Evidence map›Paper›PMID 32335224›Full record

ArticleJournal of biomedical informatics2020

Deep phenotyping: Embracing complexity and temporality-Towards scalability, portability, and interoperability.

Chunhua Weng, Nigam H Shah, George Hripcsak

Abstract readEditorial
In one paragraph

Article in Journal of biomedical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 2 pooled it
–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

34 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  10. Deep phenotyping obesity using EHR data: Promise, Challenges, and Future Directions.medRxiv : the preprint server for health sciences · 2024
    Article
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  17. Machine learning approaches for electronic health records phenotyping: a methodical review.Journal of the American Medical Informatics Association : JAMIA · 2023
    Article
  18. Article
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  20. Review
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.

Chunhua WengDepartment of Biomedical Informatics, Columbia University, New York, NY, USA. Electronic address: chunhua@columbia.edu.
Nigam H ShahMedicine - Biomedical Informatics Research, Stanford University, Stanford, CA, USA. Electronic address: nigam@stanford.edu.
George HripcsakDepartment of Biomedical Informatics, Columbia University, New York, NY, USA. Electronic address: gh13@cumc.columbia.edu.

Funding

Clinical and Translational Science AwardUL1TR001873 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI REILLY, MUREDACH P · 2016 to 2025
$99.0M
OMOP information model for eMERGE phenotypingU01HG008680 · NHGRI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Wendy K Chung, GEORGE M HRIPCSAK · 2015 to 2026
$13.3M
DISCOVERING AND APPLYING KNOWLEDGE IN CLINICAL DATABASESR01LM006910 · NLM · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI HRIPCSAK, GEORGE M · 2000 to 2023
$10.6M
Bridging the Semantic Gap Between Research Eligibility Criteria and Clinical DataR01LM009886 · NLM · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI WENG, CHUNHUA · 2009 to 2020
$5.3M
Methods for generalized ontology terms enrichment analysisR01LM011369 · NLM · STANFORD UNIVERSITY · PI SHAH, NIGAM H · 2013 to 2020
$5.0M
Deep phenotyping in Electronic Health Records for Genomic MedicineR01LM012895 · NLM · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI WANG, KAI, WENG, CHUNHUA · 2018 to 2021
$3.3M
Deep learning based predictive analytics to improve patient health.R01LM013061 · NLM · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Krzysztof Kiryluk, CHUNHUA WENG · 2019 to 2026
$2.7M
NCATS NIH HHS UL1 TR001873NHGRI NIH HHS U01 HG008680NLM NIH HHS R01 LM006910NLM NIH HHS R01 LM009886NLM NIH HHS R01 LM011369NLM NIH HHS R01 LM012895NLM NIH HHS R01 LM013061
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Identifiers

PMID32335224
PMCPMC7179504

What OpenQuestion holds

Textmetadata
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.