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UNOS associate data scientist Carlos Martinez uses machine learning to interpret kidney allocation rates

UNOS associate data scientist Carlos Martinez uses machine learning to interpret kidney allocation rates

More than two dozen United Network for Organ Sharing researchers presented their data-driven studies at the American Transplant Congress this year.

Among them, UNOS associate data scientist Carlos Martinez shared the results of his effort to use machine learning to predict deceased donor kidney biopsy results. “We were motivated to do the research based on the influential role of biopsy findings on kidney allocation,” he said. “We wanted to determine if biopsies served as representations of other clinical data.”

The results of the research indicated that predicting biopsy results based on clinical and lab data is challenging, but suggested that machine learning could present a new way to interpret the data.

Read more about how Martinez worked with UNOS data science manager Andrew Placona to develop and evaluate the new machine learning model.

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