Identification of Key Candidate Genes in Prostate Adenocarcinoma Using Bioinformatics and Machine Learning Approaches

This study integrates clinical and genomic data using machine learning to predict overall survival and identify key prognostic genes in prostate adenocarcinoma.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-12
DOI
https://doi.org/10.5281/zenodo.17332803
Primary Topic
Prostate Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
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article

Identification of Key Candidate Genes in Prostate Adenocarcinoma Using Bioinformatics and Machine Learning Approaches

Zenodo (CERN European Organization for Nuclear Research)
Prostate Cancer Diagnosis and Treatment
article

Identification of Key Candidate Genes in Prostate Adenocarcinoma Using Bioinformatics and Machine Learning Approaches

article en

Abstract

This study integrates clinical and genomic data using machine learning to predict overall survival and identify key prognostic genes in prostate adenocarcinoma.

Zenodo (CERN European Organization for Nuclear Research)
Çanakkale Onsekiz Mart Üniversitesi (TR)
Openalex Percentile: Top 34%
Prostate Cancer Diagnosis and Treatment
DOIOpen Access PDFOpenAlex
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Identification of Key Candidate Genes in Prostate Adenocarcinoma Using Bioinformatics and Machine Learning Approaches · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS