Videos and Podcasts
Explainable AI for Health
Dave DeCaprio, Co-Founder and CTO at ClosedLoop, sits down with Ian Alrahwan of the The University of Texas at Austin AI Heath Lab.
In this podcast episode, Dave DeCaprio, Co-Founder and CTO at ClosedLoop, sits down with Ian Alrahwan of the The University of Texas at Austin AI Heath Lab. Together, they discuss where AI and ML fit into clinicians’ decision-making process and the rationale behind training models on specific populations. Dave shares the story behind ClosedLoop’s CMS AI Challenge win and why the ability to rapidly experiment set the company apart.
Listen to the podcast
Related Resources
AI = ROI How AI Drives Health Outcomes and Tangible ROI in Healthcare
In this webinar with Massachusetts Health Data Consortium, ClosedLoop discusses measuring tangible ROI for predictive systems, creating explainable AI, addressing algorithmic bias, and overcoming the deployment challenges of machine learning models.
Practice-Based Evidence Improving Health Equity Requires Transforming our Focus, Tools, and Systems
Access this on-demand webinar with AIMed to hear Carol McCall, Chief Health Analytics Officer at ClosedLoop, describe how: (1) there are still significant gaps in evidence regarding effective health equity interventions, (2) closing this gap will require expanding the ways evidence is created and used, and (3) organizations are better positioned than they may think to adopt new methods now and can play an active role in improving health equity.
Millennium Alliance Live Featuring Andrew Eye
Andrew Eye, CEO at ClosedLoop, breaks down AI's role in driving down the total cost of care and improving clinical decision-making to produce better health outcomes.
