AutoMIL: Automated Multiple Instance Learning for Whole-Slide Image Classification

AutoMIL is an open‑source framework that automates key steps of multiple instance learning pipelines for whole‑slide image classification, including preprocessing, training, and evaluation. In benchmark tests, it achieved ROC‑AUC scores of 0.94 on UBC‑OCEAN, 0.99 on PCam, and 0.93‑0.96 on a TCGA‑NSCLC subset, matching the performance of specialized pipelines. The framework’s ensembling approach particularly improved results on imbalanced datasets, demonstrating the need for automated pipelines to adapt to dataset characteristics.

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• computer-vision
• benchmarks