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January 6, 2026AIOpen Access

AI-Driven Advances in Precision Oncology: Toward Optimizing Cancer Diagnostics and Personalized Treatment

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Authors

LBLuka BulićPBPetar BrlekNHNenad Hrvatin

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Overview

AI demonstrates improved risk stratification and treatment outcomes in precision oncology, suggesting better cancer diagnostics and therapies.

Key Points

  • This research examines the role of AI in enhancing cancer diagnostics and personalized treatment through precision oncology.
  • Integration of radiological, histopathological, genomic, and clinical data
  • Application of prognostic algorithms to predict survival and treatment responses
  • Exploration of reinforcement learning models for optimizing radiotherapy
  • Development of AI-driven image analysis platforms in radiology and pathology
  • AI improves tumor characterization and molecular classification
  • Clinical decision support systems assist physicians in managing complex cancer care
  • Current AI models face challenges of data quality and algorithmic bias
  • Regulatory hurdles potentially limit effective AI integration in oncology

Cite This Study

Bulić et al. (2026) studied this question.

synapsesocial.com/papers/695d85653483e917927a4f7dhttps://doi.org/10.3390/ai7010011
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