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Artificial intelligence and machine learning in cancer imaging.

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|October 31, 2022
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Summary
This summary is machine-generated.

Artificial intelligence (AI) and machine learning (ML) tools are advancing cancer imaging. Multidisciplinary collaboration is crucial for developing and implementing these AI/ML tools effectively in healthcare.

Keywords:
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Area of Science:

  • Oncology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Artificial intelligence (AI) and machine learning (ML) are increasingly utilized in developing tools for cancer imaging.
  • The integration of these advanced technologies into clinical practice necessitates careful consideration.

Purpose of the Study:

  • To review key developments in AI and ML for cancer imaging.
  • To discuss challenges and opportunities in this rapidly evolving field.
  • To outline considerations for developing and disseminating AI/ML tools and fostering the necessary ecosystem.

Main Methods:

  • Multidisciplinary review of current AI and ML applications in cancer imaging.
  • Analysis of challenges and opportunities for algorithm development and implementation.
  • Discussion on ecosystem development for AI/ML in cancer imaging.

Main Results:

  • Significant advancements in AI/ML tools for cancer imaging are evident.
  • Multidisciplinary engagement is vital for successful tool development and adoption.
  • Key challenges include robust testing and widespread dissemination.

Conclusions:

  • Effective development and implementation of AI/ML in cancer imaging demand a collaborative, multidisciplinary approach.
  • Addressing challenges in algorithm development, testing, and dissemination is essential for clinical integration.
  • Fostering a supportive ecosystem is critical for the growth of AI/ML in oncology imaging.