Each October, the conversation around breast cancer tends to focus on awareness. But the most powerful shift is happening behind the scenes – in the data, diagnostics, and AI tools transforming how the disease is detected and treated. A new generation of founders and scientists is proving that early detection is not just a medical milestone, but a business frontier.
Lunit is leading the charge with Lunit INSIGHT MMG, an AI system that analyzes mammograms with remarkable precision, helping radiologists detect malignant lesions earlier and more consistently. The company’s partnerships with national screening programs across the globe demonstrate how machine learning can scale life-saving insight.
iCAD is redefining early detection through its ProFound AI Breast Health Suite, which integrates cancer detection, breast density assessment, and short-term risk evaluation into one comprehensive platform. Its latest FDA-cleared updates significantly improve accuracy in dense breast tissue—one of the field’s most persistent challenges.
Therapixel, is another innovator using AI to improve radiologists’ accuracy and reduce diagnostic fatigue. By standardizing how mammograms are interpreted, it’s helping health systems around the world reduce variability and improve outcomes.
Women Founders Rewriting the Playbook
Geetha Manjunath, founder and CEO of NIRAMAI in India, developed Thermalytix, an AI-driven, non-invasive screening tool that uses thermography to detect abnormalities even in younger women, addressing a major gap in traditional mammography. Her work has drawn global attention for its ability to deliver low-cost, accessible screening across developing markets.
Kaitlin Christine, founder of Gabbi, is turning prevention into prediction. Her platform analyzes medical history, imaging records, and lifestyle data to forecast an individual’s risk of developing breast cancer, making early screening proactive rather than reactive.
Cristina Rossi, co-founder and CEO of b-rayZ, is advancing explainable AI in breast cancer diagnostics, building technology that empowers radiologists while ensuring that equity, transparency, and human judgment remain at the core of every decision.
Regina Barzilay, a pioneering AI scientist at MIT and breast cancer survivor, is leveraging her own experience to transform the field. Her Mirai model, trained on thousands of mammograms, can predict a woman’s future risk years in advance, changing not just how we detect disease, but how we define prevention.
The rise of AI-assisted diagnostics has far-reaching implications beyond healthcare. It forces every industry to wrestle with questions of data responsibility, transparency, and trust.
Executives across sectors can draw lessons from this movement:
