Artificial Intelligence healthcare tools

Innovating medical technologies that address real-world clinical needs and translate discovery into better patient care

Innovating medical technologies that address real-world clinical needs and translate discovery into better patient care
AI Medical Solutions was built on the belief that emerging technologies should serve patients first. Our work is grounded in clinical realities—from telehealth challenges to medical language barriers—ensuring that innovation translates directly into better care. We aim to make healthcare more affordable, accessible, and effective.
We collaborate with physicians, biotech entrepreneurs, researchers, and academic mentors to ensure every tool meets clinical standards. From NSF grant applications to IRB protocols, our work is guided by medical advisors who help us align innovation with real-world care. These partnerships are the foundation that allows us to refine, validate, and responsibly scale our solutions.
Our flagship app, HealthVision, transforms a smartphone into a reliable range-of-motion assessment device, empowering clinicians to conduct accurate exams even in telehealth settings. We are also piloting an LLM-powered multilingual intake assistant to bridge language gaps and capture richer patient histories. Each tool is built to reduce clinician burden while improving diagnostic clarity.

AI Medical Solutions was founded by Ryan Morgenstern with a mission to develop innovative technologies that make healthcare more precise, accessible, and effective.
Ryan graduated magna cum laude from New York University, where he was inducted into Phi Beta Kappa. His research background spans psychophysiological biosensor validation, computational medicine, and digital health innovation.
Ryan is also the author of Medicine and the Artificial Intelligence Age: A Decision Science Framework for Evaluating Digital Health Technologies. Written for clinicians navigating the rapidly evolving landscape of medical technology, the book presents a framework for evaluating when and how emerging innovations can meaningfully improve clinical practice.
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