Integration of CT Radiomics and Ultrasound Radiomics With Liquid Biopsy to Predict the Response to Neoadjuvant Chemotherapy in Patients With Locally Advanced Gastric Cancer: A Prospective Study

<![CDATA[20 On the Upswing: A Retrospective Cohort Study Evaluating Neoadjuvant Chemotherapy Response in Metaplastic Breast Cancer Patients]]>

Navigating Biomarker Conversations: Empowering Patient Understanding in Gastroesophageal Cancer

How confident are you navigating biomarker conversations with your gastric cancer patients?

<![CDATA[AI Test Predicts Breast Cancer Recurrence Using Standard Pathology Slides]]>

UC San Diego AI Model Predicts Cancer Treatment Response from Tumor Genetics

A new AI model developed by UC San Diego researchers could make it possible to predict treatment response based only on a tumor's genetics.

Revolutionizing Whole-Body MRI: The HA-DSB Approach

A novel framework could drastically reduce the lengthy PET-MR scan times with enhanced accuracy, thanks to innovative AI modeling.

Path2Space deep-learning model predicts spatial gene expression from routine pathology slides for breast cancer biomarker discovery

Path2Space predicts spatial gene expression directly from histopathology, enabling low-cost, large-scale characterization of the tumor micro