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4 October 2024 Practical considerations for AI in medical imaging: tool development and validation
Lubomir M. Hadjiiski
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Proceedings Volume PC13118, Emerging Topics in Artificial Intelligence (ETAI) 2024; PC131180M (2024) https://doi.org/10.1117/12.3031759
Event: Nanoscience + Engineering, 2024, San Diego, California, United States
Abstract
Rapid advances in artificial intelligence (AI) and machine learning have enabled rapid development of decision support tools for application in broad health care areas. Many of the AI systems target medical imaging applications. The availability of public datasets additionally stimulated the advancement of the medical AI systems and the ability of research groups to contribute to the field. In-house AI system development is crucial for exploring new ideas, and new research directions and applications which strongly contribute to the generation of fundamental knowledge by a broad research community in broad clinical areas. Number of in-house computer-aided AI decision support applications will be presented. It is essential to properly train and rigorously validate a clinical decision support tool and verify its generalizability and reliability prior to translation for patient care in the clinic. Best practices for the development and performance assessment of computer-aided AI decision support systems will be discussed.
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Lubomir M. Hadjiiski "Practical considerations for AI in medical imaging: tool development and validation", Proc. SPIE PC13118, Emerging Topics in Artificial Intelligence (ETAI) 2024, PC131180M (4 October 2024); https://doi.org/10.1117/12.3031759
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KEYWORDS
Artificial intelligence
Standards development
Medical imaging
Biomedical applications
Reliability
Solid modeling
Systems modeling
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