TL;DR
Artificial intelligence-driven tools performed well for title/abstract screening and general data extraction but were less accurate for full-text screening and interpretation of modeling choices.
Systematic literature reviews are widely acknowledged to be at the top of most evidence hierarchies but are very time-consuming and labour-intensive. The advent of artificial intelligence (AI) offers possibilities to accelerate the review process. We propose a systematic literature review protocol that incorporates A...
The models reproduced human screening tendencies despite the small dataset size, demonstrating the technical feasibility of LLM-assisted article selection and providing the first demonstration of LLM-assisted identification of EQ-5D data in biomedical literature.
Abstract Objective To examine whether the outputs of machine learning algorithms designed to predict risk of cardiovascular disease (CVD) address known deficiencies of the Framingham Risk Score (FRS) and improve risk estimates. Methods For this critical review, Medline, Embase and IEEE were searched from inception to 1...
Machine learning models have been proposed for identifying prediabetes, but their methodological quality, generalisability, and readiness for primary care implementation remain uncertain. We conducted a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020-compliant systematic revi...
Abstract Background A growing body of literature leverages large language models (LLMs) to make mental health predictions. However, these models are prone to bias, and studies to validate their clinical utility are lacking. Objective This scoping review aims to uncover bias and clinical utility limitations stemming fro...
The growing availability of electronic health records (EHRs) has accelerated the use of artificial intelligence (AI) and machine learning (ML) in public health. Yet, how well these methods work in low- and middle-income countries (LMICs), remains poorly understood. This review synthesises studies on ML-based prediction...
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