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

Viewpoints and Perspectives (619) Artificial Intelligence (2129) Patient-Reported Outcome Measures (PROMs) (372) Machine Learning (2076)

Published on in Vol 22, No 8 (2020): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19918, first published .
Is Artificial Intelligence Better Than Human Clinicians in Predicting Patient Outcomes?

Is Artificial Intelligence Better Than Human Clinicians in Predicting Patient Outcomes?

Is Artificial Intelligence Better Than Human Clinicians in Predicting Patient Outcomes?

Authors of this article:

Joon Lee1, 2, 3 Author Orcid Image
Article Authors Cited by (32) Tweetations (23) Metrics

Journals

  1. Lee S, Li B, Martin E, D’Souza A, Jiang J, Doktorchik C, Southern D, Lee J, Wiebe N, Quan H, Eastwood C. CREATE: A New Data Resource to Support Cardiac Precision Health. CJC Open 2021;3(5):639 View
  2. Cabitza F, Campagner A. The need to separate the wheat from the chaff in medical informatics. International Journal of Medical Informatics 2021;153:104510 View
  3. Byun H, Yu S, Oh J, Bae J, Yoon M, Lee S, Chung J, Kim T. An Assistive Role of a Machine Learning Network in Diagnosis of Middle Ear Diseases. Journal of Clinical Medicine 2021;10(15):3198 View
  4. Matthiesen S, Diederichsen S, Hansen M, Villumsen C, Lassen M, Jacobsen P, Risum N, Winkel B, Philbert B, Svendsen J, Andersen T. Clinician Preimplementation Perspectives of a Decision-Support Tool for the Prediction of Cardiac Arrhythmia Based on Machine Learning: Near-Live Feasibility and Qualitative Study. JMIR Human Factors 2021;8(4):e26964 View
  5. Berber A, Srećković S. When something goes wrong: Who is responsible for errors in ML decision-making?. AI & SOCIETY 2024;39(4):1891 View
  6. Hah H, Goldin D. How Clinicians Perceive Artificial Intelligence–Assisted Technologies in Diagnostic Decision Making: Mixed Methods Approach. Journal of Medical Internet Research 2021;23(12):e33540 View
  7. Kao J, Farrugia M, Frontario S, Zucker A, Copel E, Loscalzo J, Sangal A, Darakchiev B, Singh A, Missios S. Association of radiation dose intensity with overall survival in patients with distant metastases. Cancer Medicine 2021;10(22):7934 View
  8. Antoniadi A, Galvin M, Heverin M, Wei L, Hardiman O, Mooney C. A Clinical Decision Support System for the Prediction of Quality of Life in ALS. Journal of Personalized Medicine 2022;12(3):435 View
  9. Shingshetty L, Maheshwari A, McLernon D, Bhattacharya S. Should we adopt a prognosis-based approach to unexplained infertility?. Human Reproduction Open 2022;2022(4) View
  10. Xiong W, Fan H, Ma L, Wang C. Challenges of human—machine collaboration in risky decision-making. Frontiers of Engineering Management 2022;9(1):89 View
  11. Emani S, Rui A, Rocha H, Rizvi R, Juaçaba S, Jackson G, Bates D. Physicians’ Perceptions of and Satisfaction With Artificial Intelligence in Cancer Treatment: A Clinical Decision Support System Experience and Implications for Low-Middle–Income Countries. JMIR Cancer 2022;8(2):e31461 View
  12. Jang W, Choi Y, Kim J, Yon D, Lee Y, Chung S, Kim C, Yeo S, Lee J. Artificial Intelligence–Driven Respiratory Distress Syndrome Prediction for Very Low Birth Weight Infants: Korean Multicenter Prospective Cohort Study. Journal of Medical Internet Research 2023;25:e47612 View
  13. Wegner M, Fontaine V, Nana P, Dieffenbach B, Fabre D, Haulon S. Artificial Intelligence–Assisted Sac Diameter Assessment for Complex Endovascular Aortic Repair. Journal of Endovascular Therapy 2025;32(4):1172 View
  14. Yang J, Yan J, Xiong C, Zhang X, Shen L, Zhi J, Ma S, Dong H, Yang Y. Development and validation of a scoring system to predict esophagogastroduodenoscopy necessity. Journal of Digestive Diseases 2023;24(12):671 View
