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Deep learning may help doctors choose better lung cancer treatments
Deep learning, a powerful machine learning model, could guide doctors and healthcare workers in weighing treatment and care options, according to a team of Great Valley researchers.
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Deep learning may help doctors choose better lung cancer treatments
Matt Swayne
February 16, 2021
MALVERN, Pa. 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.
It is a hopeful time of year for the European Alliance for Personalised Medicine (EAPM) as spring finally unveils itself across the EU and coronavirus vaccinations proceed apace, writes EAPM Executive Director Dr. Denis Horgan. New newsletter, 9th EU Presidency Conference The latest EAPM newsletter is now available for your attention, and it has much in there to […]
Machine learning model may guide treatment decisions for lung cancer patients
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.