Evidence map›Paper›PMID 29295162›Full record

ArticleStudies in health technology and informatics2017

Phenotypic Analysis of Clinical Narratives Using Human Phenotype Ontology.

Feichen Shen, Liwei Wang, Hongfang Liu

Abstract read
In one paragraph

Article in Studies in health technology and informatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Computational analysis of 10,860 phenotypic annotations in individuals with SCN2A-related disorders.Genetics in medicine : official journal of the American College of Medical Genetics · 2021
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Rare disease knowledge enrichment through a data-driven approach.BMC medical informatics and decision making · 2019
    Article
  10. Clinical genome sequencing in an unbiased pediatric cohort.Genetics in medicine : official journal of the American College of Medical Genetics · 2019
    Article
  11. Article
  12. Article
  13. 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.

Feichen ShenDepartment of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
Liwei WangDepartment of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
Hongfang LiuDepartment of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.

Funding

Biomedical Data Translator Technical Feasibility Assessment and Architecture DesignOT3TR002019 · NCATS · JOHNS HOPKINS UNIVERSITY · PI CHUTE, CHRISTOPHER G, HAENDEL, MELISSA A · 2016 to 2019
$5.7M
NCATS NIH HHS OT3 TR002019
6 · The paper itself

Abstract

Phenotypes are defined as observable characteristics and clinical traits of diseases and organisms. As connectors between medical experimental findings and clinical practices, phenotypes play vital roles in translational medicine. To facilitate the translation between genotype and phenotype, Human Phenotype Ontology (HPO) was developed as a semantically computable vocabulary to capture phenotypic abnormalities found in human diseases discovered through biomedical research. The use of HPO in annotating phenotypic information in clinical practice remains unexplored. In this study, we investigated the use of HPO to annotate phenotypic information in clinical domain by leveraging a corpus of 12.8 million clinical notes created from 2010 to 2015 for 729 thousand patients at Mayo Clinic Rochester campus and assessed the distribution information of HPO terms in the corpus. We also analyzed the distributional difference of HPO terms among demographic groups. We further demonstrated the potential application of the annotated corpus to support knowledge discovery in precision medicine through Wilson's Disease.

Indexed as

GenotypeNarrationPhenotypePrecision MedicineHumansTranslational Research, BiomedicalHuman Phenotype OntologyPhenotypic AnalysisSemantic Annotation

Identifiers

PMID29295162
PMCPMC7466871

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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.