Machine-learning Software Beats Pathologists in Lung Cancer Assessment Study

Lung cancer research may have just taken a considerable leap forward — a recent study reports that a computer using a machine-learning approach was trained to predict the type, severity, and prognosis of such cancers far better than a skilled pathologist. In addition to giving oncologists a tool for predicting outcomes, the study, “Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features,” published in the journal Nature Communications, shows the method could also provide scientists with new insights into cancer cell characteristics, helping them understand how a tumor starts developing and how it changes during disease progression. Basically, machine learning is always based on data, observations, direct experience, or instruction. The computer, literally, studies computer algorithms and then computes the information to complete a task or make an accurate prediction. While the study was performed on lung…


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