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Advanced Radiotherapy Techniques and Machine Learning in Cancer Treatment - Tsair-Fwu Lee - Bog

- Integrating Cutting-Edge Technology and Data Science for Enhanced Oncological Outcomes

Bag om Advanced Radiotherapy Techniques and Machine Learning in Cancer Treatment

In 'Advanced Radiotherapy Techniques and Machine Learning in Cancer Treatment, ' this comprehensive work not only explores the synergy of advanced radiotherapy approaches like intensity-modulated radiation therapy and Stereotactic Body Radiotherapy (SBRT) with machine learning, but it also emphasizes the importance of meta-analysis in enhancing our understanding of these technologies. Addressing challenges such as treatment-induced edema, secondary cancer risks, and Normal Tissue Complication Probability (NTCP), the book integrates meta-analysis to offer a more robust insight into personalized cancer care, informed by the latest AI and radiomics advancements. Ideal for healthcare and technology professionals and students, it highlights the transformative integration of technology in medicine

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9789999314619
  • Indbinding:
  • Paperback
  • Udgivet:
  • 20. Januar 2024
  • Størrelse:
  • 152x229x6 mm.
  • Vægt:
  • 163 g.
  • 2-3 uger.
  • 18. Juli 2024
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Beskrivelse af Advanced Radiotherapy Techniques and Machine Learning in Cancer Treatment

In 'Advanced Radiotherapy Techniques and Machine Learning in Cancer Treatment, ' this comprehensive work not only explores the synergy of advanced radiotherapy approaches like intensity-modulated radiation therapy and Stereotactic Body Radiotherapy (SBRT) with machine learning, but it also emphasizes the importance of meta-analysis in enhancing our understanding of these technologies. Addressing challenges such as treatment-induced edema, secondary cancer risks, and Normal Tissue Complication Probability (NTCP), the book integrates meta-analysis to offer a more robust insight into personalized cancer care, informed by the latest AI and radiomics advancements. Ideal for healthcare and technology professionals and students, it highlights the transformative integration of technology in medicine

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