Optimizing the study design of clinical trials to identify the efficacy of artificial intelligence tools in clinical practices

Affiliations

¹ Department of Medical Statistics, Clinical Trials Unit, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhong Shan Er Road, Guangzhou,510080, China.
² ESIEE Paris, Cité Descartes BP99, Noisy-le-Grand 93162, France.
³ Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhong Shan Er Road, Guangzhou, 510080, China.

Qian Zhou et al. EClinicalMedicine. 2019.

. 2019 Oct 25:16:10-11.

doi: 10.1016/j.eclinm.2019.09.016. eCollection 2019 Nov.

¹ Department of Medical Statistics, Clinical Trials Unit, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhong Shan Er Road, Guangzhou,510080, China.
² ESIEE Paris, Cité Descartes BP99, Noisy-le-Grand 93162, France.
³ Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhong Shan Er Road, Guangzhou, 510080, China.

No abstract available

Conflict of interest statement

None (all authors).

Quality of reporting of randomised controlled trials of artificial intelligence in healthcare: a systematic review.
Shahzad R, Ayub B, Siddiqui MAR. Shahzad R, et al. BMJ Open. 2022 Sep 5;12(9):e061519. doi: 10.1136/bmjopen-2022-061519. BMJ Open. 2022. PMID: 36691151 Free PMC article.

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