Role of artificial intelligence in haemodynamic monitoring
This narrative review explores the evolving role of artificial intelligence (AI) in haemodynamic monitoring, emphasising its potential to revolutionise patient care. The historical reliance on invasive procedures for haemodynamic assessments is contrasted with the emerging non-invasive AI-driven app...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wolters Kluwer Medknow Publications
2024-01-01
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| Series: | Indian Journal of Anaesthesia |
| Subjects: | |
| Online Access: | http://www.ijaweb.org/article.asp?issn=0019-5049;year=2024;volume=68;issue=1;spage=93;epage=99;aulast=Myatra |
| _version_ | 1797225830852591616 |
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| author | Sheila N Myatra Bharat G Jagiasi Neeraj P Singh Jigeeshu V Divatia |
| author_facet | Sheila N Myatra Bharat G Jagiasi Neeraj P Singh Jigeeshu V Divatia |
| author_sort | Sheila N Myatra |
| collection | DOAJ |
| description | This narrative review explores the evolving role of artificial intelligence (AI) in haemodynamic monitoring, emphasising its potential to revolutionise patient care. The historical reliance on invasive procedures for haemodynamic assessments is contrasted with the emerging non-invasive AI-driven approaches that address limitations and risks associated with traditional methods. Developing the hypotension prediction index and introducing CircEWSTM and CircEWS-lite TM showcase AI's effectiveness in predicting and managing circulatory failure. The crucial aspects include the balance between AI and healthcare professionals, ethical considerations, and the need for regulatory frameworks. The use of AI in haemodynamic monitoring will keep growing with ongoing research, better technology, and teamwork. As we navigate these advancements, it is crucial to balance AI's power and healthcare professionals' essential role. Clinicians must continue to use their clinical acumen to ensure that patient outliers or system problems do not compromise the treatment of the condition and patient safety. |
| first_indexed | 2024-03-07T21:35:43Z |
| format | Article |
| id | doaj.art-87aad3e7b1c54c4a914a9fda053a0172 |
| institution | Directory Open Access Journal |
| issn | 0019-5049 0976-2817 |
| language | English |
| last_indexed | 2024-04-24T14:15:15Z |
| publishDate | 2024-01-01 |
| publisher | Wolters Kluwer Medknow Publications |
| record_format | Article |
| series | Indian Journal of Anaesthesia |
| spelling | doaj.art-87aad3e7b1c54c4a914a9fda053a01722024-04-03T08:48:33ZengWolters Kluwer Medknow PublicationsIndian Journal of Anaesthesia0019-50490976-28172024-01-01681939910.4103/ija.ija_1260_23Role of artificial intelligence in haemodynamic monitoringSheila N MyatraBharat G JagiasiNeeraj P SinghJigeeshu V DivatiaThis narrative review explores the evolving role of artificial intelligence (AI) in haemodynamic monitoring, emphasising its potential to revolutionise patient care. The historical reliance on invasive procedures for haemodynamic assessments is contrasted with the emerging non-invasive AI-driven approaches that address limitations and risks associated with traditional methods. Developing the hypotension prediction index and introducing CircEWSTM and CircEWS-lite TM showcase AI's effectiveness in predicting and managing circulatory failure. The crucial aspects include the balance between AI and healthcare professionals, ethical considerations, and the need for regulatory frameworks. The use of AI in haemodynamic monitoring will keep growing with ongoing research, better technology, and teamwork. As we navigate these advancements, it is crucial to balance AI's power and healthcare professionals' essential role. Clinicians must continue to use their clinical acumen to ensure that patient outliers or system problems do not compromise the treatment of the condition and patient safety.http://www.ijaweb.org/article.asp?issn=0019-5049;year=2024;volume=68;issue=1;spage=93;epage=99;aulast=Myatraartificial intelligenceearly warning signshaemodynamic monitoringhypotension prediction indexmachine learning |
| spellingShingle | Sheila N Myatra Bharat G Jagiasi Neeraj P Singh Jigeeshu V Divatia Role of artificial intelligence in haemodynamic monitoring Indian Journal of Anaesthesia artificial intelligence early warning signs haemodynamic monitoring hypotension prediction index machine learning |
| title | Role of artificial intelligence in haemodynamic monitoring |
| title_full | Role of artificial intelligence in haemodynamic monitoring |
| title_fullStr | Role of artificial intelligence in haemodynamic monitoring |
| title_full_unstemmed | Role of artificial intelligence in haemodynamic monitoring |
| title_short | Role of artificial intelligence in haemodynamic monitoring |
| title_sort | role of artificial intelligence in haemodynamic monitoring |
| topic | artificial intelligence early warning signs haemodynamic monitoring hypotension prediction index machine learning |
| url | http://www.ijaweb.org/article.asp?issn=0019-5049;year=2024;volume=68;issue=1;spage=93;epage=99;aulast=Myatra |
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