AI & DIGITAL ONCOLOGY
Multimodal AI biomarkers: from biology to patient stratification
Artificial intelligence is enabling a new class of biomarkers by integrating histology, molecular data, imaging, and clinical records to generate scalable, biologically grounded insights for precision oncology.
AI-driven multimodal strategy improves risk stratification in early breast cancer
Integrating digital pathology with genomic and clinical data may enhance prediction of late recurrence and refine selection for adjuvant treatment intensification in HR-positive, HER2-negative disease
Customised app shows promise for monitoring prostate cancer patients in real-time
A pilot study reports high levels of acceptance and compliance despite an older patient population
LATEST NEWS
First-line dual targeting combination shows encouraging, durable responses in triple-negative breast cancer
A manageable safety profile was also reported for pumitamig plus the antibody-drug conjugate DB-1305/BNT325 in an early-phase study
Sustained quality-of-life benefits reported with first-line antibody-drug conjugate in triple negative breast cancer
Patient-reported outcomes show that datopotamab deruxtecan also improved patient functioning and symptom control compared to chemotherapy
Piccart: “Academic research is losing ground very rapidly”
At a senior stage of her career in oncology, Prof. Martine Piccart remains deeply committed in supporting young oncologists in cancer research
Heather H. Cheng
Dominik Modest
Ivana Bozovic-Spasojevic
Rinath Jeselsohn
Alejandro González Sánchez