Optimising artificial intelligence ultrasound tools in anaesthesiology and perioperative medicine: The next frontier for advanced technology application
Artificial intelligence (AI) was once considered avant-garde. However, AI permeates every industry today, impacting work and home lives in many ways. While AI-driven diagnostic and therapeutic applications already exist in medicine, a chasm remains between the potential of AI and its clinical applic...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wolters Kluwer Medknow Publications
2024-11-01
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| Series: | Indian Journal of Anaesthesia |
| Subjects: | |
| Online Access: | https://journals.lww.com/10.4103/ija.ija_578_24 |
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| author | Anastasia Jones Ryan Tang Anahita Dabo-Trubelja Cindy B. Yeoh Leshawn Richards Vijaya Gottumukkala |
| author_facet | Anastasia Jones Ryan Tang Anahita Dabo-Trubelja Cindy B. Yeoh Leshawn Richards Vijaya Gottumukkala |
| author_sort | Anastasia Jones |
| collection | DOAJ |
| description | Artificial intelligence (AI) was once considered avant-garde. However, AI permeates every industry today, impacting work and home lives in many ways. While AI-driven diagnostic and therapeutic applications already exist in medicine, a chasm remains between the potential of AI and its clinical applications. This article reviews the status of AI-powered ultrasound (US) applications in anaesthesiology and perioperative medicine. A literature search was performed for studies examining AI applications in perioperative US. AI applications for echocardiography and regional anaesthesia are the most robust and well-developed. While applications are available for lung imaging and vascular access, AI programs for airway and gastric US imaging solutions have yet to be available. Legal and ethical challenges associated with AI applications need to be addressed and resolved over time. AI applications are beneficial in the context of education and training. While low-resource settings may benefit from AI, the financial burden is a considerable limiting factor. |
| format | Article |
| id | doaj-art-eb6c425a54f34f8090951b6ed12656ed |
| institution | Kabale University |
| issn | 0019-5049 0976-2817 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Wolters Kluwer Medknow Publications |
| record_format | Article |
| series | Indian Journal of Anaesthesia |
| spelling | doaj-art-eb6c425a54f34f8090951b6ed12656ed2025-01-24T15:14:01ZengWolters Kluwer Medknow PublicationsIndian Journal of Anaesthesia0019-50490976-28172024-11-0168111016102110.4103/ija.ija_578_24Optimising artificial intelligence ultrasound tools in anaesthesiology and perioperative medicine: The next frontier for advanced technology applicationAnastasia JonesRyan TangAnahita Dabo-TrubeljaCindy B. YeohLeshawn RichardsVijaya GottumukkalaArtificial intelligence (AI) was once considered avant-garde. However, AI permeates every industry today, impacting work and home lives in many ways. While AI-driven diagnostic and therapeutic applications already exist in medicine, a chasm remains between the potential of AI and its clinical applications. This article reviews the status of AI-powered ultrasound (US) applications in anaesthesiology and perioperative medicine. A literature search was performed for studies examining AI applications in perioperative US. AI applications for echocardiography and regional anaesthesia are the most robust and well-developed. While applications are available for lung imaging and vascular access, AI programs for airway and gastric US imaging solutions have yet to be available. Legal and ethical challenges associated with AI applications need to be addressed and resolved over time. AI applications are beneficial in the context of education and training. While low-resource settings may benefit from AI, the financial burden is a considerable limiting factor.https://journals.lww.com/10.4103/ija.ija_578_24anaesthesiologyartificial intelligencemachine learningmedicationmonitoringperioperative medicinepoint-of-care ultrasoundregional anaesthesia |
| spellingShingle | Anastasia Jones Ryan Tang Anahita Dabo-Trubelja Cindy B. Yeoh Leshawn Richards Vijaya Gottumukkala Optimising artificial intelligence ultrasound tools in anaesthesiology and perioperative medicine: The next frontier for advanced technology application Indian Journal of Anaesthesia anaesthesiology artificial intelligence machine learning medication monitoring perioperative medicine point-of-care ultrasound regional anaesthesia |
| title | Optimising artificial intelligence ultrasound tools in anaesthesiology and perioperative medicine: The next frontier for advanced technology application |
| title_full | Optimising artificial intelligence ultrasound tools in anaesthesiology and perioperative medicine: The next frontier for advanced technology application |
| title_fullStr | Optimising artificial intelligence ultrasound tools in anaesthesiology and perioperative medicine: The next frontier for advanced technology application |
| title_full_unstemmed | Optimising artificial intelligence ultrasound tools in anaesthesiology and perioperative medicine: The next frontier for advanced technology application |
| title_short | Optimising artificial intelligence ultrasound tools in anaesthesiology and perioperative medicine: The next frontier for advanced technology application |
| title_sort | optimising artificial intelligence ultrasound tools in anaesthesiology and perioperative medicine the next frontier for advanced technology application |
| topic | anaesthesiology artificial intelligence machine learning medication monitoring perioperative medicine point-of-care ultrasound regional anaesthesia |
| url | https://journals.lww.com/10.4103/ija.ija_578_24 |
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