Zhou Qian, Chen Zhi-Hang, Cao Yi-Heng, Peng Sui
Department of Medical Statistics, Clinical Trials Unit, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhong Shan Er Road, 510080, Guangzhou, China.
Department of Liver Surgery, The First Affiliated Hospital, Sun Yat-sen University, 510080, Guangzhou, China.
NPJ Digit Med. 2021 Oct 28;4(1):154. doi: 10.1038/s41746-021-00524-2.
The evidence of the impact of traditional statistical (TS) and artificial intelligence (AI) tool interventions in clinical practice was limited. This study aimed to investigate the clinical impact and quality of randomized controlled trials (RCTs) involving interventions evaluating TS, machine learning (ML), and deep learning (DL) prediction tools. A systematic review on PubMed was conducted to identify RCTs involving TS/ML/DL tool interventions in the past decade. A total of 65 RCTs from 26,082 records were included. A majority of them had model development studies and generally good performance was achieved. The function of TS and ML tools in the RCTs mainly included assistive treatment decisions, assistive diagnosis, and risk stratification, but DL trials were only conducted for assistive diagnosis. Nearly two-fifths of the trial interventions showed no clinical benefit compared to standard care. Though DL and ML interventions achieved higher rates of positive results than TS in the RCTs, in trials with low risk of bias (17/65) the advantage of DL to TS was reduced while the advantage of ML to TS disappeared. The current applications of DL were not yet fully spread performed in medicine. It is predictable that DL will integrate more complex clinical problems than ML and TS tools in the future. Therefore, rigorous studies are required before the clinical application of these tools.
传统统计学（TS）和人工智能（AI）工具干预在临床实践中的影响证据有限。本研究旨在调查涉及评估TS、机器学习（ML）和深度学习（DL）预测工具的干预措施的随机对照试验（RCT）的临床影响和质量。在PubMed上进行了一项系统综述，以识别过去十年中涉及TS/ML/DL工具干预的RCT。从26,082条记录中总共纳入了65项RCT。其中大多数进行了模型开发研究，并且总体上取得了良好的性能。TS和ML工具在RCT中的功能主要包括辅助治疗决策、辅助诊断和风险分层，但DL试验仅用于辅助诊断。与标准治疗相比，近五分之二的试验干预措施未显示出临床益处。尽管在RCT中DL和ML干预措施比TS取得了更高的阳性结果率，但在偏倚风险较低的试验中（17/65），DL相对于TS的优势有所降低，而ML相对于TS的优势则消失了。DL目前在医学中的应用尚未完全普及。可以预见，未来DL将比ML和TS工具整合更复杂的临床问题。因此，在这些工具临床应用之前需要进行严格的研究。
