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Recent Advances in Generative AI for Healthcare Applications.

Yasin Shokrollahi1, Jose Colmenarez1, Wenxi Liu2

  • 1Department of Biomedical Engineering and Science, Florida Institute of Technology, Melbourne, FL, 32901, USA.

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PubMed
Summary
This summary is machine-generated.

Generative AI, particularly diffusion and transformer models, is revolutionizing healthcare. These advanced AI technologies are improving medical imaging, drug discovery, and clinical decision-making, with significant future potential.

Keywords:
Diffusion modelsGenerative AIHealthcareReviewTransformers

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Area of Science:

  • Medical Informatics
  • Artificial Intelligence
  • Biotechnology

Background:

  • Artificial intelligence (AI) is transforming healthcare delivery and research.
  • Generative AI models, including diffusion and transformer architectures, show significant promise.
  • Applications span medical imaging, drug design, and clinical decision support.

Purpose of the Study:

  • To synthesize recent advancements in generative AI for healthcare.
  • To focus on the impact of diffusion and transformer models.
  • To provide a comprehensive overview for researchers and practitioners.

Main Methods:

  • Review of recent literature on generative AI in healthcare.
  • Emphasis on diffusion models and transformer architectures.
  • Analysis of applications in medical imaging, drug discovery, and clinical support.

Main Results:

  • Generative AI enhances medical imaging (reconstruction, classification, generation).
  • Breakthroughs achieved in protein structure prediction and drug design.
  • Improvements noted in clinical documentation, diagnostics, and decision support.

Conclusions:

  • Generative AI, especially diffusion and transformer models, offers transformative potential in healthcare.
  • Current capabilities are expanding, but limitations require further research.
  • Future directions include refining models and broadening clinical integration.