Machine-learning background helps PhD student at U of T design faster test, predicting …

A new, rapid gene-expression test could help clinicians determine the best management for patients with acute myeloid leukemia (AML) by making it possible to accurately predict a patient’s response to chemotherapy within one to two days of diagnosis. Although the standard treatment for AML is intensive chemotherapy, patients vary widely in their response. Currently, it is difficult to predict who will do well with chemotherapy, and who will not benefit and might do better with novel therapies offered by clinical trials.  “AML is an acute condition, and every day counts,” says researcher Stanley W. K. Ng. “For this reason, clinicians usually start treatment right away, without waiting for the test results.” By contrast, Ng’s test can determine patient risk in just 24 to 48 hours. Ng, a senior PhD candidate at…


Link to Full Article: Machine-learning background helps PhD student at U of T design faster test, predicting …

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