Evidence map›Paper›PMID 38147866›Full record

ArticleYearbook of medical informatics2023

Year 2022 in Medical Natural Language Processing: Availability of Language Models as a Step in the Democratization of NLP in the Biomedical Area.

Cyril Grouin, Natalia Grabar, Section Editors for the IMIA Yearbook Section on Natural Language Processing

Abstract read
In one paragraph

Article in Yearbook of medical informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Informatics for One Health.Yearbook of medical informatics · 2023
    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

3 authors.

Cyril GrouinUniversité Paris Saclay, CNRS, Laboratoire Interdisciplinaire des Sciences du Numérique, 91400 Orsay, France.
Natalia GrabarUMR8163 STL, CNRS, Université de Lille, Domaine du Pont-de-bois, 59653 Villeneuve-d'Ascq cedex, France.
Section Editors for the IMIA Yearbook Section on Natural Language Processing

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo analyse the content of publications within the medical Natural Language Processing (NLP) domain in 2022.

methodsAutomatic and manual preselection of publications to be reviewed, and selection of the best NLP papers of the year. Analysis of the important issues.

resultsThree best papers have been selected. We also propose an analysis of the content of the NLP publications in 2022, stressing on some of the topics.

conclusionThe main trend in 2022 is certainly related to the availability of large language models, especially those based on Transformers, and to their use by non-NLP researchers. This leads to the democratization of the NLP methods. We also observe the renewal of interest to languages other than English, the continuation of research on information extraction and prediction, the massive use of data from social media, and the consideration of needs and interests of patients.

Indexed as

Information Storage and RetrievalNatural Language ProcessingHumans

Identifiers

PMID38147866
PMCPMC10751107

What OpenQuestion 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 OpenQuestion graph.