Evidence map›Paper›PMID 35910476›Full record

ReviewFrontiers in surgery2022

Natural language processing in low back pain and spine diseases: A systematic review.

Luca Bacco, Fabrizio Russo, Luca Ambrosio, Federico D'Antoni, Luca Vollero, Gianluca Vadalà, Felice Dell'Orletta, Mario Merone, Rocco Papalia, Vincenzo Denaro

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

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

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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

10 authors.

Luca BaccoDepartment of Engineering, Unit of Computer Systems and Bioinformatics, Campus Bio-Medico University of Rome, Rome, Italy.
Fabrizio RussoDepartment of Orthopaedic and Trauma Surgery, Campus Bio-Medico University Hospital Foundation, Rome, Italy.
Luca AmbrosioResearch Unit of Orthopaedic and Trauma Surgery, Campus Bio-Medico University of Rome, Rome, Italy.
Federico D'AntoniDepartment of Engineering, Unit of Computer Systems and Bioinformatics, Campus Bio-Medico University of Rome, Rome, Italy.
Luca VolleroDepartment of Engineering, Unit of Computer Systems and Bioinformatics, Campus Bio-Medico University of Rome, Rome, Italy.
Gianluca VadalàDepartment of Orthopaedic and Trauma Surgery, Campus Bio-Medico University Hospital Foundation, Rome, Italy.
Felice Dell'OrlettaItaliaNLP Lab, National Research Council, Istituto di Linguistica Computazionale "Antonio Zampolli", Pisa, Italy.
Mario MeroneDepartment of Engineering, Unit of Computer Systems and Bioinformatics, Campus Bio-Medico University of Rome, Rome, Italy.
Rocco PapaliaDepartment of Orthopaedic and Trauma Surgery, Campus Bio-Medico University Hospital Foundation, Rome, Italy.
Vincenzo DenaroDepartment of Orthopaedic and Trauma Surgery, Campus Bio-Medico University Hospital Foundation, Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Natural Language Processing (NLP) is a discipline at the intersection between Computer Science (CS), Artificial Intelligence (AI), and Linguistics that leverages unstructured human-interpretable (natural) language text. In recent years, it gained momentum also in health-related applications and research. Although preliminary, studies concerning Low Back Pain (LBP) and other related spine disorders with relevant applications of NLP methodologies have been reported in the literature over the last few years. It motivated us to systematically review the literature comprised of two major public databases, PubMed and Scopus. To do so, we first formulated our research question following the PICO guidelines. Then, we followed a PRISMA-like protocol by performing a search query including terminologies of both technical (e.g.,

Indexed as

artificial intelligencedeep learninglow back painnatural language processingspine disorderssystematic review

Identifiers

PMID35910476
PMCPMC9329654

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.