Evidence map›Paper›PMID 34409286›Full record

ArticleFrontiers in artificial intelligence2021

DICE: A Drug Indication Classification and Encyclopedia for AI-Based Indication Extraction.

Arjun Bhatt, Ruth Roberts, Xi Chen, Ting Li, Skylar Connor, Qais Hatim, Mike Mikailov, Weida Tong, Zhichao Liu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in artificial intelligence, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Knowledge-guided generative artificial intelligence for automated taxonomy learning from drug labels.Journal of the American Medical Informatics Association : JAMIA · 2024
    Article
  3. Article
  4. 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

9 authors.

Arjun BhattDivision of Bioinformatics & Biostatistics, National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, United States.
Ruth RobertsApconiX Ltd, Alderley Edge, United Kingdom.
Xi ChenDivision of Bioinformatics & Biostatistics, National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, United States.
Ting LiDivision of Bioinformatics & Biostatistics, National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, United States.
Skylar ConnorDivision of Bioinformatics & Biostatistics, National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, United States.
Qais HatimOffice of Translational Sciences, Center for Drug Evaluation and Research, US FDA, Silver Spring, MD, United States.
Mike MikailovOffice of Science and Engineering Labs, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD, United States.
Weida TongDivision of Bioinformatics & Biostatistics, National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, United States.
Zhichao LiuDivision of Bioinformatics & Biostatistics, National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug labeling contains an 'INDICATIONS AND USAGE' that provides vital information to support clinical decision making and regulatory management. Effective extraction of drug indication information from free-text based resources could facilitate drug repositioning projects and help collect real-world evidence in support of secondary use of approved medicines. To enable AI-powered language models for the extraction of drug indication information, we used manual reading and curation to develop a

Indexed as

artificial intelligencedeep learningdrug indicationnatural language processingtransformers

Identifiers

PMID34409286
PMCPMC8366025

What OpenQuestion holds

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LicenceCC BY
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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.