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Can machine learning predict pharmacotherapy outcomes? An application study in osteoporosis
33
Zitationen
6
Autoren
2022
Jahr
Abstract
Machine learning-based models hold potential in forecasting the outcomes of treatment for osteoporosis via early initiation of first-line therapy for patients with subclinical disease; or a switch to second-line treatment for patients with a high risk of impending treatment failure. This convenient approach can assist clinicians in adjusting treatment tailored to individual patient for prevention of disease progression or ineffective therapy.
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