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

翻译：本文介绍PathBench-MIL，一个面向组织病理学中多示例学习（MIL）的开源AutoML与基准测试框架。该系统实现了端到端MIL流程的自动化构建，涵盖预处理、特征提取与MIL聚合等环节，并对数十种MIL模型与特征提取器提供可复现的基准测试。PathBench-MIL集成了可视化工具、统一配置系统与模块化扩展机制，能够支持跨数据集与跨任务的快速实验与标准化研究。PathBench-MIL已在https://github.com/Sbrussee/PathBench-MIL公开提供。