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

Viewpoints and Perspectives (514) Artificial Intelligence (1371) Patient-Reported Outcome Measures (PROMs) (288) Machine Learning (1465)

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 (22) 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
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  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
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  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 2023 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. The Development of a Machine Learning Model to Predict the Duration of Atrial Fibrillation as a Support System to Improve the Diagnostic Accuracy of Cardiologists (Preprint). JMIR Medical Informatics 2024 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 CDSS: An Interview Study (Preprint). Journal of Medical Internet Research 2024 View

Books/Policy Documents

  1. Hadap A, Khatri V. Scientific Publishing Ecosystem. View