The Convergence

Host: Brian P. McDonough, MD, FAAFP Guest: Kate Rouch As AI tools become more accessible, patients are increasingly using them to research symptoms, understand diagnoses, and prepare for appointments, creating new opportunities—and challenges—for care delivery. In this episode of The Convergence, Dr. Brian McDonough speaks with Kate Rouch, a breast cancer survivor and Chief Marketing Officer at OpenAI, about how patients are using AI and how clinicians can navigate this evolving dynamic.

Host: Brian P. McDonough, MD, FAAFP Guest: Clement Papadacci, PhD 4D ultrasound and ultrasound localization microscopy (ULM) are reshaping non-invasive imaging, allowing clinicians to visualize entire organs—down to vessels smaller than a human hair—in dynamic, real-time detail. Dr. Clément Papadacci joins Dr. Brian McDonough to share how his groundbreaking probe reveals organ-scale blood flow without radiation or traditional contrast agents. Dr. Papadacci is a researcher at Inserm and the Physics for Medicine Institute in Paris.

Host: Brian P. McDonough, MD, FAAFP Guest: Jean-Claude Saghbini Primary care is facing a massive supply-demand gap—and artificial intelligence (AI) may finally offer a scalable solution. In this episode of The Convergence, Dr. Brian McDonough speaks with Jean-Claude Saghbini, Chief Technology Officer at Lumeris, about “Tom,” an agentic AI tool designed to reduce physician burnout and expand care access.

Host: Brian P. McDonough, MD, FAAFP Guest: Matthew Newman From streamlining research to informing real-time decisions, AI-powered platforms are beginning to reshape how clinicians and researchers access and apply data in patient care. Learn more as Dr. Brian McDonough speaks with Matt Newman, Senior Vice President of Industry Solutions at Manifold, about how new technologies are bringing together disconnected data sources, making it easier to ask clinical questions and get meaningful answers faster.

Host: Brian P. McDonough, MD, FAAFP Guest: Theodoros Zanos, PhD An artificial intelligence (AI)-driven clinical alert model has the potential to reshape inpatient care by detecting early signs of deterioration an average of 17 hours before adverse events occur. Dr. Brian McDonough sits down with Dr. Theodoros Zanos, to learn more about how his team combined continuous data from clinical wearables with advanced machine learning to enable early risk detection in the medical-surgical setting. Dr. Zanos leads the Division of Health AI and is an Associate Professor of Medicine at the Feinstein Institutes for Medical Research and the Zucker School of Medicine at Hofstra University/Northwell Health.