Our CEO, Brian Anderson, MD, recently spoke about current efforts to mitigate potential harm from algorithms to marginalized communities at an event organized by the Doris Duke Foundation. Thank you to Kameron Matthews, MD, JD, FAAFP, Tina Hernandez-Boussard, and Shyam Visweswaran, MD, PhD for having this valuable discussion. #EncodingEquity #AI Watch here: https://lnkd.in/g6kJXEMS
Coalition for Health AI (CHAI)
Health and Human Services
Providing guidelines for the responsible use of AI in healthcare
About us
The Coalition for Health AI (CHAI™) is a community of academic health systems, organizations, and expert practitioners of artificial intelligence (AI) and data science. These members have come together to harmonize standards and reporting for health AI and educate end-users on how to evaluate these technologies to drive their adoption. Our mission is to provide guidelines regarding an ever-evolving landscape of health AI tools to ensure high-quality care, increase credibility amongst users, and meet healthcare needs.
- Website
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chai.org
External link for Coalition for Health AI (CHAI)
- Industry
- Health and Human Services
- Company size
- 2-10 employees
- Headquarters
- Boston
- Type
- Nonprofit
- Founded
- 2021
Locations
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Primary
Boston, US
Employees at Coalition for Health AI (CHAI)
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Dave Anderson
Ethical AI • Algorithm Auditing • Data Privacy • CyberSecurity • Production ML/AI | Board Member Data Community DC | USCG Auxiliary
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Nirav R. Shah
Senior Scholar, Clinical Excellence Research Center
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Jody Ranck
Startup Executive, social scientist, writer/thinker, digital health, AI, Ethics
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Tanya A. Zucconi, MBA, CPHIMS, PMP
| TRANSFORMATIVE HEALTHCARE | OPERATIONS | DIGITAL HEALTH INNOVATION | STRATEGIC COMMUNICATOR | MATRIXED MANAGEMENT EXPERTISE | POPULATION HEALTH |…
Updates
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Our CEO, Brian Anderson, MD, recently spoke with Keith J. Figlioli on LRVHealth's Healthcare is Hard podcast. Brian and Keith discuss developing transparency, safety, privacy, and reliability in healthcare AI, the evaluation of AI systems through assurance labs, and the importance of diverse representation throughout this pursuit. Listen to the full episode here: https://lnkd.in/egAst7bh
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We are thrilled to be hosting our first CHAI Assurance Standards Insight Infusion session on July 23rd at 2pm EST! This first session will be a general overview of the guide and checklists to provide insights into how you can comment. We invite the public to come learn more and contribute to this important work. Speakers include: Brian Anderson, MD, Nicoleta Economou, Megan Salwei, Lee Fleisher, Cora Han, Lisa Lehmann, Liz Garwood, David Talby, Alison Callahan, and Merage Ghane, Ph.D. Register here: https://lnkd.in/gaXEFp7w For CHAI members, we will be then be holding five additional sessions that will provide in-depth insights into the documents as applied to each of our five core principles areas. Become a member of CHAI: https://lnkd.in/gJj3mN4t We look forward to seeing you there! Coalition for Health AI (CHAI) #responsibleAI
Assurance Standards Insight Infusion #1
events.teams.microsoft.com
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Coalition for Health AI (CHAI) reposted this
A good POLITICO article on Scott Gottlieb's new JAMA opinion piece on how to approach new regulatory powers for the FDA over Health AI. Recommend reading both the media piece and the actual paper linked below. 👇 Coalition for Health AI (CHAI) #ResponsibleAI https://lnkd.in/eZUEzt9V
Trump’s FDA commissioner on regulating AI
politico.com
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Coalition for Health AI (CHAI) reposted this
Thrilled to share that CHAI has opened up several leadership job roles working on our amazing team!! We are #hiring! If you want to be part of an amazing team of passionate, extremely competent and fun people, making real impact in the field of Health AI, take a look at the job openings we just posted. 👇 👇 I also added several additional jobs posted in the comments thread below. Please share and repost if you know anyone who might be interested as well. Thanks!!
