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Artificial intelligence across oncology specialties: current applications and emerging tools.
John Kang1, Kyle Lafata2,3,4, Ellen Kim5,6
1Department of Radiation Oncology, University of Washington, Seattle, Washington, USA.
BMJ Oncology
|January 31, 2025
Summary
Artificial intelligence (AI) helps analyze vast oncology data for better cancer detection and treatment planning. This review explores AI
Area of Science:
- Oncology
- Artificial Intelligence
- Medical Informatics
Background:
- Personalized oncology relies on extensive diagnostic and therapeutic data.
- The sheer volume of data exceeds human interpretation capabilities.
- Artificial intelligence (AI) offers a solution for managing and interpreting complex oncology data.
Purpose of the Study:
- To review multidisciplinary perspectives on AI applications in oncology.
- To highlight AI's role in integrating diverse data sources and tools.
Main Methods:
- Literature review synthesizing multidisciplinary insights on AI in oncology.
- Exploration of AI applications across various oncology subfields.
Main Results:
- AI enhances data interpretation for improved cancer detection and prediction.
- AI is applicable in AI-imaging, pathology, patient triage, radiotherapy, genomics-driven therapy, and surgery.
- Integration of AI with natural language processing, digital twins, and clinical informatics is crucial.
Conclusions:
- AI is essential for advancing personalized oncology by managing data complexity.
- AI integration promises to improve diagnostic accuracy, treatment efficacy, and clinical workflows.
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