Risk of bias of prognostic models developed using machine learning: a systematic review in oncology.

ABSTRACT:

Background

Prognostic models are used widely in the oncology domain to guide medical decision-making. Little is known about the risk of bias of prognostic models developed using machine learning and the barriers to their clinical uptake in the oncology domain.

Methods

We conducted a systematic review and searched MEDLINE and EMBASE databases for oncology-related studies developing a prognostic model using machine learning methods published between 01/01/2019 and 05/09/2019. The primary outcome was risk of bias, judged using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). We described risk of bias overall and for each domain, by development and validation analyses separately.

Results

We included 62 publications (48 development-only; 14 development with val

SUBMITTER: Dhiman P 

PROVIDER: S-EPMC9261114 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature