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

Clinical Information and Decision Making (1688) Decision Support for Health Professionals (1361) Artificial Intelligence (1779) Machine Learning (1770) User-centred Design Case Studies (654)

Published on in Vol 24, No 1 (2022): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28659, first published .
A Clinical Decision Support System for Sleep Staging Tasks With Explanations From Artificial Intelligence: User-Centered Design and Evaluation Study

A Clinical Decision Support System for Sleep Staging Tasks With Explanations From Artificial Intelligence: User-Centered Design and Evaluation Study

A Clinical Decision Support System for Sleep Staging Tasks With Explanations From Artificial Intelligence: User-Centered Design and Evaluation Study

Authors of this article:

Jeonghwan Hwang1 Author Orcid Image ;   Taeheon Lee1 Author Orcid Image ;   Honggu Lee1 Author Orcid Image ;   Seonjeong Byun2 Author Orcid Image
Article Authors Cited by (18) Tweetations (2) Metrics

Journals

  1. Du Y, Antoniadi A, McNestry C, McAuliffe F, Mooney C. The Role of XAI in Advice-Taking from a Clinical Decision Support System: A Comparative User Study of Feature Contribution-Based and Example-Based Explanations. Applied Sciences 2022;12(20):10323 View
  2. Calisto F, Santiago C, Nunes N, Nascimento J. BreastScreening-AI: Evaluating medical intelligent agents for human-AI interactions. Artificial Intelligence in Medicine 2022;127:102285 View
  3. Xu Q, Xie W, Liao B, Hu C, Qin L, Yang Z, Xiong H, Lyu Y, Zhou Y, Luo A, Li C. Interpretability of Clinical Decision Support Systems Based on Artificial Intelligence from Technological and Medical Perspective: A Systematic Review. Journal of Healthcare Engineering 2023;2023(1) View
  4. Pinnock H, Murphie P, Vogiatzis I, Poberezhets V. Telemedicine and virtual respiratory care in the era of COVID-19. ERJ Open Research 2022;8(3):00111-2022 View
  5. González-Alday R, García-Cuesta E, Kulikowski C, Maojo V. A Scoping Review on the Progress, Applicability, and Future of Explainable Artificial Intelligence in Medicine. Applied Sciences 2023;13(19):10778 View
  6. He X, Zheng X, Ding H, Liu Y, Zhu H. AI-CDSS Design Guidelines and Practice Verification. International Journal of Human–Computer Interaction 2024;40(18):5469 View
  7. Subramanian H, Canfield C, Shank D. Designing explainable AI to improve human-AI team performance: A medical stakeholder-driven scoping review. Artificial Intelligence in Medicine 2024;149:102780 View
  8. Evans R, Bryant L, Russell G, Absolom K. Trust and acceptability of data-driven clinical recommendations in everyday practice: A scoping review. International Journal of Medical Informatics 2024;183:105342 View
  9. Zhang L, Zhao S, Yang Z, Zheng H, Lei M. An Artificial Intelligence Platform to Stratify the Risk of Experiencing Sleep Disturbance in University Students After Analyzing Psychological Health, Lifestyle, and Sports: A Multicenter Externally Validated Study. Psychology Research and Behavior Management 2024;Volume 17:1057 View
  10. Gomez C, Smith B, Zayas A, Unberath M, Canares T. Explainable AI decision support improves accuracy during telehealth strep throat screening. Communications Medicine 2024;4(1) View
  11. Kang M, Rossetti S, Lowenthal G, Knaplund C, Zhou L, Schnock K, Cato K, Dykes P. Designing and testing clinical simulations of an early warning system for implementation in acute care settings. JAMIA Open 2024;7(4) View
  12. Chen K, Luo L, Tan Y, Chen G. Medical diagnosis based on artificial intelligence and decision support system in the management of health development. Journal of Evaluation in Clinical Practice 2025;31(3) View
  13. Scarpato N, Ferroni P, Guadagni F. XAI Unveiled: Revealing the Potential of Explainable AI in Medicine - A Systematic Review. IEEE Access 2024:1 View
  14. Teixeira da Silva J, Yamada Y. Could generative artificial intelligence serve as a psychological counselor? Prospects and limitations. Central Asian Journal of Medical Hypotheses and Ethics 2024;5(4):297 View
  15. Gomez C, Cho S, Ke S, Huang C, Unberath M. Human-AI collaboration is not very collaborative yet: a taxonomy of interaction patterns in AI-assisted decision making from a systematic review. Frontiers in Computer Science 2025;6 View
  16. Tsai C, Kim J, Chen Q, Rowell B, Yang X, Kontar R, Whitaker M, Lester C. Effect of Artificial Intelligence Helpfulness and Uncertainty on Cognitive Interactions with Pharmacists: Randomized Controlled Trial. Journal of Medical Internet Research 2025;27:e59946 View
  17. Dhanani S, Ramchandani R, Allan J, Hudek N, Herry C, Scales N, Adhikari N, Brehaut J, Burns K, Chassé M, Iyengar A, Meade M, Ramsay T, Scales D, Selzner M, Sener A, Slessarev M, Talbot H, Weiss M, Zaltzman J, Seely A. Feasibility and Optimization of Donation Advisor: a Decision Support Tool for Deceased Organ Donation and Transplantation. Transplantation Direct 2025;11(3):e1748 View
  18. Butler J, Doubleday A, Sattar U, Nies M, Jeppesen A, Wright M, Reese T, Kawamoto K, Fiol G, Madaras-Kelly K. “Be Really Careful about That”: Clinicians' Perceptions of an Intelligence Augmentation Tool for In-Hospital Deterioration Detection. Applied Clinical Informatics 2025;16(02):377 View