  15. Funk P, Hoch C, Knoedler S, Knoedler L, Cotofana S, Sofo G, Bashiri Dezfouli A, Wollenberg B, Guntinas-Lichius O, Alfertshofer M. ChatGPT’s Response Consistency: A Study on Repeated Queries of Medical Examination Questions. European Journal of Investigation in Health, Psychology and Education 2024;14(3):657 View
  16. Suresh K, Görg C, Ghosh D. Model‐agnostic explanations for survival prediction models. Statistics in Medicine 2024;43(11):2161 View
  17. Aden D, Zaheer S, Khan S. Possible benefits, challenges, pitfalls, and future perspective of using ChatGPT in pathology. Revista Española de Patología 2024;57(3):198 View
  18. Nakayama L, Matos J, Quion J, Novaes F, Mitchell W, Mwavu R, Hung C, Santiago A, Phanphruk W, Cardoso J, Celi L, Wong A. Unmasking biases and navigating pitfalls in the ophthalmic artificial intelligence lifecycle: A narrative review. PLOS Digital Health 2024;3(10):e0000618 View
  19. Shimoo S, Senoo K, Okawa T, Kawai K, Makino M, Munakata J, Tomura N, Iwakoshi H, Nishimura T, Shiraishi H, Inoue K, Matoba S. Using Machine Learning to Predict the Duration of Atrial Fibrillation: Model Development and Validation. JMIR Medical Informatics 2024;12:e63795 View
  20. Giebel G, Raszke P, Nowak H, Palmowski L, Adamzik M, Heinz P, Tokic M, Timmesfeld N, Brunkhorst F, Wasem J, Blase N. Problems and Barriers Related to the Use of AI-Based Clinical Decision Support Systems: Interview Study. Journal of Medical Internet Research 2025;27:e63377 View
  21. Cuevas-Nunez M, Silberberg V, Arregui M, Jham B, Ballester-Victoria R, Koptseva I, de Tejada M, Posada-Caez R, Manich V, Bara-Casaus J, Fernández-Figueras M. Diagnostic performance of ChatGPT-4.0 in histopathological description analysis of oral and maxillofacial lesions: a comparative study with pathologists. Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology 2025;139(4):453 View
  22. Twinprai P, Phruetthiphat O, Wongwises K, Apinyankul R, Suthisopapan P, Liawrungrueang W, Twinprai N. AI classification of knee prostheses from plain radiographs and real-world applications. European Journal of Orthopaedic Surgery & Traumatology 2025;35(1) View
  23. Patil M, Lin L, Ford R, James E, Morton S, Marsh-Wakefield F, Hawke S, Grau G. Harnessing Artificial Intelligence for the Diagnosis, Treatment and Research of Multiple Sclerosis. Sclerosis 2025;3(2):15 View
  24. Marinescu Ș, Oncioiu I, Ghibanu A. The Digital Transformation of Healthcare Through Intelligent Technologies: A Path Dependence-Augmented–Unified Theory of Acceptance and Use of Technology Model for Clinical Decision Support Systems. Healthcare 2025;13(11):1222 View
  25. Pasquadibisceglie V, Appice A, Malerba D, Fiameni G. Leveraging a large language model (LLM) to predict hospital admissions of emergency department patients. Expert Systems with Applications 2025;287:128224 View
  26. Mazzucchelli M, Salzano S, Caltabiano R, Magro G, Certo F, Barbagallo G, Broggi G. Diagnostic Performance of ChatGPT‐4.0 in Histopathological Analysis of Gliomas: A Single Institution Experience. Neuropathology 2025;45(4) View
  27. Kendir M, Zuhurlu M. Evaluation Large Language Models’ Time Dependent Consistency in Aesthetic Surgery Consultations and Comparison of Their Performance Across Different Clinical Domains. Aesthetic Plastic Surgery 2025 View

Books/Policy Documents

  1. Hadap A, Khatri V. Scientific Publishing Ecosystem. View
  2. Koon S. The Design of Human-Centered Artificial Intelligence for the Workplace. View

Conference Proceedings

  1. Abad Z, Lee J. 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). Detecting Uncertainty of Mortality Prediction Using Confident Learning View
  2. Janjua J, Ghazal T, Abushiba W, Abbas S. 2024 IEEE 65th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON). Optimizing Patient Outcomes with AI and Predictive Analytics in Healthcare View
  3. Tarafder M, Ahmed N, Hossain Z, Rahman M, Rahman T, Ahamed A. 2024 IEEE Conference on Engineering Informatics (ICEI). Integrating Transformative AI for Next-Level Predictive Analytics in Healthcare View