PathBench-MIL: A Comprehensive AutoML and Benchmarking Framework for Multiple Instance Learning in Histopathology
Published:Dec 19, 2025 12:35
•1 min read
•ArXiv
Analysis
This article introduces PathBench-MIL, a framework for AutoML and benchmarking in multiple instance learning (MIL) within histopathology. The focus is on providing a comprehensive tool for researchers in this specific domain. The use of AutoML suggests an attempt to automate and optimize model selection and hyperparameter tuning, which could lead to more efficient and effective research. The benchmarking aspect allows for standardized comparison of different MIL approaches.
Key Takeaways
- •PathBench-MIL is a framework for AutoML and benchmarking in multiple instance learning.
- •The framework is specifically designed for histopathology.
- •It aims to improve efficiency and effectiveness in research through automated model selection and hyperparameter tuning.
- •Benchmarking allows for standardized comparison of MIL approaches.
Reference
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