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Artificial intelligence in cancer: applications, challenges, and future perspectives.

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Area of Science:

  • Oncology
  • Medical Informatics
  • Computer Science

Background:

  • Artificial intelligence (AI) is rapidly advancing oncological research and personalized medicine.
  • Progress in AI algorithms, specialized hardware, and large-scale cancer data access fuels new applications.
  • AI is being applied across various cancer types and clinical domains.

Purpose of the Study:

  • To review the integration and applications of AI in oncology.
  • To highlight AI's potential in addressing complex challenges in cancer research.
  • To discuss barriers to the broader adoption of AI in clinical practice.

Main Methods:

  • Systematic organization of AI applications by cancer type and clinical domain.
  • Review of examples demonstrating AI's use in elucidating biological mechanisms and predicting outcomes.
  • Analysis of AI's role in interpreting epidemiological, behavioral, and real-world datasets.

Main Results:

  • AI applications show promise in improving patient outcomes through pattern identification in clinical data.
  • Deep learning models have successfully addressed previously insurmountable challenges in oncology.
  • AI facilitates the understanding of complex biological and real-world cancer data.

Conclusions:

  • AI holds significant promise for accelerating cancer research and improving health outcomes.
  • Ethical and scientifically rigorous application of AI is crucial for its success.
  • Overcoming adoption barriers is essential for realizing the full potential of AI in oncology.