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Coalition for Health AI (CHAI) reposted this
A worthy call to action by CHAI founding members, John Brownstein, Christopher Longhurst, Karandeep Singh, Ashish Atreja, MD, MPH and Aneesh Chopra. This deeply resonates and aligns with the Coalition for Health AI (CHAI)'s vision to establish a federated network of Quality Assurance Labs for AI. Imaging a network of labs that can readily, and transparently generate prospective, real world evidence on AI model performance is desperately needed for post-market surveillance purposes if we are to ensure AI models are safe and effective for all of us.
AI promises to revolutionize healthcare by enhancing diagnosis, treatment, and patient safety. Yet, a critical gap exists between AI research and its real-world impact. We urgently need comprehensive clinical effectiveness evaluations to bridge this divide. My colleagues at UC San Diego Health, UC Davis Health, and I published this article in the NEJM AI to establish boundaries for using AI in the healthcare setting, bringing together research and real-world evidence for comprehensive clinical effectiveness. AI is bound to revolutionize our industry that was traditionally adverse to change, yet it is essential to collaborate on the shared goal of safer, more effective, and equitable care for all patients. Christopher Longhurst Karandeep Singh Aneesh Chopra Ashish Atreja, MD, MPH Our call to action: (1) Move Beyond Model Validation: It's essential to validate AI models not just through simulations but in real-world clinical settings, akin to clinical trials for new drugs. (2) Focus on Local Context: The importance of local health care contexts in AI model validation cannot be overstated. Different settings require tailored approaches for optimal outcomes. (3) Implement Science Principles: Adopting implementation science principles will ensure that AI tools are effectively integrated into health care workflows, resulting in tangible improvements in patient outcomes. A robust network of healthcare delivery organizations is crucial to focus on the clinical effectiveness of AI models in real-world settings. This collaborative approach will help us achieve safer, more effective, and equitable care for all patients. #HealthcareInnovation #AIinHealthcare #ClinicalEffectiveness #PatientSafety #ImplementationScience #AIValidation #EquitableCare #HealthTech
A Call for Artificial Intelligence Implementation Science Centers to Evaluate Clinical Effectiveness
ai.nejm.org
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"The question we asked was: is there a consensus perspective, at a technically specific level, to inform developers of what responsible AI looks like? The answer was no, there’s not. We believed that we needed one urgently, so our focus has been bringing together a community to build a consensus around what responsible AI looks like, with the hope of ensuring that AI serves all of us." Check out our CEO, Brian Anderson, MD in a recent Q&A with STAT's Nicholas St. Fleur about our work creating frameworks for the development and deployment of responsible AI in healthcare.
Q&A: Defining responsible AI in health care, with CHAI CEO Brian Anderson
https://www.statnews.com
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Coalition for Health AI (CHAI) reposted this
AI is evolving quickly, and many feel a sense of urgency. Clinicians must have a strong basis to trust that an AI solution will improve patient care and outcomes. At the Coalition for Health AI (CHAI), we are working to bring more evidence and transparency to that process. We are a diverse and growing community dedicated to creating a trusted framework to evaluate the safety and efficacy of these models and enable local validation. I recently sat down with STAT to talk about the pathway to responsible AI in healthcare.
Q&A: Defining responsible AI in health care, with CHAI CEO Brian Anderson
https://www.statnews.com
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Today we are excited to release the first draft of the CHAI Assurance Framework for responsible #healthAI. Our mission is to help build the broadest possible consensus across the health ecosystem to help ensure AI is effective and trusted. Our framework consists of an Assurance Standards Guide developed through collaboration between multiple, diverse stakeholders from across industries, and corresponding Assurance Reporting Checklists that translate the Guide into actionable evaluation criteria. Thank you to all who have contributed to this important work. The draft framework released today is open to public review and comment, for the next 60 days. You can find more information on our website.
CHAI Releases Draft Responsible Health AI Framework for Public Comment - CHAI - Coalition for Health AI
chai.org
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Coalition for Health AI (CHAI) reposted this
Next Tuesday, the Centre for Digital Transformation of Health present the second installment in their series exploring the potential of clinical AI in healthcare, featuring renowned expert Prof Nigam Shah from the Stanford Biomedical Data Science Program. As a founding member of the Coalition for Health AI (CHAI), Prof Shah is helping shape the future of healthcare by establishing guidelines for the adoption of credible, equitable and transparent health AI systems. Register to join online or in person on June 18, with limited spots available: https://ow.ly/T7Mz50Sgmkt
Prof Nigam Shah: How can we ensure that healthcare AI is actually useful?
eventbrite.com.au