Clinico-radiological characteristic-based machine learning in reducing unnecessary prostate biopsies of PI-RADS 3 lesions with dual validation
ConclusionsThe machine learning –based random forest classifier provided a reliable probability if a PI-RADS 3 patient was benign.Key Points•Machine learning –based classifiers could combine the clinical characteristics with accessible information on image report of PI-RADS 3 patient to generate a probability of malignancy.•This probability could assist surgeons to make diagnostic decisions with more confidence and higher efficiency.
Source: European Radiology - Category: Radiology Source Type: research
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