A REVIEW ON INTEGRATION OF MACHINE LEARNING FOR THE EARLY DETECTION OF CANCER THROUGH IMAGE ANALYSIS

  • Unique Paper ID: 183128
  • Volume: 12
  • Issue: 3
  • PageNo: 192-196
  • Abstract:
  • The early identification of cancer is essential for enhancing patient outcomes and increasing survival rates. Conventional diagnostic techniques frequently encounter difficulties in accurately detecting early-stage cancers, which can result in postponed treatment and diminished opportunities for effective intervention. Recent advancements in artificial intelligence, particularly in machine learning and deep learning, have greatly improved the ability to diagnose and forecast cancer. This review examines the application of multi-modal imaging data, genomics, and clinical parameters to implement machine learning strategies in the early diagnosis of cancer. The integration of machine learning with imaging data obtained from various modalities has been shown to be an effective approach for enhancing the diagnostic precision of early cancer detection. This review will explore the current landscape of machine learning in the diagnosis of early-stage cancer, with a focus on the analysis of multi-modal imaging.

Cite This Article

  • ISSN: 2349-6002
  • Volume: 12
  • Issue: 3
  • PageNo: 192-196

A REVIEW ON INTEGRATION OF MACHINE LEARNING FOR THE EARLY DETECTION OF CANCER THROUGH IMAGE ANALYSIS

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