The current MA risk adjustment model has shortcomings, both in predictive accuracy and payment equity across the Medicare ...

A machine-learning algorithm originally built to spot impact craters on Mars has been retrained on ocean-floor data, and the ...

Artificial intelligence technology allows computers and machines to simulate human intelligence and problem-solving capabilities.

Objective This study aims to evaluate the relationship between obesity (measured by Body Mass Index (BMI)) and postoperative ...

Supervised learning algorithms learn from labeled data, where the desired output is known. These algorithms aim to build a model that can predict the output for new, unseen input data. Let’s take a ...

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...

This course covers three major algorithmic topics in machine learning. Half of the course is devoted to reinforcement learning with the focus on the policy gradient and deep Q-network algorithms. The ...

The accelerating growth of electronic waste (e-waste), industrial byproducts, and natural resources depletion highlights the ...

Intelligent organizations prioritize investments in machine learning and real-time data to improve decision making, accelerate revenue generation efforts, reduce operational expenses and protect ...

For grid-scale energy storage and national energy resilience, the U.S. needs better batteries. Lawrence Livermore National ...