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Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies.

Nagendran M, Chen Y, Lovejoy CA, et al. Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies. BMJ. 2020;368:m689. Published 2020 Mar 25. doi:10.1136/bmj.m689

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May 13, 2020
Nagendran M, Chen Y, Lovejoy CA, et al. BMJ. 2020;368:m689.

This systematic review assessed randomized and non-randomized trials comparing the performance of artificial intelligence (AI; specifically deep learning algorithms) in medical imaging versus expert clinicians in order to characterize the state of the evidence and suggest future research directions which encourage innovation while protecting patients. The review identified 10 registered trials and 81 published non-randomized trials. Although 61 of 81 published studies reported that AI performance was comparable or better than that of clinicians, the authors identified few prospective studies or studies conducted in real-world settings; additionally, overall risk of bias was high and adherence to reporting standards was poor. Future studies examining the impact of AI in medicine must decrease risk of bias, increase relevance to real world clinical settings, and improve reporting and transparency.

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Nagendran M, Chen Y, Lovejoy CA, et al. Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies. BMJ. 2020;368:m689. Published 2020 Mar 25. doi:10.1136/bmj.m689

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