Breast cancer is often diagnosed by invasive tissue biopsies, and treatment decisions are subsequently guided by molecular subtyping. Despite its accuracy this process is constrained by delays, procedural risks, and limited accessibility in facilities with limited resources. We suggest a unique less invasive diagnostic pathway that combines multi-omics data, with AI-assisted POCUS imaging, for the molecular subtyping of breast mass. This method provides a scalable and easily accessible substitute for tissue biopsy while screening for breast cancer. Our findings demonstrate the potential of AI-integrated imaging and omics for earlier detection of breast cancer. This can significantly contribute to improving screening methods of breast cancer and subsequently decreases the rate of late-stage breast cancer detection.

Majd Oteibi, MD, DHSc, MAS, CCRP, FRSPH, she is the Founder and CEO of Validus Institute Inc. She has over 20 years of experience in clinical research, with a strong record of leading cross-disciplinary teams, securing multi-therapeutic partnerships, and delivering translational studies at the intersection of obstetrics, gynecology, women’s health, and biomedical engineering. Her current work focuses on developing innovative AI-assisted technologies for the early detection of breast cancer. She integrates advanced breast phantom models with AI-assisted point-of-care ultrasound (POCUS) to enhance diagnostic accuracy and clinician training. She has published multiple peer-reviewed articles. She also serves as a reviewer at multiple reputable scientific journals. Her research aims to reduce breast cancer metastasis and improve diagnostic access in low-resource settings and remote areas. Beyond research, she is an associate professor at National University.