From Interview #107
With Dr. Kyle Bonesteel and Jennifer Bires
Mental health care is entering a new era of precision medicine. In this episode, neuropsychologist Dr. Kyle Bonesteel and psychosocial oncology leader Jennifer Bires explore how artificial intelligence is transforming the way clinicians detect, diagnose, and treat mental health conditions.
Traditionally, mental health assessment has relied heavily on subjective patient narratives and screening tools that capture only a moment in time. Today, emerging technologies such as digital phenotyping, voice analysis, wearable devices, and functional brain mapping are enabling clinicians to uncover patterns that were previously invisible. These tools can help identify emotional distress earlier, personalize therapy strategies, and extend mental health support beyond the clinic visit.
Dr. Bonesteel explains how AI can act as a “signal amplifier” for clinicians, improving diagnostic clarity by analyzing neurological patterns and behavioral signals. Bires discusses how AI-driven insights can expand access to care, particularly in oncology settings where emotional distress often accompanies cancer treatment. Together, they highlight a future where precision mental health care matches the right intervention to the right patient at the right time.
From Interview #106
With Dr. Amar Rewari and Dr. Lindsey Cotton
As artificial intelligence becomes embedded across clinical workflows, healthcare leaders face a defining challenge: how to govern AI safely, responsibly, and at scale. In this full interview, Dr. Amar Rewari and Dr. Lindsey Cotton unpack what clinicians must understand about AI governance as healthcare enters 2026.
The conversation explores how FDA oversight, CLIA regulation, and real-world evidence intersect with modern AI tools, from decision support systems to emerging autonomous workflows. Drawing on experience in oncology, diagnostics, and health policy, the guests explain why FDA approval alone is insufficient, why institutional accountability matters, and how AI model drift creates silent clinical risk. They also examine implementation science, clinician trust, workforce burnout, and why governance frameworks must evolve alongside reimbursement incentives.
For clinicians and health system leaders, this discussion offers a pragmatic roadmap for evaluating AI tools, balancing innovation with safety, and preparing organizations for the next phase of AI adoption in patient care.
From Interview #105
With Jim St. Clair and James Fargason
Digital twins are emerging as one of the most powerful tools to reduce uncertainty in medicine, particularly in oncology, where clinicians are often forced to make high-stakes decisions with incomplete data. In this full interview, Jim St. Clair and James Fargason explore how digital twin technology could fundamentally reshape healthcare by creating dynamic, data-driven virtual representations of patients that evolve in real time.
Drawing on advances from engineering, infrastructure, and aerospace, the conversation examines how patient-centric digital twins could integrate genomics, pharmacogenomics, environmental exposure, clinical history, and real-world data to improve treatment selection, reduce toxicity, and accelerate clinical trials. The discussion highlights why digital twins go beyond static AI predictions, emphasizing continuous feedback, simulation, and probability modeling.
The guests also address critical challenges, including data fragmentation, ownership, trust, and clinician adoption. As healthcare moves toward precision medicine and value-based care, digital twins may become indispensable tools for clinicians, researchers, and patients seeking more personalized, evidence-driven decisions.
From Interview #104
With Samara Barend
Medical-grade wearables are rapidly moving beyond wellness tracking and becoming essential tools in cancer care. In this episode, Samara Barend, CEO of AION Biosystems, joins leading oncology clinicians to explain how continuous, longitudinal patient data is reshaping early detection, treatment tolerance, and emergency prevention. Barend shares the development story behind TempShield, the first FDA-cleared long-term wearable designed to identify infection risk before it becomes life-threatening. The discussion explores how continuous temperature monitoring reduces preventable hospitalizations, why certain signals offer higher clinical value than others, and how providers can integrate these devices without overwhelming clinical workflows. The conversation also addresses interoperability, reimbursement, alert fatigue, and the shift toward simulation-driven precision medicine.
