Evidence map›Paper›PMID 38435870›Full record

ArticleCureus2024

Artificial Intelligence for Personalized Perioperative Medicine.

Elena Bignami, Matteo Panizzi, Valentina Bellini

Abstract readEditorial
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Advances in telemedicine implementation for preoperative assessment: a call to action.Journal of anesthesia, analgesia and critical care · 2024
    Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Elena BignamiDepartment of Medicine and Surgery, Anesthesiology, Critical Care and Pain Medicine Division, Azienda Ospedaliero Universitaria di Parma, Parma, ITA.
Matteo PanizziDepartment of Medicine and Surgery, Anesthesiology, Critical Care and Pain Medicine Division, Azienda Ospedaliero Universitaria di Parma, Parma, ITA.
Valentina BelliniDepartment of Medicine and Surgery, Anesthesiology, Critical Care and Pain Medicine Division, Azienda Ospedaliero Universitaria di Parma, Parma, ITA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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".

Indexed as

artificial intelligence in anesthesiainternet of things (iot)patient's trajectoriesperioperative medicinetranshumanism

Identifiers

PMID38435870
PMCPMC10905205

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.