Evidence map›Paper›PMID 37822918›Full record

ReviewEJVES vascular forum2023

Comprehensive Review of Natural Language Processing (NLP) in Vascular Surgery.

Fabien Lareyre, Bahaa Nasr, Arindam Chaudhuri, Gilles Di Lorenzo, Mathieu Carlier, Juliette Raffort

Abstract readReview
In one paragraph

Review in EJVES vascular forum, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  7. Review
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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

6 authors.

Fabien LareyreDepartment of Vascular Surgery, Hospital of Antibes Juan-les-Pins, France.
Bahaa NasrDepartment of Vascular and Endovascular Surgery, Brest University Hospital, Brest, France.
Arindam ChaudhuriBedfordshire - Milton Keynes Vascular Centre, Bedfordshire Hospitals, NHS Foundation Trust, Bedford, UK.
Gilles Di LorenzoDepartment of Vascular Surgery, Hospital of Antibes Juan-les-Pins, France.
Mathieu CarlierDepartment of Urology, University Hospital of Nice, Nice, France.
Juliette RaffortUniversité Côte d'Azur, Inserm, U1065, C3M, Nice, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The use of Natural Language Processing (NLP) has attracted increased interest in healthcare with various potential applications including identification and extraction of health information, development of chatbots and virtual assistants. The aim of this comprehensive literature review was to provide an overview of NLP applications in vascular surgery, identify current limitations, and discuss future perspectives in the field. Data sources: The MEDLINE database was searched on April 2023. Review methods: The database was searched using a combination of keywords to identify studies reporting the use of NLP and chatbots in three main vascular diseases. Keywords used included Natural Language Processing, chatbot, chatGPT, aortic disease, carotid, peripheral artery disease, vascular, and vascular surgery. Results: Given the heterogeneity of study design, techniques, and aims, a comprehensive literature review was performed to provide an overview of NLP applications in vascular surgery. By enabling identification and extraction of information on patients with vascular diseases, such technology could help to analyse data from healthcare information systems to provide feedback on current practice and help in optimising patient care. In addition, chatbots and NLP driven techniques have the potential to be used as virtual assistants for both health professionals and patients. Conclusion: While Artificial Intelligence and NLP technology could be used to enhance care for patients with vascular diseases, many challenges remain including the need to define guidelines and clear consensus on how to evaluate and validate these innovations before their implementation into clinical practice.

Indexed as

Artificial IntelligenceLiterature searchNatural Language ProcessingVascular surgery

Identifiers

PMID37822918
PMCPMC10562666

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.