# 用于个性化化疗敏感性预测的因果多模态人工智能

> 全文为英语

**Published:** 2026年9月15日
**Author:** Dhruva Biswas, Jeroen Berrevoets, Alec McClean, Linus Bao, Jungkyu Park, Ken G. Zeng, Joseph Cappadona, Cerise Tang, Chuwen Liu, Bartosz Machura, Yin Wu, Valerie Speirs, Hatem Soliman, Rohit Bhargava, Sheheryar Kabraji, Thaer Khoury, David Page, Brian Piening, Carlo Bifulco, Claudia Meurs, Pieter Westenend, Sylvie Chabaud, Jerome Lemonnier, Paul H. Cottu, Florence Dalenc, Fabrice Andre, Frederique Madeleine Penault-Llorca, Thomas Bachelot, Frederick Howard, Francisco J. Esteva, Kevin Kalinsky, Lajos Pusztai, Jan Witowski, Krzysztof J. Geras
**Source:** arXiv — cs.AI
**Language:** en-US
**HTML:** https://aiqazaqstan.com/zh/articles/causal-multi-modal-ai-for-personalized-chemosensitivity-prediction

化疗可以提高一些乳腺癌患者的生存率，但医生无法可靠地预测哪些患者是乳腺癌患者。目前的指南依赖复发评分作为治疗获益的替代指标，这可能会导致化疗的过度处方。在这里，我们提出一个因果关系……

> 内容来自原始来源： **arXiv — cs.AI**
> [在 arXiv — cs.AI 阅读全文](https://arxiv.org/abs/2609.13567)

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