advances and trends in the bidirectional transformation between biological data and knowledge. Chinese Bulletin of Life Sciences 2026;38(2):236 View
  14. Tiwari E, Shrimankar D, Maindarkar M, Saba L, Suri J. Women’s Cardiovascular Disease and Stroke Risk Stratification Using a Precision and Personalized Framework Embedded with an Explainable Artificial Intelligence Paradigm: A Narrative Review. Diagnostics 2026;16(8):1158 View

Books/Policy Documents

  1. Zhang G, Zhang S, Wu H. Handbook of Human-Centered Artificial Intelligence. View