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Scott Doyle
State University Of New York At Buffalo
$1,891,472
Attributed
$1,891,472
Total exposure
1
Grants
1
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 $382.9K · FY2020–24$500K$375K$250K$125K$0
'20
'21
'22
'23
'24
Funding mix
By agency
NIH$1,891,472 · 1
By mechanism
R01$1,891,472 · 1
Top collaborators
No co-investigators on record.
Most similar at State University Of New York At Buffalo
Same institution · by research overlap
- Jun Xia$3,270,650
- Akinsola Ayomikun Oyelakin$53,384
- Steven Lewis$62,326
- Nicholas Michael Smith$1,388,838
Others in their field
Other Emerging Leaders on “Computational Pipelines”
- Yunda Huang · Fred Hutchinson Cancer Center$52,114,037
- Arnab Kumar Chatterjee · Washington University$22,541,385
- John Freymann · Leidos Biomedical Research, Inc.$14,011,208
- Sacha Gnjatic · Icahn School Of Medicine At Mount Sinai$13,678,514
- Noel P Burtt · Broad Institute, Inc.$11,051,536
- Forrest Christie Collman · Allen Institute$10,451,052
Research focus
Computational PipelinesAggressive BehaviorAftercareCompanionsAngiogenesisArchitectureArtificial IntelligenceAlgorithmsAnalysis PipelineActive LearningBiological MarkersBlindedCancer PatientCancer RecurrenceCancer TypeCessation Of LifeClinical ApplicationClinical PracticeClinical TrialsCohortCollectionCombined Modality TherapyCommunitiesConsensus
Grant awards (5)
A Quantitative Risk Model for Predicting Outcome and Identifying Structural Biomarkers of Treatment Targets in Oral Cancer on a Large Multi-Center Patient Cohort$372,344
R01 · FY2024 · DE · contact PI
A Quantitative Risk Model for Predicting Outcome and Identifying Structural Biomarkers of Treatment Targets in Oral Cancer on a Large Multi-Center Patient Cohort$379,976
R01 · FY2023 · DE · contact PI
A Quantitative Risk Model for Predicting Outcome and Identifying Structural Biomarkers of Treatment Targets in Oral Cancer on a Large Multi-Center Patient Cohort$376,210
R01 · FY2022 · DE · contact PI
A Quantitative Risk Model for Predicting Outcome and Identifying Structural Biomarkers of Treatment Targets in Oral Cancer on a Large Multi-Center Patient Cohort$380,042
R01 · FY2021 · DE · contact PI
A Quantitative Risk Model for Predicting Outcome and Identifying Structural Biomarkers of Treatment Targets in Oral Cancer on a Large Multi-Center Patient Cohort$382,900
R01 · FY2020 · DE · contact PI