A5069432751- Radiomics and Machine Learning in Medical Imaging
- Colorectal Cancer Screening and Detection
- Esophageal Cancer Research and Treatment
- Bladder and Urothelial Cancer Treatments
- Prostate Cancer Diagnosis and Treatment
- Liver Disease and Transplantation
- Circular RNAs in diseases
- Cancer-related molecular mechanisms research
- Cardiovascular Function and Risk Factors
- MRI in cancer diagnosis
- Liver Disease Diagnosis and Treatment
- MicroRNA in disease regulation
National Cancer Institute
2020
National Institutes of Health
2020
University of Colorado Anschutz Medical Campus
2019
Background The Prostate Imaging Reporting and Data System (PI‐RADS) provides guidelines for risk stratification of lesions detected on multiparametric MRI (mpMRI) the prostate but suffers from high intra/interreader variability. Purpose To develop an artificial intelligence (AI) solution PI‐RADS classification compare its performance with expert radiologist using targeted biopsy results. Study Type Retrospective study including data our institution publicly available ProstateX dataset....
To develop an artificial intelligence (AI)-based model for identifying patients with lymph node (LN) metastasis based on digital evaluation of primary tumors and train the using cystectomy specimens available from The Cancer Genome Atlas (TCGA) Project; our institution were included validation leave-out test cohort.
You have accessJournal of UrologyBladder Cancer: Basic Research & Pathophysiology IV (PD47)1 Apr 2020PD47-10 MULTIRESOLUTION APPLICATION OF ARTIFICIAL INTELLIGENCE IN DIGITAL PATHOLOGY FOR PREDICTION POSITIVE LYMPH NODES FROM PRIMARY TUMORS BLADDER CANCER Stephanie Harmon, Thomas Sanford, Michael Daneshvar*, G Brown, Chris Yang, Sherif Mehralivand, Joanna Shih, Joseph Jacob, Vladimir Valera, Piyush Agarwal, Peter Choyke, and Baris Turkbey HarmonStephanie Harmon More articles by this author ,...