Evidence map›Paper›PMID 37908699›Full record

ReviewCureus2023

Advancements and Challenges in the Application of Artificial Intelligence in Surgical Arena: A Literature Review.

Reda H Mithany, Samana Aslam, Shenouda Abdallah, Mark Abdelmaseeh, Farid Gerges, Mohamed S Mohamed, Mina Manasseh, Andrew Wanees, M Hasaan Shahid, Mahmoud Saied Khalil and 1 more

Abstract 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 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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  10. Lessons learned in application driven imaging agent design for image-guided surgery.European journal of nuclear medicine and molecular imaging · 2024
    Review
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  18. Potential and Promise: Artificial Intelligence in Pediatric Surgery.Journal of Indian Association of Pediatric Surgeons
    Article
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

11 authors.

Reda H MithanyLaparoscopic Colorectal Surgery, Kingston Hospital National Health Service (NHS) Foundation Trust, Kingston Upon Thames, GBR.
Samana AslamGeneral Surgery, Lahore General Hospital, Lahore, PAK.
Shenouda AbdallahSurgery, Jaber Al-Ahmad Hospital, Kuwait, KWT.
Mark AbdelmaseehGeneral Surgery, Faculty of Medicine, Assuit University, Assuit, EGY.
Farid GergesGeneral and Emergency Surgery, Kingston Hospital National Health Service (NHS) Foundation Trust, Kingston Upon Thames, GBR.
Mohamed S MohamedOrthopaedics, King's College, London, GBR.
Mina ManassehGeneral Surgery, Torbay and South Devon National Health Service (NHS) Foundation Trust, Torquay, GBR.
Andrew WaneesGeneral Surgery, Dar El-Salam Hospital, Cairo, EGY.
M Hasaan ShahidSurgery, Glangwili General Hospital, Carmarthen, GBR.
Mahmoud Saied KhalilGeneral Practice, Primary Care Polyclinics, Riyadh, SAU.
Nesma DanielMedical Laboratory Science, Ain Shams Hospital, Cairo, EGY.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This literature review delves into the transformative potential of artificial intelligence (AI) in the field of surgery, exploring its evolution, applications, and technological advancements. AI, with its ability to mimic human intelligence, presents a paradigm shift in surgical practices. The review critically analyzes a broad range of research, encompassing machine learning, deep learning, natural language processing, and their diverse applications in preoperative planning, surgical simulation, intraoperative guidance, and postoperative analysis. Ethical, legal, and regulatory considerations, as well as challenges and future directions, are also explored. The study underscores AI's ability to revolutionize surgical visualization and its role in shaping the future of healthcare.

Indexed as

ai and machine learningartificial intelligenceartificial intelligence and robotics in healthcareartificial intelligence educationrobotic-assisted surgery

Identifiers

PMID37908699
PMCPMC10613559

What OpenQuestion holds

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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.