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81% cancer detection with AI mammography. Are we finally winning?
A groundbreaking Lancet trial just dropped results that should make every healthcare executive pay attention.
200,000 mammograms. 10+ countries. One stunning outcome:
AI-assisted screening detected 81% of cancers at screening, compared to 74% with standard double-reading. That’s not a marginal improvement, that’s transformational.
But here’s what really caught my eye:
📊 27% fewer aggressive cancers missed
📊 21% fewer large tumors developing
📊 12% reduction in interval cancers (those sneaky ones found between screenings)
📊 44% reduction in radiologist workload
Google’s NHS study added another bombshell: their AI caught 25% of interval cancers that human radiologists missed entirely.
Think about what this means for your imaging centers and screening programs.
We’re not just finding more cancers. We’re finding them smaller, earlier, when they’re actually treatable. We’re catching the aggressive ones that kill. And we’re doing it while our radiologists read 32% faster.
With radiologist shortages crushing departments nationwide, this isn’t just innovation, it’s survival.
The question isn’t whether to adopt AI mammography anymore.
The question is: can you afford not to?
Every day we delay implementation is another day of preventable late-stage diagnoses. Another day of burned-out radiologists drowning in reads. Another day we’re failing the 1 in 8 women who will face breast cancer.
Your competitors are already moving on this. Insurance is starting to cover it. Patients will demand it.
What’s your timeline?
♻️ Repost if early cancer detection should be a healthcare priority
👉 Follow me, Jonathan Govette, for daily, real-time updates on healthcare technology and business news. LinkedIn Profile: https://www.linkedin.com/in/jonathangovette/
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Author:
Jonathan Govette is a seasoned healthcare and technology executive with more than two decades of experience building, scaling, and advising digital health companies. He is the Co-Founder and CEO of Oatmeal Health, an AI-driven Lung Cancer Screening and Diagnostics company focused on expanding access to early detection for underrepresented populations, particularly patients served by Federally Qualified Health Centers and value-based health plans.
With a background in engineering, product development, and strategic partnerships, Jonathan has founded and led multiple health technology ventures across clinical care delivery, regulated medical software, and AI-enabled diagnostics. His work sits at the intersection of medicine, technology, and health equity, with a consistent focus on translating complex clinical problems into scalable, real-world solutions.
Jonathan has spent much of his professional life dedicated to improving outcomes for marginalized and underserved communities. He has designed and implemented frameworks that align clinical quality, reimbursement, and technology to sustainably advance health equity at scale. This mission is deeply personal and informs his leadership philosophy and long-term vision for healthcare transformation.
In addition to his operating experience, Jonathan is an author and long-time writer in the healthcare domain, with over 20 years of published work covering digital health, medical innovation, and healthcare systems. He is a frequent mentor to early-stage founders and regularly advises startups on product strategy, partnerships, and go-to-market execution in regulated healthcare environments.
Before entering industry full-time, Jonathan nearly pursued a career in medicine with an early path toward cardiothoracic surgery, an experience that continues to shape his clinical perspective and respect for frontline care delivery.
CEO | Oatmeal Health | AI Lung Cancer Startup | Engineer | Writer | Almost Became a Doctor (Cardiac Thoracic Surgeon) | 3x Health Tech Founder | Startup Mentor | Follow to share what I’ve learned along the way.
