As predictive models proliferate, providers and decision makers require accessible information to guide their use. Preventing and combating bias must also be priorities in model development and in ...

Inaccurate or overlooked alerts on manufacturing data can be reduced with proper data handling when developing and deploying predictive models. Data analytics, and specifically predictive analytics, ...

CEO of InfluxData, a leading time series platform, board member for One Heart Worldwide and board advisor for Lucidworks and The Fabric. In the current global business landscape, data-driven ...

Patients are less comfortable with predictive models used for health care administration compared with those used in clinical practice, signaling misalignment between patient comfort, policy, and ...

Effective evaluation and governance of predictive models used in health care, particularly those driven by artificial intelligence (AI) and machine learning, are needed to ensure that models are fair, ...

Which kind of AI should companies focus on—generative AI, which produces writing, computer code, images, video and other content, or predictive AI, which targets ads, marketing, fraud detection, risk ...