AI, Medicine, and Lessons Learned at Breck and Stanford: A Conversation with Dr. Curt Langlotz ’77

Dr. Curt Langlotz is a pioneer in medical AI. As the Director of the Center for Artificial Intelligence in Medicine and Imaging (AIMI) at Stanford and a professor of radiology and AI, he bridges the gap between cutting-edge engineering and life-saving clinical care. We sat down with him to discuss his journey from the Breck computer lab to the halls of Stanford Medicine.

Alumni Office (AO): Can you introduce yourself, including your graduation year from Breck and your current role?

Curt Langlotz (CL): I am Curt Langlotz, a proud member of the class of 1977. Today, I have several roles at Stanford. I run my own research lab with about a dozen students and postdoctoral scholars; we develop AI methods to help radiologists detect disease earlier and prevent medical errors. I also lead the Center for Artificial Intelligence in Medicine and Imaging (AIMI) in the School of Medicine, which supports over 200 faculty members interested in building similar applications to help physicians make better decisions and improve patient outcomes. Most recently, I started working in the office of our Vice Provost and Dean of Research, supporting and coordinating AI and data science research across Stanford. Outside of Stanford, I work with several startups in the health AI space and really enjoy advising young entrepreneurs.

AO: After Breck, you went to Stanford for Human Biology, a Master’s in Computer Science, and an MD/PhD. What was the specific spark that led you to merge those worlds?

CL: I’ve always been fascinated by how the body and the mind work, but I also grew up as a kid who loved playing with computers. When I was a student at Breck, we used an acoustic coupler where you would literally jam the phone receiver into these rubber donuts to dial into the University of Minnesota and program via teletype. The connection speed was 112 bits per second. Not gigabits or megabits--just bits! We literally watched our programming results arrive, one character at a time.

When I arrived at Stanford, I initially thought I’d be a chemistry major because there wasn’t yet an undergraduate computer science major. Instead, when I realized how much I enjoyed computer science, my workaround was to major in Human Biology, designing a custom concentration in computer models of biological systems. That allowed me to take my first AI courses.

At the end of college, many of my friends were applying to medical school, but I knew I didn't want to be a traditional doctor. Because I was so deep into the tech side, I decided to enter a brand-new Stanford program: a Master’s in Artificial Intelligence. I actually have a Stanford diploma from 1983 with 'Artificial Intelligence' printed on it, so I’ve been at this for a long time. While I was in that program, I was steered toward the medical school to meet a mentor who had just finished an M.D./Ph.D in AI. Seeing his path showed me that I could be both an academic AI researcher and a physician. At the end of my Master’s, I was admitted to both Stanford’s medical school and to a new AI-related Ph.D program to bridge those two worlds.

When it came time to choose a medical specialty, I settled on Radiology because I found I had a natural knack for seeing abnormalities and patterns in medical images. I also loved the field's definitive nature. In medicine, there are often so many mysteries surrounding a patient's health, but in radiology, we tend to have the answers. You get a scan, you look inside the body, and you can usually figure out exactly what’s going on. It’s the ultimate synergy of visual problem-solving and advanced technology, which has kept me hooked ever since. I practiced radiology for 35 years.

AO: Were there specific Breck faculty members who made a lasting impact on your life?

CL: Absolutely. Miss Fruen, my chemistry teacher, was wonderful. She let us learn through play. I remember chemical reactions that created volcanoes with sparks flying. She also let me serve as a teaching assistant for an astronomy course, where I gave my first lecture on telescopes.

And I was especially bonded to Mr. Yonker, my math teacher. He was a master teacher who encouraged students to study a topic and give a lecture on it. I guess my lecture on the central limit theorem went well because he mentioned it in the college recommendation letters he wrote for me.

Lastly, I had a great psychology teacher named Mr. Vollmer. I loved his class. Those are just a few of the great teachers I had at Breck.

AO: Beyond the classroom, what core lessons or values did you take away from your time at Breck?

CL: I’m incredibly grateful for the experience because, as one of three kids being raised by a single mom, I was there on a scholarship. Breck taught me the value of academic excellence and personal integrity. I also learned a lot about leadership on the golf team. I wasn’t the best golfer on the team, but I was selected as captain anyway. That experience taught me that leadership isn't defined by being the most skilled person in the room. Instead, it’s found in how you bring people together and in the example you set for others.

