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

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 2023 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 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