{"ID":2827070,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.17517","arxiv_id":"2512.17517","title":"PathBench-MIL: A Comprehensive AutoML and Benchmarking Framework for Multiple Instance Learning in Histopathology","abstract":"We introduce PathBench-MIL, an open-source AutoML and benchmarking framework for multiple instance learning (MIL) in histopathology. The system automates end-to-end MIL pipeline construction, including preprocessing, feature extraction, and MIL-aggregation, and provides reproducible benchmarking of dozens of MIL models and feature extractors. PathBench-MIL integrates visualization tooling, a unified configuration system, and modular extensibility, enabling rapid experimentation and standardization across datasets and tasks. PathBench-MIL is publicly available at https://github.com/Sbrussee/PathBench-MIL","short_abstract":"We introduce PathBench-MIL, an open-source AutoML and benchmarking framework for multiple instance learning (MIL) in histopathology. The system automates end-to-end MIL pipeline construction, including preprocessing, feature extraction, and MIL-aggregation, and provides reproducible benchmarking of dozens of MIL models...","url_abs":"https://arxiv.org/abs/2512.17517","url_pdf":"https://arxiv.org/pdf/2512.17517v1","authors":"[\"Siemen Brussee\",\"Pieter A. Valkema\",\"Jurre A. J. Weijer\",\"Thom Doeleman\",\"Anne M. R. Schrader\",\"Jesper Kers\"]","published":"2025-12-19T12:35:57Z","proceeding":"cs.CV","tasks":"[\"cs.CV\",\"cs.LG\",\"cs.NE\",\"cs.SE\",\"q-bio.TO\"]","methods":"[]","has_code":false,"code_links":[{"ID":605782,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2827070,"paper_url":"https://arxiv.org/abs/2512.17517","paper_title":"PathBench-MIL: A Comprehensive AutoML and Benchmarking Framework for Multiple Instance Learning in Histopathology","repo_url":"https://github.com/Sbrussee/PathBench-MIL","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}