At the next Machine Learning Working Group virtual meeting, Greeshma Agasthya, research scientist in the Advanced Computing for Health Sciences Section at Oak Ridge National Lab, will present “Machine learning and deep learning-based time series analysis for early metastatic prostate cancer detection.” Agasthya’s talk will be held Monday, Aug. 23, from noon to 1 p.m. via Zoom. Learn more and get registration information.
Presentation abstract
Prostate cancer (PCa) is the second most common cancer among men in the United States. It was estimated that there were 191,930 new PCa cases in 2020 in the United States. A 2018 study showed an increasing trend in metastatic PCa (mPCa) too and they forecast an increase in annual burden by 42% by 2025.
Despite this prevalence and forecast, a 2011 study showed a decline of nearly 40% in PCa incidence, over the previous 25 years. However, this decline is not reflected in the mPCa survival numbers, with one study showing there was no improvement noted in overall survival for men with mPCa over a 20-year period. To help address this trend in mPCa and impact outcomes, Agasthya’s study will develop machine learning and deep learning models to predict mPCa at primary PCa diagnosis.