Artificial Intelligence-Driven Image and Data Analytics in Anesthesia.
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| Názov: | Artificial Intelligence-Driven Image and Data Analytics in Anesthesia. |
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| Autori: | Madadi F; Department of Anesthesiology, School of Medicine, Anesthesiology Research Center, Ayatollah Taleghani Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran., Kohzadi Z; Department of Health Information Technology and Management, School of Allied Medical Sciences, Studen Research Committee, Shahid Beheshti University of Medical Sciences, Tehran, Iran., Rahmatizadeh S; Department of Health Information Management, School of Allied Medical Sciences, Anesthesiology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran., Sabouri AS; Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA., Dabbagh A; Department of Anesthesiology, School of Medicine, Anesthesiology Research Center, Shahid Modarres Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Electronic address: alidabbagh@yahoo.com. |
| Zdroj: | Anesthesiology clinics [Anesthesiol Clin] 2025 Sep; Vol. 43 (3S), pp. e1-e15. Date of Electronic Publication: 2025 Aug 12. |
| Spôsob vydávania: | Journal Article; Review |
| Jazyk: | English |
| Informácie o časopise: | Publisher: Saunders Country of Publication: United States NLM ID: 101273663 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1932-2275 (Print) Linking ISSN: 19322275 NLM ISO Abbreviation: Anesthesiol Clin Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Philadelphia : Saunders, c2006- |
| Výrazy zo slovníka MeSH: | Artificial Intelligence* , Anesthesia*/methods , Anesthesiology*/methods , Image Processing, Computer-Assisted*/methods , Data Science*, Humans ; Data Analysis ; Deep Learning ; Data Analytics |
| Abstrakt: | 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. (Copyright © 2025 Elsevier Inc. All rights reserved.) |
| Contributed Indexing: | Keywords: Artificial intelligence (AI); Clinical decision support; Deep learning (DL); Medical image analysis; Ultrasound-guided regional anesthesia (UGRA) |
| Entry Date(s): | Date Created: 20250925 Date Completed: 20250925 Latest Revision: 20250925 |
| Update Code: | 20250926 |
| DOI: | 10.1016/j.anclin.2025.07.001 |
| PMID: | 40998491 |
| Databáza: | MEDLINE |
Nájsť tento článok vo Web of Science | Abstrakt: | 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.<br /> (Copyright © 2025 Elsevier Inc. All rights reserved.) |
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| ISSN: | 1932-2275 |
| DOI: | 10.1016/j.anclin.2025.07.001 |