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Cancer research
AI is accelerating discovery, imaging, and clinical trial research across cancers.
Oncology Clinical Trial EnrollmentAI quickly and accurately organized cancer data to help match patients to clinical trials worldwide.This could help researchers overcome data and language barriers, making trial matching faster and more accurate across many health systems if validated further.Cancer researchRead →
Localized Prostate CancerAI and gene tests together better predict prostate cancer spread risk.This could help researchers validate combined tests that better measure cancer risk and guide future study designs for treatment in prostate cancer.Cancer researchRead →
Gastric CancerAI predicted two important cancer markers simultaneously from routine tissue images and patient data.This could help researchers develop faster, cheaper ways to find key markers for immunotherapy using regular hospital images. If validated further, it may point toward screening tools that reduce costly genetic testing.Cancer researchRead →
Bladder CancerAI helped find CKAP2 as a strong new marker to spot bladder cancer in tissue samples.This could help researchers better detect bladder cancer by focusing on CKAP2, which may improve early identification and study of the disease if validated further.Cancer researchRead →
Cancer-Related Fatigue In Ovarian CancerAI predicted cancer-related fatigue risk reliably in ovarian cancer patients early in their care.This could help researchers identify patients at high risk for fatigue sooner, enabling better research on targeted support. If validated further, it may improve study designs for fatigue management.Cancer researchRead →
