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Milena Anne Gianfrancesco
University Of California Berkeley
$619,477
Attributed
$619,477
Total exposure
3
Grants
3
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 $184.4K · FY2015–22$200K$150K$100K$50K$0
'15
'16
'17
'18
'19
'20
'21
'22
Funding mix
By agency
NIH$619,477 · 3
By mechanism
K01$457,849 · 1
F32$124,732 · 1
F31$36,896 · 1
Top collaborators
No co-investigators on record.
Most similar at University Of California Berkeley
Same institution · by research overlap
- Nilabh Shastri$19,407,030
- Stephen P Hinshaw$8,624,655
- Sarah Yun-Mi Lee$156,023
- Holly Elser$63,978
- Glenys J Thomson$1,335,490
Others in their field
Top investigators on “California”
- Gary D Acton · University Of California-Davis$320,373,312
- Mitchell J Malone · Texas A&M Research Foundation$320,373,312
- Gerald T Nepom · Benaroya Research Inst At Virginia Mason$298,740,071
- Judith S. Currier · University Of California Los Angeles$152,313,768
- Joseph J. Eron · Univ Of North Carolina Chapel Hill$137,892,773
- Sharon A Nachman · Johns Hopkins University$135,132,510
Research focus
CaliforniaEnvironmentElectronic Health RecordSan FranciscoAdverse EventEthnic OriginQuality Of LifePharmaceutical PreparationsRisk FactorsSafetyData SetUniversitiesBaseBiologicalPatient SafetyPositioning AttributeCharacteristicsProgramsRheumatoid ArthritisRaceSystemic Lupus ErythematosusComorbidityComputing MethodologiesEvent
Grant awards (8)
Computational methods using electronic health records and registry data to detect and predict clinical outcomes in rheumatic disease$12,577
K01 · FY2022 · AR · contact PI
Computational methods using electronic health records and registry data to detect and predict clinical outcomes in rheumatic disease$130,424
K01 · FY2021 · AR · contact PI
Computational methods using electronic health records and registry data to detect and predict clinical outcomes in rheumatic disease$54,000
K01 · FY2021 · AR · contact PI
Computational methods using electronic health records and registry data to detect and predict clinical outcomes in rheumatic disease$130,424
K01 · FY2020 · AR · contact PI
Computational methods using electronic health records and registry data to detect and predict clinical outcomes in rheumatic disease$130,424
K01 · FY2019 · AR · contact PI
Examining the causal effect of sociodemographic and genetic factors on patient safety outcomes in individuals prescribed high-risk immunosuppressive medications$63,538
F32 · FY2018 · AR · contact PI
Examining the causal effect of sociodemographic and genetic factors on patient safety outcomes in individuals prescribed high-risk immunosuppressive medications$61,194
F32 · FY2017 · AR · contact PI
Direct and indirect effects of obesity genes on multiple sclerosis$36,896
F31 · FY2015 · NS · contact PI