The Signal Directory
Founders, investors, health system and payer leaders, policy people and analysts. Filter by the part of the industry they work in and where they post.
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Director of Stanford AIMI Center, Stanford University
Readers get research insights on medical imaging AI, updates on academic radiology AI evaluations, and regular summaries of the field's clinical safety benchmarks.
Medical Imaging AI / Clinical Validation / Radiology Research
Best for: Radiologists and medical imaging AI researchers.
Chief Health AI Officer, UC San Diego Health
Readers get updates on clinical AI governance, practical advice on deploying machine learning tools at the bedside, and critical evaluations of health technology.
Clinical AI Governance / Bedside Implementation / EHR Integration
Best for: Clinical informaticians and hospital IT leaders.
Chief Data Science Officer, Mass General Brigham
Readers obtain deep insights into enterprise AI deployment in large hospital networks, clinical validation frameworks, and national policies on imaging AI standards.
Enterprise AI / Clinical Imaging Standards / Healthcare Quality
Best for: Health system executives and imaging technologists.
Principal Research Scientist, MIT
Readers receive global perspectives on clinical database transparency, machine learning bias, and international research collaborations utilizing open-source medical data resources.
Open-Science Data / Global Clinical AI / Algorithmic Transparency
Best for: Open-science advocates and global health researchers.
Associate Professor, MIT
Readers get detailed insights on machine learning robustness, algorithmic fairness in clinical datasets, and academic research focused on equitable health technology development.
Machine Learning Robustness / Algorithmic Fairness / Clinical Datasets
Best for: Computer scientists and medical ethics professionals.
Chief Medical Officer, Nuance Communications
Followers gain industry perspectives on generative AI in medicine, enterprise-scale healthcare cloud computing tools, and translation of research into clinical products.
Generative Healthcare AI / Enterprise Health Technology / Product Translation
Best for: Digital health developers and technology leaders.
Chief Data Scientist, Duke Health
Followers get authoritative updates on health AI evaluation frameworks, algorithm registry standards, and institutional governance structures designed to ensure safe, equitable AI.
AI Evaluation Standards / Health Algorithm Registries / Responsible AI
Best for: Healthcare compliance officers and AI governance leads.
Chief Data Scientist, Stanford Health Care
Followers receive academic and practical perspectives on using electronic health record data to train clinical AI models, safe deployment strategies, and health AI governance.
Clinical Data Science / Informatics / AI Deployment Governance
Best for: Informatics professionals and clinical data scientists.
Founder and CEO, Bayesian Health
Readers learn about real-world clinical AI deployment, methods for reducing diagnostic errors, and building reliable artificial intelligence tools for critical care environments.
Diagnostic AI / Critical Care / AI Product Development
Best for: Digital health founders and intensive care clinicians.
Associate Professor of Health Policy, UC Berkeley
Followers receive rigorous analysis of algorithmic bias in healthcare, evaluations of clinical machine learning models, and methods to make clinical algorithms more equitable.
Algorithmic Bias / Machine Learning Equity / Clinical Policy
Best for: Health policy researchers and clinical data scientists.
Showing 10 of 121 people. Listings are editorial, not paid, and nobody pays to appear here.