Healthcare AI Weekly: AI Triage Meets Governance | Healthcare AI Weekly

I’m Raphael Malikian, a healthcare AI builder with 20+ years of domain experience, from family medicine practice to bootstrapping a direct primary care startup. This channel documents my healthcare-AI pivot: building in public, sharing insights on clinical workflows, digital health, LLM evaluation, automation, research ops, and turning real projects into a practical portfolio. Every week I release Healthcare AI Weekly which is a journal club discussing an important peer-reviewed healthcare AI article, and one you might have missed. Do you have a healthcare problem that you help with solving? Reach out. My email is [email protected] Links Github github.com/rtmalikian LinkedIn linkedin.com/in/raphael-t-malikian-mbbs-bsc-hons-71075436a --- This week in Healthcare AI Weekly: a source-grounded look at two new peer-reviewed healthcare AI papers. 1) Bavali-Gazik et al. — Developing and validating an AI-based electronic triage model for cardiac-suspected ED patients. PMID: 42182049; PMCID: PMC13195029. 2) Hiratsuka et al. — AI/ML in Alaska Native healthcare systems: symposium perspectives. PMID: 42176020; PMCID: PMC13202658. Comment question: which layer matters most for healthcare AI right now — model performance, workflow fit, or governance? Synthetic voice disclosure: narration uses edge-tts en-US-AndrewNeural synthetic voice for review production. Watch this episode on YouTube: https://youtu.be/gQbft5MLFTA YouTube Channel: https://www.youtube.com/@RaphaelMalikian-g4h Created by Raphael T. Malikian ([email protected]). In true AI fashion, this podcast was created with AI tools including text-to-speech using Microsoft Edge TTS and Hermes Agent by Nous Research.