Evidence map›Paper›PMID 36045824›Full record

ReviewAnnals of medicine and surgery (2012)2022

The future of Cardiothoracic surgery in Artificial intelligence.

Hassan Mumtaz, Muhammad Saqib, Farrukh Ansar, Durafshan Zargar, Madiha Hameed, Mohammad Hasan, Pakiza Muskan

Open access · diamondAbstract readReview
In one paragraph

Review in Annals of medicine and surgery (2012), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 2 pooled it
2.1field-weighted citation impact, top 12% 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, 2 syntheses or guidelines pooled it, 35 citations in OpenAlex.

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  16. Recent advances in cardiac anaesthesia.Indian journal of anaesthesia · 2023
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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

7 authors at 6 institutions in 1 country.

Hassan MumtazMaroof International Hospital, Islamabad Public Health Scholar: Health Services Academy, Islamabad, Pakistan.
Muhammad SaqibKhyber Medical College, Peshawar Hospital, Khyber Teaching Hospital, Peshawar, Pakistan.
Farrukh AnsarNorthwest School of Medicine, Peshawar, Pakistan.
Durafshan ZargarAyub Medical College, Abbottabad, Pakistan.
Madiha HameedAyub Medical College, Abbottabad, Pakistan.
Mohammad HasanJinnah Postgraduate Medical Center (JPMC), Pakistan.
Pakiza MuskanFauji Foundation University, Islamabad, Pakistan.
Ayub Medical College · PKFoundation University Islamabad · PKHealth Services Academy · PKJinnah Postgraduate Medical Center · PKKhyber Medical College · PKNorthwest General Hospital and Research Center · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Humans' great and quick technological breakthroughs in the previous decade have undoubtedly influenced how surgical procedures are executed in the operating room. AI is becoming incredibly influential for surgical decision-making to help surgeons make better projections about the implications of surgical operations by considering different sources of data such as patient health conditions, disease natural history, patient values, and finance. Although the application of artificial intelligence in healthcare settings is rapidly increasing, its mainstream application in clinical practice remains limited. The use of machine learning algorithms in thoracic surgery is extensive, including different clinical stages. By leveraging techniques such as machine learning, computer vision, and robotics, AI may play a key role in diagnostic augmentation, operative management, pre-and post-surgical patient management, and upholding safety standards. AI, particularly in complex surgical procedures such as cardiothoracic surgery, may be a significant help to surgeons in executing more intricate surgeries with greater success, fewer complications, and ensuring patient safety, while also providing resources for robust research and better dissemination of knowledge. In this paper, we present an overview of AI applications in thoracic surgery and its related components, including contemporary projects and technology that use AI in cardiothoracic surgery and general care. We also discussed the future of AI and how high-tech operating rooms will use human-machine collaboration to improve performance and patient safety, as well as its future directions and limitations. It is vital for the surgeons to keep themselves acquainted with the latest technological advancement in AI order to grasp this technology and easily integrate it into clinical practice when it becomes accessible. This review is a great addition to literature, keeping practicing and aspiring surgeons up to date on the most recent advances in AI and cardiothoracic surgery.

Identifiers

PMID36045824
PMCPMC9422274
OpenAlexW4288926427

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.