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August 16, 2025Open Access

AI-Based Computational Pathology for Precision Lung Cancer Management: A Systematic Review and Meta-Analysis of Diagnostics and Prognostic Algorithms

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Authors

ICIngkar ChegedekovaAKAkim KapsalyamovPJPrashant K. Jamwal

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Overview

Systematic review evaluates AI's impact on accuracy and workload in lung cancer diagnostics, suggesting transformative potential.

Key Points

  • AI enhances diagnostic accuracy, facilitating personalized treatment strategies and improving patient outcomes worldwide.
  • Sensitivity, specificity, and predictive values were key performance metrics analyzed across 14 studies in the review.
  • The systematic review followed PRISMA guidelines and examined methods in histopathology, CT, and X-ray imaging modalities.
  • Implementation barriers include limited generalizability and ethical concerns, highlighting areas for further research and development.

Cite This Study

Chegedekova et al. (2025) studied this question.

synapsesocial.com/papers/68c235fdb210217d647729adhttps://doi.org/10.20944/preprints202508.0341.v1
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Also Consider

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  1. 1ARTIFICIAL INTELLIGENCE (AI) IN THE DIAGNOSIS OF PATHOLOGIST-CONFIRMED LUNG CANCER: A SYSTEMATIC REVIEW AND A DIAGNOSTIC TEST ACCURACY (DTA) META-ANALYSIS2025
  2. 2The Impact of Artificial Intelligence on Lung Cancer Diagnosis and Personalized Treatment2025 · 13 citations
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  5. 5A Systematic Review on Artificial Intelligence in Cancer Prediction2025