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Amber M. Angell
University Of Southern California
$2,140,438
Attributed
$2,374,719
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.
Funding over time
peak $1.5M · FY2022–25$2M$1.5M$1M$500K$0
'22
'23
'24
'25
Funding mix
By agency
NIH$2,374,719 · 3
By mechanism
R01$1,906,157 · 2
R21$468,562 · 1
Top collaborators
- Yi Guo2 shared
Most similar at University Of Southern California
Same institution · by research overlap
- David K Ann$16,827,823
- Adam Matthew Leventhal$15,113,791
- Kai Wang$10,901,792
- Jennifer A Ailshire$5,776,163
- Norah A. Terrault$8,729,722
Others in their field
Other Rising Stars on “Indexing”
- Heinz Ernst Moser · University Of Texas Med Br Galveston$13,657,841
- April Carson · University Of Mississippi Med Ctr$9,022,104
- Christine W Hockett · Avera Mckennan$8,908,366
- Fumiaki Yokokawa · University Of Texas Med Br Galveston$7,180,989
- Brian J Lopresti · University Of Pittsburgh At Pittsburgh$6,934,890
- Monica Cecilia Munoz-Torres · University Of Colorado Denver$6,821,056
Research focus
IndexingLos AngelesElectronic Health RecordData SetAutism Spectrum DisorderAutistic ChildrenPediatric HospitalsRisk Prediction ModelMachine LearningNatural Language ProcessingStructured DataReview LiteratureFutureSociodemographicsReportingUnstructured DataDiagnosticChildParentsCohortCodeDisparity ReductionDiagnosisAutistic
Grant awards (5)
Machine Learning Prediction of Persistent Adverse Mental Health Outcomes for Autistic Children: Leveraging Social Determinants of Health from Clinical Data$817,597
R01 · FY2025 · MH · contact PI
Characterizing gastrointestinal disorder trajectories for autistic sub-groups: Machine learning prediction of risk profiles and response to treatment$632,427
R01 · FY2025 · HD · contact PI
Characterizing gastrointestinal disorder trajectories for autistic sub-groups: Machine learning prediction of risk profiles and response to treatment$456,133
R01 · FY2024 · HD · contact PI
Using Machine Learning with Real-World Data to Identify Autism Risk in Children$201,598
R21 · FY2023 · MH · contact PI
Using Machine Learning with Real-World Data to Identify Autism Risk in Children$266,964
R21 · FY2022 · MH · contact PI