Practical AI in Healthcare

In their sixth Reflections episode, Steve and Leon look back across five conversations (Sarah Rossetti, Jeff Smith of ONC, Hugo Campos, Fred Bennett, and Zak Kohane) and decide, deliberately, not to force a single grand theme. What surfaces anyway is one question asked five ways: as AI gets genuinely capable, what still has to be human, and what makes it trustworthy? They cover Rossetti's CONC...

A quiet war is underway over who controls your health data in the age of AI, and the front-runners aren't the usual suspects. Dr. Isaac "Zak" Kohane, Chair of Biomedical Informatics at Harvard Medical School and founding editor of NEJM AI, traces the line from SMART on FHIR (the accidental standard he helped create in 2009) to today's battle for the doctor-facing AI layer, where...

For its first-ever live episode, recorded before an audience at New York Tech Week, Practical AI in Healthcare sits down with Fred Bennett, founder and CEO of PatientTalker — an ambient-AI app built for the patient rather than the clinician. (Steve Labkoff is a disclosed advisor to the company.) Bennett traces the idea to his father's cardiology visit, where three family members left with thre...

Patient advocate Hugo Campos spent more than a decade fighting for access to the data from his own implanted defibrillator. When the system wouldn't budge, he stopped trying to reform it and started building around it. In this episode, Hugo shows how he used agentic AI coding tools to create OpenKP, an open-source app that liberates his records from inside Kaiser Permanente, despite calling hi...

What happens when the rules for getting AI into clinical care are written by someone who has spent his career inside both the advocacy world and the government? In this episode, we talk with Jeff Smith of ONC at HHS, the first government official on Practical AI in Healthcare. Smith walks us through ONC's proposed HTI-5 rule, including a striking move to treat AI agents as "users" wi...

On National Nurses Day, Practical AI in Healthcare welcomes its first nurse: Sarah Rossetti, RN, PhD, of Columbia University. Her CONCERN early warning system takes an unusual approach to predicting patient deterioration. Instead of modeling a patient's vital signs and labs, it models the nurse's documentation behavior, since the frequency and timing of charting reflect clinical concern lo...

In their fifth Reflections episode, Steve and Leon look back across six conversations (Matt Truppo at Sanofi, Ted Shortliffe, Barry Chaiken, David Hidalgo-Gato, and Danny van Leeuwen) to ask a sharper question: how specialized does AI have to be to actually work? The throughline is depth. The LLM is a commodity, and so, increasingly, is the generalist agent. What stays scarce is specialization in...

Danny van Leeuwen is a nurse of 50 years, a multiple sclerosis patient, host of the Health Hats podcast, and a serial member of national outcomes panels at CMS, AHRQ, PCORI, and the National Academy of Medicine. He has tried more than 100 health apps and uses five. In this episode, he explains how he uses AI to interrogate his own chart, surface symptom patterns, and prepare for clinical encounter...

David Hidalgo-Gato is the founder and CEO of Cleo Health. While more than 100 competitors were building generic ambient AI scribes, David's team chose emergency medicine and stayed with one design partner for nine months and roughly 50 product iterations before launching. The result: an average 54-minute time savings per shift, a patient-assignment tool that turned a four-hour process into 15...

When physician Barry Chaiken was diagnosed with prostate cancer, his clinical training gave way to fear. It took a friend asking, "What are you doing?" to snap him back into doctor-mode thinking. That experience reshaped how he sees AI in healthcare. In this episode, Chaiken draws on his dual perspective as physician and two-time cancer survivor to argue that consumer health AI is failin...

In Part 2 of our conversation with Matt Truppo, Global Head of Research Platforms and Computational R&D at Sanofi, we move from discovery to development, where the real stakes begin. Matt unpacks the promise and limitations of “digital patient twins,” a concept often described as the holy grail of drug development. With nearly 90% of drugs failing in clinical trials, even modest gains in predi...

Ted Shortliffe built MYCIN at Stanford in the 1970s, one of the first medical AI systems ever deployed in a clinical setting. Five decades later, he joins Steve and Leon to examine what has persisted in clinical decision support — above all, the demand for explainability — what has changed (computational power finally caught up to the ideas), and what the field may have lost along the way. The con...

