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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Emeritus Professor of Computer Science, Swansea University
Thoughtful analysis of digital health safety failures, usability focused medical device design, and the intersection of human factors engineering and clinical informatics.
Digital Health Safety / Human Computer Interaction / Medical Devices
Best for: Medical device manufacturers and clinical safety officers
Chair, Department of Biomedical Informatics, Harvard Medical School
Provides deep academic perspectives on the integration of artificial intelligence in medicine, clinical genomics, and the evolution of health informatics platforms.
Precision Medicine / Medical AI / Biomedical Informatics
Best for: Bioinformatics researchers and medical AI engineers
Professor of Dermatology, Harvard Medical School
Expert perspectives on digital health integration, virtual care adoption models, and clinical research regarding the effectiveness of remote patient monitoring technologies.
Digital Health / Telehealth / Virtual Care
Best for: Clinicians and virtual care providers
Professor and Center Director, University of California, San Francisco
Shares data driven research on electronic health record systems, health information exchange policies, and the measurable impact of technology on clinician burnout.
Electronic Health Records / Health IT Policy / Informatics Research
Best for: Health IT policymakers and clinical researchers
Professor of Population Health, NYU Langone Health
Shares valuable research on healthcare delivery science, electronic health record optimizations, and strategies to bridge the gap between clinical research and operations.
Delivery Science / EHR Optimization / Quality Improvement
Best for: Health services researchers and hospital administrators.
Professor, AI and Health, Massachusetts Institute of Technology
Offers updates on advanced deep learning applications in oncology, breast cancer risk assessment models, and machine learning models for early drug discovery.
Oncology AI / Drug Discovery / Deep Learning
Best for: Oncology researchers and pharmaceutical computational scientists
Director, Tech Policy Institute, Cornell University
Examines the policy implications of emerging technologies, focusing on AI regulations, public health communication, and tracking health misinformation across digital platforms.
Tech Policy / AI Regulation / Health Misinformation
Best for: Policy advisers and public health communication strategists
Showing 7 of 121 people. Listings are editorial, not paid, and nobody pays to appear here.