Can the 'additive tree' model expand machine learning in medicine?

When health care providers order a test or prescribe a medicine, they want to be 100 percent confident in their decision. That means being able to explain their decision and study it over depending upon how a patient responds. As artificial intelligence's footprint increases in medicine, that ability to check work and follow the path of a decision can become a bit muddied. That's why the discovery of a once-hidden through-line between two popular predictive models used in artificial intelligence opens the door much wider to confidently spread machine learning further throughout health care. The discovery of the linking algorithm and the subsequent creation of the "additive tree" is now detailed in the Proceedings of the National Academy of Sciences (PNAS).

from News on Artificial Intelligence and Machine Learning https://ift.tt/2nsGOAF

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