AI in drug discovery has been long on promise and short on delivery. Matt Truppo, Global Head of Research Platforms and Computational R&D at Sanofi, presents a different picture. His team used AI to identify 10+ novel drug targets in 12 months, screen 30 million target combinations in days, and produce AI-designed compounds with 75% synthesizability. But Truppo is equally candid about the gaps...

Every five episodes, Steve and Leon step back to examine what picture forms when you put their guest conversations side by side. This time, five guests from completely different healthcare domains -- data quality, clinical trials, medical translation, patient data, participatory medicine -- independently converged on the same conclusion: the AI works; the infrastructure around it doesn't yet....

Amy Price survived a car accident that left her with a broken neck, severe brain injury, and $4 million in medical bills. She was told she'd need to be institutionalized. Instead, she earned a DPhil at Oxford and became Editor-in-Chief of the Journal of Participatory Medicine. In this episode, Amy sits down with Leon to discuss why patients belong inside the AI design process, what it really m...

Shashi Shankar spent nearly a decade at Genentech before a family cancer journey and a broken data landscape pushed him to build something different. His company Novellia works directly with patients — not data brokers — to collect and consolidate health records across multiple providers using SMART on FHIR. The result: longitudinal, patient-authorized real-world data that fills the gaps left by c...

When Adam Blum was diagnosed with follicular lymphoma, he tried over a dozen commercial trial matchers. None returned actual matches. So the serial AI entrepreneur built CancerBot, a free precision-matching service that assesses 100% of eligibility criteria — not the five surface-level attributes most matchers use. On this episode, Blum explains the Prompt Workbench (where biomedical experts refin...

For 37 years, Charlie Harp heard the same thing from healthcare organizations: "Our data quality is fine." They were right — for billing and scheduling. But AI changed the equation. Harp, founder of Clinical Architecture, built the PIQI framework to measure patient data quality across four dimensions: availability, accuracy, conformance, and plausibility. His PIQXL Gateway scores data on...

Every day, patients leave US hospitals with discharge instructions they can't read. Giovanni Donatelli, CEO of The Language Group, built FETCH — a patented AI system embedded in Epic that translates discharge documents in 15 minutes with human review. He did it because he was the 8-year-old interpreting for his immigrant parents at doctor's appointments. Hosts Steve Labkoff and Leon Rozenb...

Steve and Leon have reviewed blocks of guest episodes twice before on Practical AI in Healthcare. Both times the themes snapped into place. This time they didn't -- and the disagreement between them became the episode. Across five recent conversations, they found stories that kept spilling past the edges of their framework: AI that works but can't get paid, laws that already apply but nobo...

Bob Wachter wrote the book on the EHR disaster. Now he's written one about AI. The UCSF Chair of Medicine joins hosts Steve Labkoff and Leon Rozenblit to discuss A Giant Leap , his argument that AI doesn't need to be perfect—it needs to beat a healthcare system already failing at scale. They cover Watson's $3B collapse, why ambient scribes became AI's first clinical success story,...

What if early signs of psychosis could be detected from how patients speak—not what they say, but how they organize their thoughts? Amar Mandavia (VA Boston, Boston University) and Enrique "Kike" Gutiérrez (Polytechnic University of Madrid) join hosts Steve Labkoff and Leon Rozenblit to discuss CHiRP, an AI tool that identifies formal thought disorder from routine clinical conversations. They expl...

Real-world evidence was supposed to accelerate drug development. Instead, we've created definitional chaos—over 100 data vendors, inconsistent definitions, and studies that can't be compared. Dr. Aaron Kamauu, CEO of Navidence and co-host of Real World Wednesday, explains why one missing diagnosis code can exclude 30% of your cohort, how GLP-1 eligibility criteria vary wildly between NHS and US gu...

In this episode of Practical AI in Healthcare, we sit down with Dr. Jeff Chuang, a computational biologist at The Jackson Laboratory, to explore how AI is reshaping cancer diagnostics, starting with pediatric sarcoma. Jeff shares his journey from physics and protein folding to computational pathology, where machine learning is being applied to standard H&E pathology slides to deliver faster, c...

In this episode of Practical AI in Healthcare, we sit down with physician–informaticist Josh Geleris, MD, co-founder and Chief Product Officer of SmarterDx, to unpack one of healthcare’s most overlooked AI opportunities: revenue cycle intelligence. Drawing on his clinical training, deep technical background, and firsthand experience inside large health systems, Josh explains how AI can bridge the...