Wed, 2021-08-18 12:11
Machine Learning Working Group virtual meeting, August 23, 12pm-1pm ET
Wednesday, August 18, 2021 - 12:11

Please join us for a virtual Machine Learning Working Group Meeting on August 23rd, from 12-1pm EST. Greeshma Agasthya, PhD, Research Scientist in the Advanced Computing for Health Sciences Section at Oak Ridge National Lab will be presenting “Machine learning and deep learning-based time series analysis for early metastatic prostate cancer detection.”
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 USA. 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, Wu et al showed 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, in this study we will develop machine learning and deep learning models to predict mPCa at primary PCa diagnosis

The Center for Computational Imaging and Personalized Diagnostics has partnered with the Case Comprehensive Cancer Center to host the Machine Learning Working Group. Meetings are held with the express goal of leveraging the extensive Artificial Intelligence expertise concentrated across our partner institutions including Case Western Reserve University, University Hospitals, the Cleveland VA Medical Center, MetroHealth, and the Cleveland Clinic and beyond. Through facilitating the interaction of basic and clinical researchers we hope to strengthen the scientific merit of presented studies as well as identify novel collaborative opportunities. 

If you would like to attend this month’s session, please reach out to James Hale -

Fri, 2021-08-06 12:44
Study led by CCIPD Researcher Haojia Li Aids in Discovery of New Prognostic Biomarkers for Breast Cancer
Friday, August 6, 2021 - 12:44

CCIPD researchers have used Artificial Intelligence (AI) to identify new biomarkers for breast cancer that can predict whether the cancer will return after treatment. Furthermore, this study helped to identify which biomarkers can be identified from routinely acquired tissue biopsy samples of early-stage breast cancer. The key to that initial determination is collagen, a common protein found throughout the body, including in breast tissue. 

For more information, read the full story in CWRU’s The Daily.

Fri, 2021-07-30 14:59
Anant Madabhushi, PhD, is named to the 2021 Pathologist's Power List
Friday, July 30, 2021 - 14:59

Dr.Anant Madabhushi is named a Showstopper on The Pathologist’s 2021 Power List. This list celebrates 100 influential figures, thought leaders, and opinion shapers in pathology and laboratory medicine. Dr. Madabhushi was also named to the Power List in 2019 and 2020. 

For more information read more about this placement on The Pathologist’s website.

Thu, 2021-07-29 15:01
CCIPD Article in Top 10% Most Cited on PLOS ONE
Thursday, July 29, 2021 - 15:01

A CCIPD article is among the Top 10% Most Cited PLOS ONE papers published in 2018. Congratulations to CCIPD authors Andrew Janowczyk, PhD and Anant Madabhushi, PhD on this recognition of their paper titled, “A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue.” As of the time of recording, the article has been cited 49 times and counting!

Further congratulations to authors Jeffery Nirschl (first author), Eliot G. Peyster, Renee Frank, Kenneth Margulies and Michael Feldman.

To learn more, read the article on PLOS ONE.