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July 12, 2026CureusOpen Access

Artificial Intelligence in the Detection, Characterization, and Management of Renal Masses: A Narrative Review

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Authors

HBHasan F BualiTATarek AbushloaASAbdulaziz Al Shaibani

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Overview

Narrative review demonstrates AI's role in detecting and characterizing kidney tumors, highlighting implications for clinical practice.

Key Points

  • This review aims to summarize current evidence on the applications of AI in the detection, characterization, and management of renal masses.
  • Narrative review of English-language literature using PubMed and MEDLINE from 2018 to 2026.
  • Evaluation of AI applications in automated detection, imaging characterization, and surgical planning.
  • Analysis of AI tools' performance compared to traditional clinical scoring systems.
  • AI tools demonstrated strong performance in detecting and segmenting renal masses, with high accuracy on CT and MRI.
  • Radiomics classifiers effectively distinguished benign from malignant lesions and predicted tumor subtype without the need for biopsy.
  • Multimodal AI models outperformed established clinical scoring systems in predicting survival rates.

Cite This Study

Buali et al. (2026) studied this question.

synapsesocial.com/papers/6a532e014f7abc118adeca30https://doi.org/10.7759/cureus.112349
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