AI in Research

This project documents the methods, data, and materials for a structured narrative synthesis examining the application of artificial intelligence (AI) in clinical research in low- and middle-income countries (LMICs). The study aims to map the landscape of AI use across clinical research domains, with a particular focus on structural patterns in evidence production, validation, and research leadership. The review includes studies published between January 2019 and June 2026 and spans diagnostic applications, epidemiological modelling, clinical trials methodology, and research infrastructure. A structured search strategy was applied across multiple databases, followed by dual-reviewer screening at title–abstract and full-text stages. Given the heterogeneity of included study designs, a structured evidence weighting framework was developed to enable transparent comparison across studies rather than applying a single standard risk-of-bias tool. This OSF project serves as a transparency and reproducibility resource. It includes: * Search strategies and retrieval methods * Screening datasets with reviewer decisions * Full-text inclusion/exclusion coding * Quality appraisal framework and study-level scores * Domain classification and results summaries The project was registered after completion of data collection and analysis and is intended to provide full methodological transparency rather than prospective protocol registration. No deviations from the documented methods were made after finalisation of the screening and analysis processes.