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Cancer recurrence remains a critical concern in healthcare, impacting patient prognosis and survival. This review explores the role of artificial intelligence (AI) in predicting cancer recurrence, emphasizing its potential to enhance personalized care. Key AI techniques, including machine learning algorithms, deep learning, and multi-omics data integration, are discussed. The review also addresses the need for regulatory oversight and ethical considerations. AI-driven prediction of cancer recurrence has transformative potential in optimizing patient outcomes.

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AI-Driven Prediction of Cancer Recurrence

  • 会议论文

  • 发表日期：

    2025年

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  • B. Annapoorna,
  • M. Janga Reddy,
  • B. Satyanarayana,
  • M. Ravi,
  • Pokala Krishnaiah,
  • Chilukuri Dileep

摘要

Cancer recurrence remains a critical concern in healthcare, impacting patient prognosis and survival. This review explores the role of artificial intelligence (AI) in predicting cancer recurrence, emphasizing its potential to enhance personalized care. Key AI techniques, including machine learning algorithms, deep learning, and multi-omics data integration, are discussed. The review also addresses the need for regulatory oversight and ethical considerations. AI-driven prediction of cancer recurrence has transformative potential in optimizing patient outcomes.