CTO Dave DeCaprio sits down with Jeff Winkler on the most recent episode of Chasing Squirrels, a podcast dedicated to connecting software engineers with exciting opportunities, describing job requirements, and highlighting the transformative work of emerging startups. In this episode, Dave details his professional journey, highlights some of ClosedLoop's real-world impact, and outlines what a software engineering position at ClosedLoop looks like.
Join the Austin Forum on Technology & Society's conversation on a multitude of topics surrounding equity in tech, featuring ClosedLoop Co-Founder and CTO Dave DeCaprio, Austin Urban Technology Movement President and CEO Michael Ward Jr, Digi.city Founder Chelsea Collier, and Austin Forum on Technology & Society’s Jessica Sager.
In this 45 minute webinar session, ClosedLoop CTO Dave DeCaprio details how we won the CMS AI Health Outcomes Challenge, what obstacles we encountered along the way, and what contributed to our winning submission.
Carol McCall, Chief Healthcare Analytics Officer at ClosedLoop, and Erich Huang, PhD, Chief Science & Innovation Officer at Onduo, were recently featured as panelists at MedCity INVEST. Their discussion was centered on combatting bias in AI. Specifically, they outlined how to ensure that implicit bias does not make its way into algorithms and the standards for ensuring that technology doesn’t make systemic inequality worse.
Joseph Gartner, PhD, Director of Data Science, was featured on the Alldus AI in Action podcast. The podcast aims to share the insights of technologists and data science enthusiasts and to showcase the excellent work that is being done within AI in the United States and Europe. Joseph delves into his career and how he ended up at ClosedLoop, ClosedLoop's agile approach to AI, why the work he's doing excites him, and his predictions for the future of ClosedLoop and healthcare-focused data science.
In this podcast, Andrew Eye, Co-founder and CEO of ClosedLoop.ai, discusses how ClosedLoop's healthcare-specific data science platform enables their clients to create algorithms tailored to their specific data. Andrew also discusses the company's $34 million in Series B funding to expand the reach of its data science platform, and he goes in depth on how the company won the $1.6M CMS AI Health Outcomes Challenge — the largest healthcare-focused AI contest ever.
In this Society of Actuaries podcast, Carol McCall, FSA, MAAA, MPH, and Chief Health Analytics Officer at ClosedLoop.ai, speaks with Robert Eaton, FSA, MAAA, about how AI in healthcare has become a necessity. Carol emphasizes the importance of navigating an actuarial career with curiosity and genuine care for your chosen area of focus. The two also discuss the factors that contributed to ClosedLoop.ai recently being announced the winner of the Centers for Medicare & Medicare Services (CMS) AI Health Outcomes Challenge.
Dave DeCaprio, ClosedLoop's CTO and founder, was invited to write a chapter for Leveraging Artificial Intelligence in Global Epidemics, a book detailing the role of AI in various stages of disease outbreak – using COVID-19 as a case study. Dave's chapter, entitled "Preparing with predictions: forecasting epidemics with artificial intelligence," covers factors to consider when assessing data for AI use, explores real-world case studies, and evaluates the application of predictions in the areas of disease spread, population health management, and resource allocation.
On this episode of The Pulse of AI, Andrew Eye, founder and CEO of ClosedLoop.ai, discusses how AI and data are being used now, the barriers holding back innovation, and what healthcare will look like in 10 years. ClosedLoop combines an intuitive end to end machine learning platform with a comprehensive library of healthcare specific features and model templates. ClosedLoop has taken a vertical approach and it is really paying off both for them and their customers.
ClosedLoop’s ML Ops enables data scientists to seamlessly deploy models and drive success at scale. To support continuous improvement and learning in an ever-changing healthcare environment, ML Ops provides a suite of capabilities to not only configure and manage deployments, but automate model performance monitoring and effortlessly retrain models, with support for audit and governance.
ClosedLoop’s Enterprise Healthcare Feature Store (EHFS) provides all the features and functionality of traditional feature stores – enabling shareability, reusability, and consistency of features from model training to production and maintenance. Further, it enables data scientists to develop a centralized feature repository with unmatched efficiency through its Healthcare Feature Library.
ClosedLoop.ai, which placed first out of 300+ teams in the CMS AI Health Outcomes Challenge, has AutoML capabilities that are purpose-built to handle messy healthcare data and streamline model development from preprocessing to validation. Built-in model explainability reports leverage patent-pending Factor EvidenceTM technology and cover everything from population-level statistics to individual patient histories.