Evidence map›Paper›PMID 38174199›Full record

ReviewCureus2023

Revolutionizing Patient Care: A Comprehensive Review of Artificial Intelligence Applications in Anesthesia.

Amol Singam

Open access · diamondAbstract readReview
In one paragraph

Review in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
7.2field-weighted citation impact, top 2% of its field
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

17 citing papers in PubMed, 33 citations in OpenAlex.

  1. Advances in Remote Monitoring Technology Applications in Anesthesia: A Narrative Review.Medical science monitor : international medical journal of experimental and clinical research · 2026
    Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Reshaping Anesthesia with Artificial Intelligence: From Concept to Reality.Anesthesia and critical care (Houston, Tex.) · 2025
    Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. Review
  15. Scope of artificial intelligence in airway management.Indian journal of anaesthesia · 2024
    Article
  16. Article
  17. 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

1 author at 1 institution in 1 country.

Amol SingamCritical Care Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND.
Jawaharlal Nehru Medical College · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review explores the intersection of artificial intelligence (AI) and anesthesia, examining its transformative impact on patient care across various phases. Beginning with a historical overview of anesthesia, we highlight the critical role of technological advancements in ensuring optimal patient outcomes. The emergence of AI in healthcare sets the stage for a comprehensive analysis of its applications in anesthesia. In the preoperative phase, AI facilitates personalized risk assessments and decision support, optimizing anesthesia planning and drug dosage predictions. Moving to the intraoperative phase, we delve into AI's role in monitoring and control through sophisticated anesthesia monitoring and closed-loop systems. Additionally, we discuss the integration of robotics and AI-guided procedures, revolutionizing surgical assistance. Transitioning to the postoperative phase, we explore AI-driven postoperative monitoring, predictive analysis for complications, and the integration of AI into rehabilitation programs and long-term follow-up. These new applications redefine patient recovery, emphasizing personalized care and proactive interventions. However, the integration of AI in anesthesia poses challenges and ethical considerations. Data security, interpretability, and bias in AI algorithms demand scrutiny. Moreover, the evolving patient-doctor relationship in an AI-driven care landscape requires a delicate balance between efficiency and human touch. Looking forward, we discuss the future directions of AI in anesthesia, anticipating advances in technology and AI algorithms. The integration of AI into routine clinical practice and its potential impact on anesthesia education and training are explored, emphasizing the need for collaboration, education, and ethical guidelines. This review provides a comprehensive overview of AI applications in anesthesia, offering insights into the present landscape, challenges, and future directions. The synthesis of historical perspectives, current applications, and future possibilities underscores the transformative potential of AI in revolutionizing patient care within the dynamic field of anesthesia.

Indexed as

anesthesia monitoringartificial intelligence in anesthesiaethical considerationsfuture healthcare technologiespatient careprecision medicine

Identifiers

PMID38174199
PMCPMC10762564
OpenAlexW4389326765

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.