Artificial intelligence (AI) is helping to transform healthcare by improving research, diagnosis, treatment, and care delivery systems. Much of this progress depends on collecting and preparing large health data sets, which underpin the training of algorithms and development of AI models. In this way, health data and AI go hand-in-hand in driving the advancement of next generation treatments and care.
In this report, learn about the new approaches to data management that are helping algorithms train on diverse sets of patient data without exposing private information. Discover how the industry is responding to grassroots efforts calling for algorithmic transparency (empowering people to understand how AI impacts their care regimens) and data equity (ensuring that all communities are fairly represented in the data sets used to train AI systems). And understand how the growing adoption of aggregated data learning—combining different data sets to uncover new insights—and the realization of predictive medicine, are allowing healthcare providers to anticipate health needs for patients and communities before they arise.