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Artificial intelligence in perioperative management of major gastrointestinal surgeries

Artificial intelligence (AI) demonstrated by machines is based on reinforcement learning and revolves around the usage of algorithms. The purpose of this review was to summarize concepts, the scope, applications, and limitations in major gastrointestinal surgery. This is a narrative review of the av...

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Autores principales: Solanki, Sohan Lal, Pandrowala, Saneya, Nayak, Abhirup, Bhandare, Manish, Ambulkar, Reshma P, Shrikhande, Shailesh V
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8173379/
https://www.ncbi.nlm.nih.gov/pubmed/34135552
http://dx.doi.org/10.3748/wjg.v27.i21.2758
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author Solanki, Sohan Lal
Pandrowala, Saneya
Nayak, Abhirup
Bhandare, Manish
Ambulkar, Reshma P
Shrikhande, Shailesh V
author_facet Solanki, Sohan Lal
Pandrowala, Saneya
Nayak, Abhirup
Bhandare, Manish
Ambulkar, Reshma P
Shrikhande, Shailesh V
author_sort Solanki, Sohan Lal
collection PubMed
description Artificial intelligence (AI) demonstrated by machines is based on reinforcement learning and revolves around the usage of algorithms. The purpose of this review was to summarize concepts, the scope, applications, and limitations in major gastrointestinal surgery. This is a narrative review of the available literature on the key capabilities of AI to help anesthesiologists, surgeons, and other physicians to understand and critically evaluate ongoing and new AI applications in perioperative management. AI uses available databases called “big data” to formulate an algorithm. Analysis of other data based on these algorithms can help in early diagnosis, accurate risk assessment, intraoperative management, automated drug delivery, predicting anesthesia and surgical complications and postoperative outcomes and can thus lead to effective perioperative management as well as to reduce the cost of treatment. Perioperative physicians, anesthesiologists, and surgeons are well-positioned to help integrate AI into modern surgical practice. We all need to partner and collaborate with data scientists to collect and analyze data across all phases of perioperative care to provide clinical scenarios and context. Careful implementation and use of AI along with real-time human interpretation will revolutionize perioperative care, and is the way forward in future perioperative management of major surgery.
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spelling pubmed-81733792021-06-15 Artificial intelligence in perioperative management of major gastrointestinal surgeries Solanki, Sohan Lal Pandrowala, Saneya Nayak, Abhirup Bhandare, Manish Ambulkar, Reshma P Shrikhande, Shailesh V World J Gastroenterol Minireviews Artificial intelligence (AI) demonstrated by machines is based on reinforcement learning and revolves around the usage of algorithms. The purpose of this review was to summarize concepts, the scope, applications, and limitations in major gastrointestinal surgery. This is a narrative review of the available literature on the key capabilities of AI to help anesthesiologists, surgeons, and other physicians to understand and critically evaluate ongoing and new AI applications in perioperative management. AI uses available databases called “big data” to formulate an algorithm. Analysis of other data based on these algorithms can help in early diagnosis, accurate risk assessment, intraoperative management, automated drug delivery, predicting anesthesia and surgical complications and postoperative outcomes and can thus lead to effective perioperative management as well as to reduce the cost of treatment. Perioperative physicians, anesthesiologists, and surgeons are well-positioned to help integrate AI into modern surgical practice. We all need to partner and collaborate with data scientists to collect and analyze data across all phases of perioperative care to provide clinical scenarios and context. Careful implementation and use of AI along with real-time human interpretation will revolutionize perioperative care, and is the way forward in future perioperative management of major surgery. Baishideng Publishing Group Inc 2021-06-07 2021-06-07 /pmc/articles/PMC8173379/ /pubmed/34135552 http://dx.doi.org/10.3748/wjg.v27.i21.2758 Text en ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
spellingShingle Minireviews
Solanki, Sohan Lal
Pandrowala, Saneya
Nayak, Abhirup
Bhandare, Manish
Ambulkar, Reshma P
Shrikhande, Shailesh V
Artificial intelligence in perioperative management of major gastrointestinal surgeries
title Artificial intelligence in perioperative management of major gastrointestinal surgeries
title_full Artificial intelligence in perioperative management of major gastrointestinal surgeries
title_fullStr Artificial intelligence in perioperative management of major gastrointestinal surgeries
title_full_unstemmed Artificial intelligence in perioperative management of major gastrointestinal surgeries
title_short Artificial intelligence in perioperative management of major gastrointestinal surgeries
title_sort artificial intelligence in perioperative management of major gastrointestinal surgeries
topic Minireviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8173379/
https://www.ncbi.nlm.nih.gov/pubmed/34135552
http://dx.doi.org/10.3748/wjg.v27.i21.2758
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