Bashier ElKarami
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Bashier ElKarami has a total of 10 co-authors. Here are the top co-authors by number of shared publications:
Abedalrhman Alkhateeb
1 shared publication- Abedalrhman Alkhateeb
Department of Computer Science, Lakehead University, Thunder Bay, Canada
1 shared publication Behnam Shahrrava
Computer Science Department, The University of Windsor, ON, CA
1 shared publicationDaniel Sidhom
1 shared publicationJames Peabody
Department of Urology, Henry Ford Hospital, Detroit, MI; Vattikuti Urology Institute, Detroit, MI
1 shared publicationMani Menon
Department of Urology, Henry Ford Hospital, Detroit, MI; Vattikuti Urology Institute, Detroit, MI
1 shared publication
Latest Publications
- 17 March 2022
- Published by Elsevier in Urologic Oncology: Seminars and Original Investigations
- Vol. 40 (5) , 191.e15-191.e20
Machine learning-based prediction of upgrading on magnetic resonance imaging targeted biopsy in patients eligible for active surveillance
- 17 March 2022
- Published by Elsevier in Urologic Oncology: Seminars and Original Investigations
- Vol. 40 (5) , 191.e15-191.e20
Machine learning-based prediction of upgrading on magnetic resonance imaging targeted biopsy in patients eligible for active surveillance
- 1 September 2021
- Published by Wolters Kluwer Health in Journal of Urology
- Vol. 206 (Supplement)
MP62-04 MACHINE LEARNING-BASED PREDICTION OF UPGRADING TO ADVERSE PATHOLOGY IN PATIENTS WHO ARE CANDIDATES FOR ACTIVE SURVEILLANCE
INTRODUCTION AND OBJECTIVE:Our objective is to examine the ability of machine learning methods to predict upgrading of Gleason score on confirmatory magnetic resonance imaging guided targeted biops...
- 1 September 2021
- Published by Wolters Kluwer Health in Journal of Urology
- Vol. 206 (Supplement)
MP62-04 MACHINE LEARNING-BASED PREDICTION OF UPGRADING TO ADVERSE PATHOLOGY IN PATIENTS WHO ARE CANDIDATES FOR ACTIVE SURVEILLANCE
INTRODUCTION AND OBJECTIVE:Our objective is to examine the ability of machine learning methods to predict upgrading of Gleason score on confirmatory magnetic resonance imaging guided targeted biops...