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August 11, 2025Journal of Modern OncologyOpen Access

Prospects for the use of big data, artificial intelligence, machine learning, neural networks, and deep learning in the diagnosis and treatment of malignant tumors of the genitourinary system: a review

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Authors

AKA. V. Khachaturyan

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Overview

This review highlights machine learning and AI's role in improving diagnosis and treatment outcomes for urologic cancers, suggesting enhanced strategies.

Key Points

  • Machine learning algorithms predict treatment responses in metastatic castration-resistant prostate cancer, improving patient outcomes.
  • Analysis showed a 94% diagnostic accuracy using machine learning on images from patients diagnosed with bladder cancer and urine samples.
  • Deep learning enabled accurate tumor typing based on chemotherapy responses, enhancing personalized treatment for bladder cancer patients.
  • Artificial intelligence improved prognostic evaluation and therapy optimization in kidney cancer, expanding clinical applicability.

Cite This Study

A. V. Khachaturyan (2025) studied this question.

synapsesocial.com/papers/68a35ef30a429f797332844dhttps://doi.org/10.26442/18151434.2025.2.203225
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