Evidence map›Paper›PMID 37128366›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2022

Automated Identification of Missing IS-A Relations in the Human Phenotype Ontology.

Maryamsadat Mohtashamian, Ran Hu, Rashmie Abeysinghe, Xubing Hao, Hua Xu, Licong Cui

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2022. 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. An Automated Approach for Identifying Erroneous IS-A Relations in SNOMED CT.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024
    Article
  2. 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

6 authors.

Maryamsadat MohtashamianSchool of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX.
Ran HuSchool of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX.
Rashmie AbeysingheDepartment of Neurology, The University of Texas Health Science Center at Houston, Houston, TX.
Xubing HaoSchool of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX.
Hua XuSchool of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX.
Licong CuiSchool of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX.

Funding

TRiPOD: Toward Reusable Phenotypes in Observational Data for AD/ADRD - managing definitions and correcting biasR01AG073435 · NIA · UNIVERSITY OF PENNSYLVANIA · PI CHEN, YONG, XU, HUA · 2021 to 2025
$3.9M
Biomedical Terminology Quality Assurance for Enhancing Clinical Queries over Electronic Health RecordsR01LM013335 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI CUI, LICONG · 2020 to 2021
$663k
NIA NIH HHS R01 AG073435NLM NIH HHS R01 LM013335
6 · The paper itself

Abstract

Auditing the Human Phenotype Ontology (HPO) is necessary to provide accurate terminology for its use in clinical research. We investigate an approach leveraging the lexical features of concepts in HPO to identify missing IS-A relations among HPO concepts. We first model the names of HPO concepts as sets of words in lower case. Then, we generate two types of concept-pairs which have at least a single common word: (1) Linked concept-pairs generated from concept-pairs having an IS-A relation; (2) Unlinked concept-pairs generated from concept-pairs without an IS- A relation. Concept-pairs generate Derived Term Pairs (DTPs) emphasizing unique lexical information of each concept. If a linked concept-pair and an unlinked concept-pair generate the same DTP, then we suggest a potential missing IS-A relation among the unlinked concept-pair. Applying our approach to the 2022-02-14 release of HPO, we uncovered 2,516 potential missing IS-A relations in HPO. We validated 59 missing IS-A relations leveraging the Unified Medical Language System (UMLS) by mapping the concept-pair to UMLS concepts and verifying whether UMLS records an IS-A relation between the pair of concepts.

Indexed as

Unified Medical Language SystemHumansPhenotype

Identifiers

PMID37128366
PMCPMC10148310

What OpenQuestion holds

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Registered trials

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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.