Accuracy of machine learning and traditional statistical models in the prediction of postpartum haemorrhage: a systematic review.

ABSTRACT:

Objectives

To evaluate whether postpartum haemorrhage (PPH) can be predicted using both machine learning (ML) and traditional statistical models.

Design

Diagnostic systematic review and meta-analysis of observational and clinical studies, prospectively registered on PROSPERO, performed accordingly to the Preferred Reporting Items for Systematic Reviews and Meta-analysis and Prediction model risk of bias assessment tool for studies developing, validating or updating prediction models, with the use of an independent analysis by a large language model (GPT-4 Open AI).

Data sources

MEDLINE/PubMed, LILACS-BVS, Cochrane Library, Scopus-Elsevier, Embase-Elsevier and Web of Science.

Eligibility criteria for selected studies

The literature search was conducted on 4 Janu

SUBMITTER: Baeta T 

PROVIDER: S-EPMC11877273 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature