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Catherine Daniela Chong
Mayo Clinic Arizona
$6,420,349
Attributed
$6,420,349
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 $3.2M · FY2019–25$5M$3.8M$2.5M$1.3M$0
'19
'20
'21
'22
'23
'24
'25
Funding mix
By agency
NIH$6,420,349 · 3
By mechanism
R61$3,152,333 · 1
R33$2,111,462 · 1
OT2$1,156,554 · 1
Top collaborators
No co-investigators on record.
Others in their field
Other Emerging Leaders on “Predictive Modeling”
- Valerie Koch · University Corporation For Atmospheric Res$243,972,016
- Yunda Huang · Fred Hutchinson Cancer Center$53,780,853
- Susan M Landau · University Of California Berkeley$47,252,026
- John Hobbs · Suny At Stony Brook$42,194,917
- Christopher Bee · Suny At Stony Brook$41,239,084
- Christopher Barnaby Nelson · University Of Melbourne$27,954,628
Research focus
Predictive ModelingLaboratoriesPost-Traumatic HeadachesRecording Of Previous EventsHeadacheCohortIntentionNeuroimagingRecoveryBrain ImagingMedical HistoryDemographicsDisabilityDiagnosticCommon SymptomAlgorithmsDeformityEnrollmentBrainClinical PracticeClinical DataBrain ConcussionClinical Decision-MakingClinical Trials
Grant awards (4)
Predicting Pain Recovery: A Multimodality Machine-learning Approach using Harmonized Electronic Health Record Data$1,156,554
OT2 · FY2025 · OD · contact PI
Biomarker Signature to Predict the Persistence of Post-Traumatic Headache$1,038,506
R33 · FY2024 · NS · contact PI
Biomarker Signature to Predict the Persistence of Post-Traumatic Headache$1,072,956
R33 · FY2023 · NS · contact PI
Biomarker Signature to Predict the Persistence of Post-Traumatic Headache$3,152,333
R61 · FY2019 · NS · contact PI