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Leaving a paper trail behind

Leaving a paper trail behind
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Emergency EMR created in a week to respond to COVID-19 crisis

Emergency EMR created in a week to respond to COVID-19 crisis
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Emergency EMR created in a week to respond to COVID-19 crisis

Emergency EMR created in a week to respond to COVID-19 crisis
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Deep learning may help doctors choose better lung cancer treatments

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. Image: Wikimedia 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.

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International-journal
End-results
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நிறுவனம்-க்கு-கணக்கீட்டு

Machine learning model may guide treatment decisions for lung cancer patients

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.

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Institute-for-computational
International-journal-of-medical-informatics
Data-sciences
Penn-state-great-valley
International-journal
End-results
Cancer

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