Author

Krzysztof J. Geras

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#artificial intelligence Review Oct 2026

Transcriptome-informed multi-modal AI for predicting neoadjuvant therapy response from breast cancer biopsies

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, corrobor...

Jungkyu Park, D. Biswas, J. Cappadona et al. · 0 citations

Open access Sep 2026

An AI Model Identifies Chemotherapy Benefit in Node-Negative HR+/HER2- Breast Cancer Patients from TAILORx, a Phase 3 Randomized Clinical Trial

BACKGROUND The prescribing of adjuvant chemotherapy for patients with breast cancer must balance the survival benefit against treatment-related toxicities. TAILORx, a phase 3 randomized clinical trial, demonstrated that endocrine therapy alone was, on average, noninferior to chemoendocrine therapy for patients classifi...

N. Chan, Cerise Tang, D. Biswas et al. · medRxiv · 1 citation

#artificial intelligence Preprint Sep 2026

Causal multi-modal AI for personalized chemosensitivity prediction

The model generated treatment-specific recurrence probabilities for each patient, with near-perfect calibration and strong prognostic discrimination across both 5- and 10-year follow-up horizons, and out-performed existing recurrence-score-based tests.

D. Biswas, Jeroen Berrevoets, A. McClean et al. · 2 citations