Cerebral malaria: insight into pathology from optical coherence tomography is a research paper published in Scientific Reports (2021). On theSindex it has a DataRank of 0.764. It has been cited 23 times, with 12 citing works in its 1-hop citation network.
Scored on demand from live citation data
Linked data & code
DataRank reads this dataset's downstream impact straight off the citation graph â no black box, no proprietary weighting. How is this computed?
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Base Score Contribution
0.477
From this paper's citation signal
Citation Network Contribution
0.288
From 8 citing papers with measurable signal
Ranked by each citer's contribution to N(p) â log1p(Cq) divided by its reference count â out of 12 citers.
Medical Research Council
Grant: MR/J004189/1
Ultra-high resolution optical coherence tomography (UHR-SD OCT) in infants and children: characterisation of normal and abnormal foveal development
Medical Research Council
Grant: MRC/N004566/1
Wellcome Trust
Grant: 092668/Z/10/Z
Wellcome Trust
Grant: 084679/Z/08/Z
National Institutes of Health
Grant: 5U01AI126610
Medical Research Council
Grant: MR/N004566/1
NIAID NIH HHS
Grant: U01 AI126610
Wellcome Trust
Grant: 084679
Malawi-Liverpool-Wellcome Trust Clinical Research Programme.
Wellcome Trust
Grant: 092668
The Retinal Microvasculature in Cerebral Malaria in African Children.
National Institutes of Health
Grant: 5U01AI126610-07
Treating Brain Swelling in Pediatric Cerebral Malaria
Wellcome Trust
the Ulverscroft Foundation
Wellcome Trust
FWCI
3.60
Citation Percentile
0.9%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals
Additional file 1 of Identifying effective diagnostic biomarkers for childhood cerebral malaria in Africa integrating coexpression analysis with machine learning algorithm
Additional file 1 of Identifying effective diagnostic biomarkers for childhood cerebral malaria in Africa integrating coexpression analysis with machine learning algorithm
Additional file 2 of Identifying effective diagnostic biomarkers for childhood cerebral malaria in Africa integrating coexpression analysis with machine learning algorithm
Additional file 2 of Identifying effective diagnostic biomarkers for childhood cerebral malaria in Africa integrating coexpression analysis with machine learning algorithm