This paper is in the following e-collection/theme issue:

Cancer genomic data analysis (9) AI applications in genomics and pathology informatics, including ‘Generative AI’ (19) Innovations and Technology for Cancer Prevention and Screening (201) Innovations in Cancer Diagnostic and Decision Support (109) Prostate Cancer (47) Machine Learning (2069) Ontologies, Classifications, and Coding (324)

Published on in Vol 6 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/72423, first published .
Framework for Race-Specific Prostate Cancer Detection Using Machine Learning Through Gene Expression Data: Feature Selection Optimization Approach

Framework for Race-Specific Prostate Cancer Detection Using Machine Learning Through Gene Expression Data: Feature Selection Optimization Approach

Framework for Race-Specific Prostate Cancer Detection Using Machine Learning Through Gene Expression Data: Feature Selection Optimization Approach

Authors of this article:

David Agustriawan1 Author Orcid Image ;   Adithama Mulia1 Author Orcid Image ;   Marlinda Vasty Overbeek1 Author Orcid Image ;   Vincent Kurniawan1 Author Orcid Image ;   Jheno Syechlo1 Author Orcid Image ;   Moeljono Widjaja1 Author Orcid Image ;   Muhammad Imran Ahmad2 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Jayaseeli J, Saranya S, Lakshmi K, Kothapali R, Seok G, Joshi G, Cho W. Multimodal feature-optimized approaches for cancer classification using microarray gene expression analysis. Scientific Reports 2025;15(1) View