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Mei Liu
University Of Florida
$2,086,334
Attributed
$2,086,334
Total exposure
2
Grants
2
Lead (contact PI)
Attributed= this PI's even-split share of every grant they're on (the fair, additive number). Exposure = full size of all those grants. They are the sole PI on all grants (the two match).
Funding over time
peak $512.3K · FY2019–25$1M$750K$500K$250K$0
'19
'20
'21
'22
'23
'24
'25
Funding mix
By agency
NIH$2,086,334 · 2
By mechanism
R01$2,086,334 · 2
Top collaborators
No co-investigators on record.
Most similar at University Of Florida
Same institution · by research overlap
- Yenisel Cruz-Almeida$13,117,222
- Azra Bihorac$9,708,570
- Xiao Fan$2,217,379
- Faming Liang$2,493,510
- Xiaolin Li$1,084,214
Others in their field
Other Emerging Leaders on “Learning”
- Peter W Pisters · University Of Tx Md Anderson Can Ctr$56,084,949
- Scott Andrew Sutherland · Vignet, Inc.$37,355,117
- Neeta Jain · Vignet, Inc.$37,355,117
- Mark Begale · Vignet, Inc.$37,355,117
- Klaus Romero · Critical Path Institute$31,739,260
- Nader Fotouhi · Global Alliance For Tb Drug Development$28,468,137
Research focus
LearningHigh RiskMachine LearningPatient-Focused OutcomesIncidenceAffectHospitalsLifePatient SubsetsRisk AssessmentCessation Of LifeAcute Renal Failure With Renal Papillary NecrosisClinical PredictorsAdjudicationExposure ToClinical DataElderlyEventGeographic LocationsCreatinineComputerized Medical RecordCommunitiesBaseAlgorithms
Grant awards (6)
Personalized Machine Learning for Acute Kidney Injury Prediction and Prognosis$261,465
R01 · FY2025 · DK · contact PI
Personalized Machine Learning for Acute Kidney Injury Prediction and Prognosis$300,243
R01 · FY2024 · DK · contact PI
Identifying Personalized Risk of Acute Kidney Injury with Machine Learning$271,307
R01 · FY2021 · DK · contact PI
Identifying Personalized Risk of Acute Kidney Injury with Machine Learning$234,845
R01 · FY2021 · DK · contact PI
Identifying Personalized Risk of Acute Kidney Injury with Machine Learning$506,170
R01 · FY2020 · DK · contact PI
Identifying Personalized Risk of Acute Kidney Injury with Machine Learning$512,304
R01 · FY2019 · DK · contact PI