A Comprehensive Review of Artificial Intelligence Approaches in Kidney Cancer Medical Images Diagnosis, Datasets, Challenges and Issues and Future Directions

Abstract

Various diseases are prevalent in global populations and can be attributed to human lifestyles, economic conditions, social factors, genetics, and other country-specific factors. Our study provides a detailed analysis of the current methods and uses of artificial intelligence (AI) in diagnosing kidney cancer. This literature review examines the most recent advancements and uses of AI in diagnosing cancer of the kidneys, emphasizing its significant influence on medical diagnosis and patient treatment. Evaluate their efficacy, explore prospective areas for future study and development, and identify obstacles and constraints, offering a fundamental review of critical advancements in AI, machine learning, and deep learning. AI-powered diagnostic tools expedite the analysis of intricate images and enhance the early identification of diseases, ultimately leading to improved patient results. Furthermore, the utilization of AI-driven image processing enables the customization of treatment regimens, thereby enhancing the efficiency of healthcare provision. This review primarily highlights the importance of conducting additional research and improving AI to transform the detection and treatment of kidney cancer.