AO: Looking back at your tenures at both the University of Pennsylvania and Stanford, what are the achievements that stand out most to you?

CL: At Penn, I’m particularly proud of establishing a new division for Health Services Research. It was the early days of MRI technology, and we conducted critical research to determine which MRI tests were actually useful in specific clinical situations.

I’m also very proud of upholding the values of integrity I learned during my time at Breck. I found myself in a position where I had to be a whistleblower in a case of research misconduct. It was difficult, but it was the right thing to do to protect patients and the integrity of our field. When I first came to Stanford, I focused on modernizing our radiology practices by moving to fully digital speech recognition and imaging. I am especially proud of the research work that we do in the lab. I also built the AIMI Center from scratch.

AO: You briefly introduced the AIMI Center, which you run. Can you explain your center's core mission and what your researchers are currently focused on?

CL: Simply put, we support labs at Stanford that are building AI systems to help doctors take better care of patients. A great example is a project we did with a team of cardiologists and computer scientists. We built an AI algorithm that automatically detects calcium in the coronary arteries during routine CT scans.

Calcium is a major sign of heart disease, but it’s often overlooked in scans meant for other purposes. Our clinical trials showed that when patients were notified of this AI-detected calcium, they were significantly more likely to start life-saving cholesterol-lowering drugs. We’ve since licensed that to a startup and received FDA clearance. It’s now a product being used across the country to find patients with hidden heart disease.

AO: Stanford has become a leader in releasing medical datasets for non-commercial use. How has that shifted the global healthcare landscape?

CL: AI today is all about machine learning from data. The system learns by seeing thousands of examples, such as what a normal mammogram looks like versus one with cancer. By making data more widely available, we drive progress across the entire field.

Stanford has now released more AI-ready medical datasets than any other institution. Our chest X-ray dataset alone has been cited over 10,000 times. However, we realize that data from one California institution isn't enough. An algorithm needs to work for someone in Minnesota or Florida just as well as it does here. We are now encouraging other institutions to share de-identified data securely to ensure these AI tools work for everyone, everywhere.

AO: How do you see AI working in medicine over the next ten years?

CL: I see four main categories of progress:

Scientific Discovery: Speeding up the discovery of new drugs and treatments and improving ways to stage disease.
Decision Support: Tools that augment human decision-making to help doctors make better diagnoses and support for caregivers.
Operations: Ambient scribes that listen to doctor-patient conversations so the physician can focus on the patient rather than typing and staring at a computer screen.
Patient Use: AI algorithms used directly by patients to help manage their own health and decide when to see a doctor.

AO: What would you like the general public to understand about AI research in medicine?

CL: Two things. First, the importance of academic institutions in driving innovation. Companies like Google or OpenAI don't always have access to the massive healthcare datasets. And on campus, we have ethicists, legal scholars, and engineers who collaborate on the responsible development and implementation of these new tools. Second, is the importance of data. If you are a patient and have the opportunity to share your de-identified data for research that will benefit future patients, please do so. Data is the prime driver of all this progress.

AO: For students or young alums interested in AI and medicine, where should they start?

CL: A Pulitzer Prize-winning book called Gödel, Escher, Bach got me interested in AI as an undergraduate. It still holds up as a good read today. For technical skills, there are online courses on AI and healthcare on Coursera; you only pay if you want a certificate. There's also an online Stanford AI Course taught by my computer science colleague, Andrew Ng. The "Three Blue One Brown" website is great for learning linear algebra. And of course, our AIMI Center at Stanford has a High School AI Boot Camp. It’s virtual and very competitive (40 slots/2,000 applicants), but it’s a great way for students to build, through coding, a real medical AI system that does something useful. For something a little lighter, I recommend “The Worlds I See” by my Stanford computer science colleague, Fei Fei Li. It is a compelling play-by-play of the early days of the current AI wave and an incredible story of personal triumph.

AO: Thank you for taking the time to interview with us, Curt! It was a pleasure speaking with you.

CL: Thank you. I am very glad to have had the opportunity to share.

Dr. Langlotz ’77 will be this year’s Cum Laude Society Induction Ceremony speaker on Sunday, April 12. Cum Laude is an academic society founded in 1906 that recognizes academic excellence, integrity, and scholarship in secondary education. We are excited that he is joining us as we celebrate the achievement with our junior and senior members.