Dataset for systematic review on completeness of reporting of clinical prediction models developed using supervised machine learning techniques

This record includes the dataset collected for the systematic review titled “Completeness of reporting of clinical prediction models developed using supervised machine learning: a systematic review” published in 2022 (doi.org/10.1186/s12874-021-01469-6), and therefore, the dataset is made available after publication of results. The aim of the study was to to systematically review the adherence of Machine Learning (ML)-based prediction model studies to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Statement.

The articles included in this dataset were obtained through a search on PubMed from 1 January 2018 to 31 December 2019 and are a random sample of articles reporting on the development, with or without external validation, of a multivariable prediction model (diagnostic or prognostic) developed using supervised machine learning for individualised predictions. The dataset provides the reviewers judgements on the adherence of articles to the reporting items described in TRIPOD.