Data used for "Machine learning methods for post-transplant infection risk prediction: a scoping review"

This pre-processed data file contains the structured information extracted from the 32 studies included in the scoping review "Machine learning methods for post-transplant infection risk prediction: a scoping review". Following initial data collection based on the CHARMS framework, the raw extracted variables, such as applied machine learning algorithms, data modalities, measurement timings, and clinical outcomes, were systematically standardized and put into categories. This categorization enabled the quantitative synthesis, comparison, and visualization of the methodological landscape across the reviewed literature.