# Causal multi-modal AI for personalized chemosensitivity prediction

**Published:** September 15, 2026
**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/en/articles/causal-multi-modal-ai-for-personalized-chemosensitivity-prediction

Chemotherapy improves survival for some patients with breast cancer, but doctors cannot reliably predict who. Current guidelines rely on recurrence scores as a proxy for treatment benefit, which may contribute to the overprescription of chemotherapy. Here we present a causal…

> From the original source: **arXiv — cs.AI**
> [Read full article at arXiv — cs.AI](https://arxiv.org/abs/2609.13567)

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