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 ...

A Diagnostic Cost Group (DCG) machine learning algorithm succeeded in generating risk adjustment models and predicted healthcare spending better than the current HHS hierarchical condition category ...

The current MA risk adjustment model has shortcomings, both in predictive accuracy and payment equity across the Medicare program, which could be mitigated using lessons from machine learning. MA ...

What happens when companies on digital labor platforms no longer decide for themselves how much to pay their workers, but leave this to learning algorithms? Researchers at TU Darmstadt, Bielefeld ...

Relying on tainted, inherently biased data to make critical business decisions and formulate strategies is tantamount to building a house of cards. Yet, recognizing and neutralizing bias in machine ...