Artificial Intelligence for Personalized Perioperative Medicine.

artificial intelligence in anesthesia internet of things (iot) patient's trajectories perioperative medicine transhumanism

Journal

Cureus
ISSN: 2168-8184
Titre abrégé: Cureus
Pays: United States
ID NLM: 101596737

Informations de publication

Date de publication:
Jan 2024
Historique:
accepted: 30 01 2024
medline: 4 3 2024
pubmed: 4 3 2024
entrez: 4 3 2024
Statut: epublish

Résumé

The development of artificial intelligence (AI) is disruptive and unstoppable, also in medicine. Because of the enormous quantity of data recorded during continuous monitoring and the peculiarity of our specialty where stratification and mitigation risk are some of the core aspects, anesthesiology and postoperative intensive care are fertile fields where new technologies find ample room for expansion. Recently, research efforts have focused on the development of a holistic technology that globally embraces the entire perioperative period rather than a fragmented approach where AI is developed to carry out specific tasks. This could potentially revolutionize the perioperative medicine we know today. In fact, AI will be able to expand clinician's ability to interpret, adapt, and ultimately act in a complex reality with facets that are too complex to be managed all at the same time and in a holistic manner. With the support of new tools, as healthcare professionals we have the moral obligation to govern this transition, allowing an ethical and sustainable development of these technologies and avoiding being overwhelmed by them. We should welcome this transhumanist tension which does not aim at the replacement of human capabilities or even at the integration of these but rather at the expansion of a "single intelligence".

Identifiants

pubmed: 38435870
doi: 10.7759/cureus.53270
pmc: PMC10905205
doi:

Types de publication

Editorial

Langues

eng

Pagination

e53270

Informations de copyright

Copyright © 2024, Bignami et al.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Auteurs

Elena Bignami (E)

Department of Medicine and Surgery, Anesthesiology, Critical Care and Pain Medicine Division, Azienda Ospedaliero Universitaria di Parma, Parma, ITA.

Matteo Panizzi (M)

Department of Medicine and Surgery, Anesthesiology, Critical Care and Pain Medicine Division, Azienda Ospedaliero Universitaria di Parma, Parma, ITA.

Valentina Bellini (V)

Department of Medicine and Surgery, Anesthesiology, Critical Care and Pain Medicine Division, Azienda Ospedaliero Universitaria di Parma, Parma, ITA.

Classifications MeSH