Evidence map›Paper›PMID 34268522›Full record

ArticlemedRxiv : the preprint server for health sciences2021

Decoding Clinical Biomarker Space of COVID-19: Exploring Matrix Factorization-based Feature Selection Methods.

Farshad Saberi-Movahed, Mahyar Mohammadifard, Adel Mehrpooya, Mohammad Rezaei-Ravari, Kamal Berahmand, Mehrdad Rostami, Saeed Karami, Mohammad Najafzadeh, Davood Hajinezhad, Mina Jamshidi and 9 more

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2021. 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
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

0 citing papers in PubMed, 25 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

19 authors at 10 institutions in 4 countries.

Farshad Saberi-Movahed *College of Engineering, North Carolina State University, Raleigh, NC 22606, USA.
Mahyar Mohammadifard *Department of Radiology, Birjand University of Medical Sciences, Birjand, Iran.
Adel Mehrpooya *School of Mathematical Sciences, Science and Engineering Faculty, Queensland University of Technology (QUT), Brisbane, Australia.
Mohammad Rezaei-RavariDepartment of Computer Engineering, University of Kerman, Kerman, Iran.
Kamal BerahmandSchool of Computer Sciences, Science and Engineering Faculty, Queensland University of Technology (QUT), Brisbane Australia.
Mehrdad RostamiOulu University, Oulu, Finland.
Saeed KaramiDepartment of Mathematics, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, 45137-66731, Iran.
Mohammad NajafzadehDepartment of Applied Mathematics, Faculty of Sciences and Modern Technologies, Graduate University of Advanced Technology, Kerman, Iran.
Davood HajinezhadSAS Institute Inc., Cary, NC, USA.
Mina JamshidiDepartment of Applied Mathematics, Faculty of Sciences and Modern Technologies, Graduate University of Advanced Technology, Kerman, Iran.
Farshid AbediInfectious Diseases Research Center, Birjand University of Medical Sciences, Birjand, Iran.
Mahtab Mohammadifard *Department of Pathology, Birjand University of Medical Sciences, Birjand, Iran.
Elnaz FarbodBaruch College, City University of New York, New York, USA.
Farinaz SafaviNeuroimmunology and Neurovirology Branch, National Institute of Neurological Disorders and Stroke, National Institute of Health, Bethesda, Maryland, USA.
Mohammadreza DorvashBiomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Viewbank, VIC, Australia.
Shahrzad VahediIndependent Researcher, Vancouver, Canada.
Mahdi EftekhariDepartment of Computer Engineering, University of Kerman, Kerman, Iran.
Farid Saberi-Movahed *Department of Applied Mathematics, Faculty of Sciences and Modern Technologies, Graduate University of Advanced Technology, Kerman, Iran.
Iman Tavassoly *Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY10029.
North Carolina State University · USQueensland University of Technology · AUAustralian Regenerative Medicine Institute · AUBaruch College · USGraduate University of Advanced Technology · IRInstitute for Advanced Studies in Basic Sciences · IRSAS Institute (United States) · USBirjand University of Medical Sciences · IRIcahn School of Medicine at Mount Sinai · USKerman University of Medical Sciences · IR

Funding

Pathophysiology of Basal Ganglia DisordersZ01NS003031 · NINDS · NEUROLOGICAL DISORDERS AND STROKE · PI HALLETT, MARK · 2007 to 2008
$4.4M
KITP Interdisciplinary Biology InitiativeR25GM067110 · NIGMS · UNIVERSITY OF CALIFORNIA SANTA BARBARA · PI SHRAIMAN, BORIS I · 2003 to 2018
$1.8M
Intramural NIH HHS Z01 NS003031NIGMS NIH HHS R25 GM067110
6 · The paper itself

Abstract

One of the most critical challenges in managing complex diseases like COVID-19 is to establish an intelligent triage system that can optimize the clinical decision-making at the time of a global pandemic. The clinical presentation and patients’ characteristics are usually utilized to identify those patients who need more critical care. However, the clinical evidence shows an unmet need to determine more accurate and optimal clinical biomarkers to triage patients under a condition like the COVID-19 crisis. Here we have presented a machine learning approach to find a group of clinical indicators from the blood tests of a set of COVID-19 patients that are predictive of poor prognosis and morbidity. Our approach consists of two interconnected schemes: Feature Selection and Prognosis Classification. The former is based on different Matrix Factorization (MF)-based methods, and the latter is performed using Random Forest algorithm. Our model reveals that Arterial Blood Gas (ABG) O

Identifiers

PMID34268522
PMCPMC8282111
OpenAlexW3180846963

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.