Artificial Intelligence-Based Prostate Cancer Diagnosis Using MRI: A Comprehensive Review of Machine Learning and Deep Learning Approaches

Author(s)	Ms. Mamta Gehlot, Dr. Sumit Jain
Country	India
Abstract	Prostate cancer is one of the leading causes of cancer-related mortality among men, requiring accurate and early diagnosis for effective treatment. This review presents a comprehensive analysis of Artificial Intelligence (AI)-based techniques for prostate cancer detection, classification, grading, and segmentation using MRI data. Various methodologies, including machine learning, deep learning, hybrid models, and ensemble approaches, are examined. Deep learning models, particularly Convolutional Neural Networks and advanced architecture, demonstrate superior performance in extracting complex imaging features. Additionally, the integration of multiparametric MRI with clinical data enhances diagnostic accuracy and robustness. Despite promising results, challenges such as data imbalance, lack of interpretability, and limited clinical validation persist. This study highlights current trends, identifies research gaps, and provides insights into developing reliable and clinically applicable AI-based diagnostic systems.
Keywords	Prostate Cancer, Artificial Intelligence, Deep Learning, Machine Learning, Multiparametric MRI, Computer-Aided Diagnosis
Discipline	Engineering
Published In	Volume 4, Issue 3, May-June 2026
Published On	2026-05-09

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Advanced International Journal of Multidisciplinary Research