Transcriptome-informed multi-modal AI for predicting neoadjuvant therapy response from breast cancer biopsies
Paper recorded by Signals 4 on 2026-10-02 in cs.AI. Abstract reproduced from arXiv; link to the original below.
Published 2026-10-02 on arXiv · recorded by Signals 4 on 2026-10-05
Category: cs.AI · 人工智能 · first seen 2026-10-05
Abstract
Scarcity of labeled data limits development of deep learning biomarkers in oncology. We develop a two-stage AI model predicting pathological complete response (pCR) to neoadjuvant therapy in breast cancer. The first stage learns the transcriptome from histopathology using 8,742 patients across 32 cancer types, corroborated by pathologist review and spatial agreement with measured expression. This
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Cite this page: Transcriptome-informed multi-modal AI for predicting neoadjuvant therapy response from breast cancer biopsies: the #465 most recent of 980 cs.AI papers we have recorded (as of 2026-10-02). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/transcriptome-informed-multi-modal-ai-for-predicting-neoadjuvant-therapy-respons.html
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