Machine-learning model predicts remission, relapse in cancer patients

Researchers have developed an algorithm to accurately predict which patients diagnosed with acute myelogenous leukemia (AML), a cancer of the blood and bone marrow, will go into remission following treatment and which ones will relapse.

Using bone marrow data and medical histories of AML patients, as well as blood data from healthy individuals, researchers were able to teach a standard 64-bit computer workstation running Windows to predict remission with 100 percent accuracy, while relapse was correctly predicted in 90 percent of relevant cases.

Author: Greg Slabodkin


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