Bayesian Health

Here are the top voices who are shaping AI in healthcare right now: At Offcall, we're committed to lifting up the physicians and healthcare leaders who are moving AI in medicine forward, safely and responsibly. That's why we're so excited to spotlight the incredible group of leaders who are defining the guardrails, exposing bias, integrating into real hospitals, and always putting physicians front and center. Follow them, learn from them, and stay tuned! We'll be sharing Part 2 soon 👀 If there's someone you want to nominate to the list, be sure to tag them in the comments. 😃  Part 1 of 2 👇 🔷 Dr. Eric Topol, MD 🔷 Dr. Shiv (Shivdev) Rao 🔷 Dr. Robert Wachter 🔷 Dr. Matthew Sakumoto 🔷 Dr. Spencer Dorn 🔷 Dr. Michael Hobbs MD 🔷 Dr. Dr. Geeta Nayyar, MD, MBA 🔷 Dr. Sarah Gebauer, MD 🔷 Dr. Ethan Goh, MD 🔷 Dr. Jonathan H. Chen 🔷 Dr. Jackie Gerhart 🔷 Dr. David Rhew, M.D. 🔷 Dr. Robert Pearl, M.D. 🔷 Dr. Ziad Obermeyer 🔷 Dr. Suchi Saria 🔷 Dr. John Halamka, M.D., M.S. 🔷 Dr. Daniel Yang, MD 🔷 Brendan Keeler 🔷 Dr. Alice Chiao 🔷 Dr. Mark Sendak, MD, MPP 🔷 Dr. Rachel Draelos, MD, PhD 🔷 Dr. Nigam Shah 🔷 Dr. Bertalan Meskó, MD, PhD 🔷 Dr. Harvey Castro, MD, MBA. Read the full list here: https://lnkd.in/gYtVcZCY #AIinMedicine #HealthcareAI #PhysicianLeadership #Offcall #HealthTech #MedicalInnovation

Many people see FDA clearance as the ceiling. For us, it's the floor. It's validation that our solution works across diverse settings, with robust monitoring and quality assurance built in. But clearance is the starting point, not the goal. From there, we focus on removing barriers to use, driving adoption, and improving outcomes. Outcomes like what MemorialCare is seeing today, the kind of results that gave them the confidence to expand system-wide: 📉 3.6% absolute mortality reduction (more than 20% relative reduction) 🏥 90% adoption in the ED Read more: https://lnkd.in/eWvfEqC2

"A lot of us in palliative care worry about losing the humanity in medicine the more we automate. What's been powerful about this work is that it feels like one way to bring a lot of that humanity back to the bedside — where it belongs." A powerful reframe from Dr. Jake Strand in Becker's Healthcare on how the work between Mayo Clinic and Bayesian Health is leveraging AI to help scale compassionate conversations. The fear that AI pulls clinicians away from patients is real and worth taking seriously. But when the technology is built around patient-centered signals and designed to surface the right patient at the right moment, it gives specialty teams something they rarely have: context and support to show up for their patients when they need them most. Read the full article: https://lnkd.in/grbx4y3V

Today, palliative care conversations happen too late. Or not at all. The evidence is clear that earlier conversations ease suffering, support families, and reduce avoidable hospitalizations. But getting this right at scale is hard. We're proud to share that Bayesian Health, in collaboration with Mayo Clinic, has expanded our real-time clinical intelligence platform into palliative care. Now live at Mayo, the solution identifies patients with unmet needs earlier in their journey and reaches both bedside and palliative teams with the context to act, inside the workflow they already use. It is about giving clinicians a clearer picture earlier, when there is still time to shape care around what patients actually want. More time for symptom relief. More time for caregiver support. More time for the conversations families deserve. Grateful to Dr. Jake Strand and the entire Mayo Clinic team for their partnership, and their deep care for both patients and clinicians. Palliative care is the latest of how our platform extends earlier identification into the moments that matter most. Stay tuned for more! Read the full announcement here: https://lnkd.in/gNmYFCRN

We're proud to announce that Bayesian Health has received FDA clearance for the first continuous AI monitor for sepsis. In a condition where late detection costs lives, Bayesian is now the only cleared solution that identifies sepsis before clinical suspicion forms. And that lead time is everything. This is what we see as the new standard of care: proactive, real-time, enterprise-wide clinical intelligence that becomes part of how hospitals deliver quality at scale. Years of work made this possible. A massive thanks to our team and the health system partners who've built it with us. More to come! Read more: https://lnkd.in/gd9Hz2y3

It was a real honor to kick off the plenary at #AACR26 talking about what it actually takes to bring clinical AI into real-world adoption. Oncology patients are complex. Their vitals don't follow textbook patterns, and these variations can cause generic models to fail. If AI isn't trained for the population it's serving, clinicians tune it out, and rightly so. At Bayesian Health, our real-time clinical intelligence platform is trusted across the hospital, including the ICU, where the stakes are highest and the tolerance for noise is lowest. That trust comes from three things done well: population-specific model design, thoughtful change management, and tight workflow integration.

Our CEO Suchi Saria on stage at CNBC Changemakers Summit last week, sharing her experience riding the AI adoption wave in healthcare.

You won't want to miss next week's live discussion! We'll cover real-world validation, implementation strategies, and what drives frontline adoption - hearing directly from the clinical executives making it happen. Register here: https://lnkd.in/gtCVY-26 James Leo Conrad D Gleber James Morrison William Shatraw, MHA, DPT

What does it actually take to move sepsis care from reactive to proactive? Join our webinar to hear three clinical leaders share their real-world playbook, from deploying clinical intelligence to driving adoption to sustaining results over time. Featuring: Dr. James Leo, Dr. Conrad D Gleber, and Dr. James Morrison. Register Here: https://lnkd.in/gtCVY-26

“If you AI to have real clinical intelligence, it has to understand cause and effect - not just extract information.” - Suchi Saria This is a critical distinction that is often overlooked when thinking about where AI is going after “scribe mania”. Many AI tools today are essentially trained to read the chart and summarize it — like “an English major reading a book on medicine.” But clinical care requires something deeper: understanding how labs, medications, physiology, and time interact. A few key takeaways from our panel at ViVE: 👩🏽⚕️ To reason like a clinician, AI must synthesize messy, fragmented EMR data into a longitudinal patient story — not just process text. 🔎 High stakes clinical events such sepsis, cardiac arrest, stroke are needle-in-a-haystack problems — often 1–2% prevalence. This means signal-to-noise is everything. ✨ Adoption is the real test. It isn’t about building a model that looks good on paper. It’s building tools that physicians trust enough to use, and that measurably improves patient outcomes when deployed. Thank you ViVE for inviting us to be part of the conversation!