Uncertainty-aware and causal test-time adaptive foundation model for robust colorectal cancer pathology diagnosis - Summary - MDSpire

Uncertainty-aware and causal test-time adaptive foundation model for robust colorectal cancer pathology diagnosis

  • By

  • Shenghan Lou

  • Genshen Mo

  • Xiao Zhang

  • Hao Wang

  • Hao Li

  • Keru Ma

  • Huiying Li

  • Xinyue Zhang

  • Meihong Yan

  • Haonan Xie

  • Yuze Huang

  • Chuangqi Li

  • Siyuan Ma

  • Hongxue Meng

  • Lei Cao

  • Peng Han

  • December 6, 2025

  • 0 min

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Objective:

To develop a reliable computational pathology model for colorectal cancer diagnosis that addresses uncertainty estimation, domain shifts, and spurious correlations, enhancing clinical reliability.

Key Findings:
  • UAD-FM outperforms existing models in accuracy (specific metrics needed) and domain robustness.
  • The model provides interpretable uncertainty maps to facilitate human-AI collaboration.
  • Successful integration of epistemic and aleatoric uncertainty quantification tailored for CRC histopathology.
Interpretation:

UAD-FM offers a unified framework that enhances the reliability and generalizability of colorectal cancer pathology diagnosis, addressing critical challenges such as uncertainty estimation and domain shifts.

Limitations:
  • The model's performance may vary with different clinical settings not represented in the training datasets (specify types).
  • Further validation is needed in real-world clinical environments.
Conclusion:

UAD-FM represents a significant advancement in computational pathology for colorectal cancer, promoting safer clinical deployment through improved uncertainty awareness and adaptability.

Original Source(s)

Uncertainty-aware and causal test-time adaptive foundation model for robust colorectal cancer pathology diagnosis

  • by Shenghan Lou, Genshen Mo, Xiao Zhang, Hao Wang, Hao Li, Keru Ma, Huiying Li, Xinyue Zhang, Meihong Yan, Haonan Xie, Yuze Huang, Chuangqi Li, Siyuan Ma, Hongxue Meng, Lei Cao, Peng Han

  • December 6, 2025

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