Multi-Omic Admission-Based Prognostic Biomarkers Identified by Machine Learning Algorithms Predict Patient Recovery and 30-Day Survival in Trauma Patients is a research paper published in Metabolites (2022). On theSindex it has a DataRank of 0.449. It has been cited 19 times.
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Base Score Contribution
0.449
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →National Institutes of Health
Grant: R35-GM-127027
National Institutes of Health
Grant: DP2AI164325
National Institutes of Health
Grant: 1R35GM127027-01
Mechanisms of Immune Dysfunction after Trauma and Surgical Sepsis
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Grant: 2R38HL150207-05
Pittsburgh Innovation in Collaborative Training of Residents Alliance
National Institutes of Health
Grant: 5DP2AI164325-04
Using three-dimensional protein networks to uncover immuno-modulatory molecular phenotypes in infectious disease
National Institutes of Health
Grant: 5T32HL098036-04
Vascular Surgery Research Training
National Institutes of Health
Grant: 5R35GM119526-05
Mechanistic Elucidation and Targeted Therapy of Platelet Dysfunction After Trauma
FWCI
4.38
Citation Percentile
1.0%
Citation Trend
Fields of Study
Keywords
Sustainable Development Goals