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Artificial Intelligence-Driven Image and Data Analytics in Anesthesia
Firoozeh Madadi1, Zeinab Kohzadi2, Shahabedin Rahmatizadeh3
1Department of Anesthesiology, School of Medicine, Anesthesiology Research Center, Ayatollah Taleghani Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Abstract:
Artificial intelligence (AI) is transforming medical image analysis by enhancing accuracy, efficiency, and diagnostic precision through technologies like deep learning, convolutional neural networks, and supporter vector machines. AI aids disease detection, image segmentation, and integrates imaging with clinical data to personalize treatment. In anesthesia, AI supports point-of-care ultrasound, improving regional block procedures and clinician training via tools like ScanNav and Accuro. Challenges include limited clinical validation, regulatory issues, and model generalizability. AI-driven systems show potential for standardizing practice, improving patient safety, and assisting novice practitioners, but it must be ethically integrated and guided by expert clinical judgment for successful adoption.
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