ArticleTransactions of the American Clinical and Climatological Association2023
CLINICAL HETEROGENEITY IN THE AGE OF BIG DATA, ADVANCED ANALYTICS, AND COMPLEXITY THEORY.
David Herrington, Yue Wang
Abstract read
In one paragraphArticle in Transactions of the American Clinical and Climatological Association, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
2 authors.
David HerringtonWinston-Salem, North Carolina.
Yue WangWinston-Salem, North Carolina.
Funding
UCLA Clinical Translational Science InstituteUL1TR001881 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ARLEEN F. BROWN, ARASH NAEIM · 2016 to 2026
$118.1MInstitute for Clinical and Translational ResearchUL1TR001079 · NCATS · JOHNS HOPKINS UNIVERSITY · PI FORD, DANIEL ERNEST · 2013 to 2017
$60.1MTransgenic & Knock-out MouseP30DK063491 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Andrea L Hevener · 2003 to 2026
$40.4MWake Forest Clinical and Translational Science AwardUL1TR001420 · NCATS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ARD, JAMY D, FOLEY, KRISTIE L · 2015 to 2023
$32.3MClinical and Translational Science AwardUL1TR000040 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GINSBERG, HENRY N · 2012 to 2015
$26.2MGenomic and Proteomic Architecture of AtherosclerosisR01HL111362 · NHLBI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI HERRINGTON, DAVID MCLEOD · 2012 to 2021
$17.2MTask Area A Core Study Operations.Task Area A shall encompass annual follow-up of cohort members, clinical endpoints ascertainment, study coordination activities, maintenance of the database and biosp75N92020D00001 · NHLBI · UNIVERSITY OF WASHINGTON · PI MCCLELLAND, ROBYN LEAGH · 2020 to 2025
$17.2MTask Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00005 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI WATSON, KAROL E · 2020 to 2025
$5.1MTO EXERCISE OPTION PERIOD ONE (1) FOR TASK AREA A - MESA CORE OPERATIONS, FIELD CENTER.75N92020D00004 · NHLBI · NORTHWESTERN UNIVERSITY · PI SIEGEL, JONATHAN H · 2020 to 2025
$4.5MTask Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00006 · NHLBI · UNIVERSITY OF MINNESOTA · PI PANKOW, JAMES S · 2020 to 2025
$4.4MTask Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00003 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI POST, WENDY S · 2020 to 2025
$3.8MTask Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00007 · NHLBI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI BERTONI, ALAIN GERALD · 2020 to 2025
$3.5MNCATS NIH HHS UL1 TR000040NCATS NIH HHS UL1 TR001079NCATS NIH HHS UL1 TR001420NCATS NIH HHS UL1 TR001881NHLBI NIH HHS 75N92020D00001NHLBI NIH HHS 75N92020D00002NHLBI NIH HHS 75N92020D00003NHLBI NIH HHS 75N92020D00004NHLBI NIH HHS 75N92020D00005NHLBI NIH HHS 75N92020D00006NHLBI NIH HHS 75N92020D00007NHLBI NIH HHS HHSN268201500003CNHLBI NIH HHS HHSN268201500003INHLBI NIH HHS N01 HC095159NHLBI NIH HHS N01 HC095160NHLBI NIH HHS N01 HC095161NHLBI NIH HHS N01 HC095163NHLBI NIH HHS N01 HC095164NHLBI NIH HHS N01 HC095165NHLBI NIH HHS N01 HC095166NHLBI NIH HHS N01 HC095167NHLBI NIH HHS N01 HC095168NHLBI NIH HHS N01 HC095169NHLBI NIH HHS R01 HL111362NHLBI NIH HHS R01 HL133932NIDDK NIH HHS P30 DK063491
6 · The paper itselfAbstract
Clinical heterogeneity remains a challenge in the practice of medicine and is an underlying motivation for much of biomedical research. Unfortunately, despite an abundance of technologies capable of producing millions of discrete data elements with information about a patient's health status or disease prognosis, our ability to translate those data into meaningful improvements in understanding of clinical heterogeneity is limited. To address this gap, we have applied newer approaches to manifold learning and developed additional and complementary techniques to interrogate and interpret complex, high dimensional omics data. The central premise is that there exist manifolds embedded in high dimensional data that represent fundamental biologic processes that may help address the challenges of clinical heterogeneity. Preliminary evidence from several real-world data sets suggests that these techniques can identify coherent and reproducible manifolds embedded in higher dimensional omics data. Work is currently ongoing to determine the clinical informativeness of these novel data structures.
Indexed as
Biomedical ResearchMedicineBig DataHumansLearning
Identifiers
PMID37701617
PMCPMC10493739
What OpenQuestion holds
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