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Prostate-Specific Antigen

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Evaluating prostate cancer diagnostic methods: The role and relevance of digital rectal examination in modern era.

Investigative and clinical urology
This review examines diagnostic methods for prostate cancer, focusing on the role of digital rectal examination (DRE) alongside modern advancements like prostate-specific antigen (PSA) testing, Prostate Health Index (PHI), magnetic resonance imaging ...

Prediction of Prostate Cancer From Routine Laboratory Markers With Automated Machine Learning.

Journal of clinical laboratory analysis
BACKGROUND: In this study, we attempted to select the optimum cases for a prostate biopsy based on routine laboratory test results in addition to prostate-specific antigen (PSA) blood test using H2O automated machine learning (AutoML) software, which...

Prediction of Prostate Cancer Grades Using Radiomic Features.

Acta medica Okayama
We developed a machine learning model for predicting prostate cancer (PCa) grades using radiomic features of magnetic resonance imaging. 112 patients diagnosed with PCa based on prostate biopsy between January 2014 and December 2021 were evaluated. L...

Development of a deep learning system for predicting biochemical recurrence in prostate cancer.

BMC cancer
BACKGROUND: Biochemical recurrence (BCR) occurs in 20%-40% of men with prostate cancer (PCa) who undergo radical prostatectomy. Predicting which patients will experience BCR in advance helps in formulating more targeted prostatectomy procedures. Howe...

Integrating radiological and clinical data for clinically significant prostate cancer detection with machine learning techniques.

Scientific reports
In prostate cancer (PCa), risk calculators have been proposed, relying on clinical parameters and magnetic resonance imaging (MRI) enable early prediction of clinically significant cancer (CsPCa). The prostate imaging-reporting and data system (PI-RA...

Machine learning models for enhanced diagnosis and risk assessment of prostate cancer with Ga-PSMA-617 PET/CT.

European journal of radiology
OBJECTIVE: Prostate cancer (PCa) is highly heterogeneous, making early detection of adverse pathological features crucial for improving patient outcomes. This study aims to predict PCa aggressiveness and identify radiomic and protein biomarkers assoc...

Prediction of prostate biopsy outcomes at different cut-offs of prostate-specific antigen using machine learning: a multicenter study.

Journal of the Egyptian National Cancer Institute
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-su...

Effective reduction of unnecessary biopsies through a deep-learning-assisted aggressive prostate cancer detector.

Scientific reports
Despite being one of the most prevalent cancers, prostate cancer (PCa) shows a significantly high survival rate, provided there is timely detection and treatment. Currently, several screening and diagnostic tests are required to be carried out in ord...

Predicting Prostate Cancer Diagnosis Using Machine Learning Analysis of Healthcare Utilization Patterns.

Studies in health technology and informatics
This study investigated healthcare utilization patterns prior to prostate cancer diagnoses, aiming to develop machine learning models for early prediction of cancer diagnosis. Data from the All of Us Research Program was used, focusing on adult patie...

Validation of a Digital Pathology-Based Multimodal Artificial Intelligence Biomarker in a Prospective, Real-World Prostate Cancer Cohort Treated with Prostatectomy.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: A multimodal artificial intelligence (MMAI) biomarker was developed using clinical trial data from North American men with localized prostate cancer treated with definitive radiation, using biopsy digital pathology images and key clinical in...