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Sweden just proved AI can catch 29% more breast cancers.
And it’s cutting radiologist workload nearly in half.
The MASAI trial results are in, published in The Lancet this February. Over 100,000 women screened. The largest randomized controlled trial of AI in mammography ever conducted.
Here’s what they found:
📊 29% increase in cancer detection
🎯 12% reduction in interval cancers (the ones that show up between screenings)
⏱️ 44% reduction in radiologist reading time
✅ No increase in false positives (1.5% vs 1.4%)
But here’s what makes this revolutionary:
The AI caught mostly small, lymph node-negative invasive cancers. The kind that are treatable when found early. The kind that save lives.
Dr. Kristina Lång from Lund University made a crucial point: implementation is simple. It’s just software. No new equipment. No massive infrastructure changes.
Several Swedish regions have already adopted it.
Think about the implications for underserved communities. For rural areas with one overworked radiologist. For countries where double-reading isn’t even possible due to staffing.
We have 40,000 women dying from breast cancer annually in the US. Globally, it’s 685,000.
What if we could cut those numbers by catching cancers 29% more often, 12% sooner?
This isn’t about replacing radiologists. It’s about amplifying their expertise. One radiologist plus AI performed better than two radiologists reading separately.
The shortage of breast imaging specialists is real. The burnout is real. The missed cancers are real.
Sweden just showed us a path forward.
The question isn’t whether we’ll adopt AI screening. It’s how fast we can scale it.
♻️ Repost if early cancer detection should be available to every woman
👉 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:
CEO/Co-Founder @ Oatmeal Health | AI Lung Cancer Screening | Almost Became a Doctor | Engineer | Follow to Share What I’ve Learned Along the Way
I help patients get the care they need earlier, preventing late-stage cancer.
That’s been the throughline across three companies and almost 20 years in healthcare. At ReferralMD, we fixed broken referral networks so patients didn’t fall through the cracks. At Oatmeal Health, it’s lung cancer: building the diagnostic and screening infrastructure so the 85% of cases caught too late get caught early instead.
Today as CEO of Oatmeal Health, I lead a team embedding AI into radiology workflows to turn routine lung CT scans into reimbursable cancer risk assessments. We partner with FQHCs to reach underserved communities, and with health systems and payers to make early detection economically sustainable. Think HeartFlow or Cleerly, but for lungs.
Between companies, I advised at Techstars and Plug and Play, mentoring founders building in digital health. That experience shaped how I think about what separates companies that ship from companies that stall: distribution, reimbursement, and clinical trust, not just technology.
I’m a CancerX alumnus, a 3x healthcare founder, and someone who believes the biggest problems in cancer aren’t scientific. They’re operational.
We’re hiring mission-driven builders at Oatmeal Health. If you want to work on something that matters, reach out.
When I’m not working, I’m traveling, mentoring, and keeping up with one very energetic husky. 🐾
Substack – The Oatmeal Bite:
Millions of patients get less care because of who they are, where they live, or how they look. I’m fighting to change that. CEO @OatmealHealth, a startup built for the underserved. The Oatmeal Bite: intel for clinicians, investors, and advocates.
Jonathan Govette
CEO of Oatmeal Health
Substack:
https://oatmealhealthjonathangovette.substack.com/
