Fig. 4: Analysis of explainability and reproducibility in the reviewed studies.

a Number of publications employing various techniques for model explainability. b Number of publications employing explainability across different data collection techniques. c Use of explainability methods from 2017 to 2023. d AUC values of models employing explainability across different data collection techniques. e Percentage of studies with available data and code, or both. f-g Heatmap of the median of various performance metrics based on: data availability (f), or code availability (g). h Number of publications with available data, or code for each cancer type. i Percentage of papers using a single-cohort or a multi-cohort dataset. j Change in the number of publications using single- versus multi-cohort datasets over the years.