Doctors and healthcare workers may one day use a machine learning model, called deep learning, to guide their treatment decisions for lung cancer patients, according to a team of Penn State Great Valley researchers.
In a study, the researchers report that they developed a deep learning model that, in certain conditions, was more than 71% accurate in predicting survival expectancy of lung cancer patients, significantly better than traditional machine learning models that the team tested. The other machine learning models the team tested had about a 61% accuracy rate.
Information on a patient’s survival expectancy could help guide doctors and caregivers in making better decisions on using medicines, allocating resources and determining the intensity of care for patients, according to Youakim Badr, associate professor of data analytics.
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International Journal of Medical Informatics. Study Paper:
Ibuprofen and Emphysema
