ReviewYearbook of medical informatics2021
Year 2020 (with COVID): Observation of Scientific Literature on Clinical Natural Language Processing.
Review in Yearbook of medical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Exploring the Latest Highlights in Medical Natural Language Processing across Multiple Languages: A Survey.Yearbook of medical informatics · 2023Article
- The Role of Natural Language Processing during the COVID-19 Pandemic: Health Applications, Opportunities, and Challenges.Healthcare (Basel, Switzerland) · 2022Review
- Health Data, Information, and Knowledge Sharing for Addressing the COVID-19.Yearbook of medical informatics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo analyze the content of publications within the medical NLP domain in 2020.
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 in 2020. We also propose an analysis of the content of the NLP publications in 2020, all topics included.
conclusionThe two main issues addressed in 2020 are related to the investigation of COVID-related questions and to the further adaptation and use of transformer models. Besides, the trends from the past years continue, such as diversification of languages processed and use of information from social networks.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.