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"Cancer Prediction Tool Combines Machine Learning, Radiomics" - Greg Slabodkin

  • Health Data Management
  • New York, NY
  • (February 15, 2019)

Researchers at Mount Sinai and USC have developed a predictive framework that can distinguish between low- and high-risk prostate cancer. The prediction tool combines machine learning with radiomics, a branch of medicine that uses algorithms to extract large amounts of quantitative characteristics from medical images. “By rigorously and systematically combining machine learning with radiomics, our goal is to provide radiologists and clinical personnel with a sound prediction tool that can eventually translate to more effective and personalized patient care,” said Gaurav Pandey, PhD, assistant professor of genetics and genomic sciences at the Icahn School of Medicine at Mount Sinai.

— Gaurav Pandey, PhD, Assistant Professor, Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai

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