New tool to evaluate the risk of prostate cancer: study



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New YorkAccording to a new study, researchers, including one of Indian origin, have developed a new machine learning framework that can distinguish between low and high risk prostate cancer more accurately than ever before. The study conducted by the Icahn School of Medicine in Mount Sinai and the Keck School of Medicine at the University of Southern California (USC) showed that the framework is intended to help physicians, particularly radiologists, to identify with greater Precision treatment options for patients with prostate cancer, decreasing the possibility of unnecessary clinical intervention.

Currently, the standard methods used to evaluate the risk of prostate cancer are multiparametric magnetic resonance imaging (mpMRI), which detects prostate lesions, and the Prostate Imaging Data and Reporting System, version 2 (PI-RADS v2), a five-point scoring system that clbadifies the lesions found in the mpMRI.

However, the current tools used to predict the progression of prostate cancer are generally subjective in nature, leading to different interpretations among physicians.

The findings, published in Scientific Reports, showed that by combining machine learning with radionics, a branch of medicine that uses algorithms to extract large amounts of quantitative characteristics from medical images, the researchers were able to clbadify prostate cancer of patients with high sensitivity and an even higher predictive value. Therefore, the approach has been proposed to remedy this drawback.

"By rigorously and systematically combining machine learning with radionics, our goal is to provide radiologists and clinicians with a solid prediction tool that can translate into more effective and personalized patient care," said Gaurav Pandey, professor badistant of the Icahn School of Medicine. on Mount Sinai.

The way to predict the progression of prostate cancer with high precision is improving more and more, and we believe that our objective framework is a much needed advance, the study noted.

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