Enhancing Prostate Cancer Risk Prediction Using a Hybrid Near Sets and Soft Sets Model: A Novel Approach for Improved Patient Care

  • Amr H. Abdelhaliem Faculty of Science and Information Technology, Irbid National University, Irbid, Jordan
  • Noha MM. Abdelnapi Department of Computer Science Faculty of Computers and Information, Suez University, Egypt
  • Mohammed A. Atiea Department of Computer Science Faculty of Computers and Information, Suez University, Egypt
DOI: https://doi.org/10.19139/soic-2310-5070-2382
Keywords: Soft set; information system; near sets; near set approximations; prostate cancer

Abstract

Prostate cancer is a major health concern, and accurate risk prediction is essential for effective treatment. This paper presents a novel hybrid model combining near sets and soft sets to enhance prostate cancer risk assessment. By integrating artificial intelligence with medical data, our model captures uncertainties and provides more precise, personalized risk evaluations. Experiments focusing on key clinical factors, such as age and PSA levels, demonstrate significant improvements in early detection and treatment decisions. This research highlights the potential of hybrid AI models to improve patient care and outcomes in oncology.
Published
2025-05-06
How to Cite
Abdelhaliem, A. H., Abdelnapi , N. M., & Atiea, M. A. (2025). Enhancing Prostate Cancer Risk Prediction Using a Hybrid Near Sets and Soft Sets Model: A Novel Approach for Improved Patient Care. Statistics, Optimization & Information Computing. https://doi.org/10.19139/soic-2310-5070-2382
Issue
Online First
Section
Research Articles
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