PathBench-MIL: A Comprehensive AutoML and Benchmarking Framework for Multiple Instance Learning in Histopathology
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866918256210608128 |
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| author | Brussee, Siemen Valkema, Pieter A. Weijer, Jurre A. J. Doeleman, Thom Schrader, Anne M. R. Kers, Jesper |
| author_facet | Brussee, Siemen Valkema, Pieter A. Weijer, Jurre A. J. Doeleman, Thom Schrader, Anne M. R. Kers, Jesper |
| contents | 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 |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_17517 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | PathBench-MIL: A Comprehensive AutoML and Benchmarking Framework for Multiple Instance Learning in Histopathology Brussee, Siemen Valkema, Pieter A. Weijer, Jurre A. J. Doeleman, Thom Schrader, Anne M. R. Kers, Jesper Computer Vision and Pattern Recognition Machine Learning Neural and Evolutionary Computing Software Engineering Tissues and Organs I.4.10; I.5.1; I.5.2; I.2.5; I.2.8; I.6.5; I.6.4; J.3 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 |
| title | PathBench-MIL: A Comprehensive AutoML and Benchmarking Framework for Multiple Instance Learning in Histopathology |
| topic | Computer Vision and Pattern Recognition Machine Learning Neural and Evolutionary Computing Software Engineering Tissues and Organs I.4.10; I.5.1; I.5.2; I.2.5; I.2.8; I.6.5; I.6.4; J.3 |
| url | https://arxiv.org/abs/2512.17517 |