Bibliometric analysis of 608 AI breast cancer imaging studies finds diagnosis at 71.22% and explainable AI with a 1.00 burst ratio as the hottest frontier
Using Scopus and Web of Science and a PRISMA workflow that narrowed 4,831 records to 608 peer-reviewed journal articles and reviews from 2020 to 2026, this study applied Bibliometrix and VOSviewer for a task-aware, methodology-centric bibliometric and thematic analysis, finding that diagnosis accounts for 71.22% of studies, mammography for 42.11%, explainable AI shows the strongest burst ratio at 1.00, while treatment-response prediction covers only 2.30% and only about 15-25% of studies explicitly report hyperparameter tuning strategies.