Prediction of prostate biopsy outcomes at different cut-offs of prostate-specific antigen using machine learning: a multicenter study
Abstract Background Machine learning (ML) is a significant area of artificial intelligence, which can improve the accuracy of predictive or diagnostic models for differentiating between prostate biopsy outcomes. This study aims to develop a novel decision-support ML model for classifying patients wi...
Saved in:
| Main Authors: | Mostafa A. Arafa, Karim H. Farhat, Sherin F. Aly, Farrukh K. Khan, Alaa Mokhtar, Abdulaziz M. Althunayan, Waleed Al-Taweel, Sultan S. Al-Khateeb, Sami Azhari, Danny M. Rabah |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-03-01
|
| Series: | Journal of the Egyptian National Cancer Institute |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s43046-025-00265-3 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Association Between Prostate Cancer Detection Rate and Year of Prostate Biopsy
by: Young Jun Uhm, et al.
Published: (2025-02-01) -
Usefulness of prostate specific antigen density in detecting prostate carcinoma: A hospital-based study in patients with prostate biopsies
by: Reshmi Shrestha, et al.
Published: (2022-03-01) -
Optimal PSA density threshold for prostate biopsy in benign prostatic obstruction patients with elevated PSA levels but negative MRI findings
by: Yiji Peng, et al.
Published: (2025-03-01) -
Correlation of clinically significant prostate cancer sites across multiparametric MRI, prostate biopsy, and whole-mount pathology for optimal prostate biopsy strategy
by: Matteo Pacini, et al.
Published: (2025-02-01) -
Experience in the use of MRI-ultrasound fusion-targeted biopsy of the prostate for the diagnosis of prostate cancer
by: E. S. Nevirovich, et al.
Published: (2018-10-01)