Customize Consent Preferences

We use cookies to help you navigate efficiently and perform certain functions. You will find detailed information about all cookies under each consent category below.

The cookies that are categorized as "Necessary" are stored on your browser as they are essential for enabling the basic functionalities of the site. ... 

Always Active

Necessary cookies are required to enable the basic features of this site, such as providing secure log-in or adjusting your consent preferences. These cookies do not store any personally identifiable data.

Functional cookies help perform certain functionalities like sharing the content of the website on social media platforms, collecting feedback, and other third-party features.

Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics such as the number of visitors, bounce rate, traffic source, etc.

Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.

Advertisement cookies are used to provide visitors with customized advertisements based on the pages you visited previously and to analyze the effectiveness of the ad campaigns.

Videos and Podcasts

Reducing the Healthcare Gap with Explainable AI

Dave DeCaprio, CTO & Co-Founder, and Maria Palombini, Director of the IEEE SA Healthcare and Life Sciences global practice, discuss how AI presents a new perspective on transparency, reduction of bias, and a path toward health stakeholders’ trust with explainability in its applications.

Fairness is not a math problem. Healthcare disparities are a global challenge requiring more than just physical care. Identifying and leveraging social determinants of health is a largely untapped key to closing the healthcare gap. Join Dave DeCaprio, Chief Technology Officer & Co-Founder, and Maria Palombini, Director of the IEEE SA Healthcare and Life Sciences global practice, as they discuss how AI presents a new perspective on transparency, reduction of bias, and a path toward health stakeholders’ trust with explainability in its applications.

Listen to the podcast

Name(Required)

By clicking on “Submit,” you agree to our Privacy Policy and Terms of Use. You may receive marketing materials and can opt-out at any time.

Related Resources

Videos and Podcasts

A Framework for Measuring the ROI and Health Equity Impact of AI-Enabled Health Programs

Discover a useful framework that your organization can use to evaluate programs’ ROI and impact on health equity, especially when introducing an artificial intelligence / machine learning component.

Videos and Podcasts

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.

White Papers

Context is King in Complex Interventions

Traditional program evaluation approaches fall short when it comes to assessing complex interventions, but HCOs must be capable of evaluating whether or not their programs work if they are to succeed in healthcare’s new business model. Without a “gold standard” evaluation approach, how can HCOs measure the sustainability and impact of their interventions?

Make AI/ML a core element of your care strategy.

Get in touch today to see the ClosedLoop platform in action.