Systematic review of artificial intelligence competitions in radiology: a focus on design, evaluation, and trends
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Summary
This summary is machine-generated.Artificial intelligence (AI) competitions in medical imaging are diverse, covering numerous specialties and fostering global collaboration. These events drive innovation and increase awareness of AI
Area Of Science
- Medical Imaging
- Artificial Intelligence
- Healthcare Technology
Background
- Artificial intelligence (AI) is increasingly integrated into medical imaging.
- AI competitions serve as a platform for development and evaluation in this field.
- Understanding the landscape of these competitions is crucial for future advancements.
Purpose Of The Study
- To explore the characteristics and scope of AI competitions in medical imaging.
- To evaluate AI competitions in medical imaging retrospectively from 2017 to 2023.
- To identify trends and impacts of these competitions on AI adoption in healthcare.
Main Methods
- Retrospective review of AI competitions in medical imaging (2017-2023).
- Searched PubMed and grand-challenge website for relevant AI and competition terms.
- Included 26 AI competitions covering diverse medical imaging applications.
Main Results
- Competitions spanned various specialties, including brain imaging, stroke detection, and bone age estimation.
- Many competitions involved international collaborations between medical and engineering professionals.
- Diverse databases and global team participation were noted.
Conclusions
- AI competitions significantly contribute to the global adoption of AI in healthcare.
- These events raise awareness of AI in medical imaging among students and professionals.
- AI competitions foster interdisciplinary collaboration, drive innovation, and enhance societal understanding of AI in healthcare.
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