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Jonathan H. Chen
Stanford University
$3,609,042
Attributed
$3,609,042
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 $794.5K · FY2015–25$1M$750K$500K$250K$0
'15
'16
'17
'18
'19
'20
'21
'22
'23
'24
'25
Funding mix
By agency
NIH$3,609,042 · 3
By mechanism
R01$2,321,762 · 1
K01$893,030 · 1
R56$394,250 · 1
Top collaborators
No co-investigators on record.
Most similar at Stanford University
Same institution · by research overlap
- Amato J. Giaccia$32,506,927
- Julia F Simard$5,217,643
- Titilola Falasinnu$631,260
- Ansuman Satpathy$10,746,825
- David Matthew Maahs$18,119,674
Others in their field
Top investigators on “Training”
- Jeffrey P Krischer · University Of South Florida$314,856,919
- Christopher McKay · Battelle Memorial Institute$290,340,771
- Judith S. Currier · University Of California Los Angeles$276,624,848
- Daniel R Kuritzkes · Brigham And Women'S Hospital$258,658,543
- Michael David Hughes · Harvard University D/B/A Harvard School Of Public Health$239,830,683
- Steven E Reis · University Of Pittsburgh At Pittsburgh$232,330,444
Research focus
TrainingEvaluationPredictive ModelingMachine LearningPrototypeRecommendationPatternLearningStatisticsManualsClinical TrialsTranslatingValidationPoint Of CareElectronic Health RecordClinical Decision Support SystemsCostHospitalizationClinical PracticeAlgorithmsClinical MedicineMedicalEnvironmentFuture
Grant awards (9)
Measuring and Predicting Appropriate Antibiotic Use to Combat Resistant Bacteria$762,937
R01 · FY2025 · AI · contact PI
Measuring and Predicting Appropriate Antibiotic Use to Combat Resistant Bacteria$764,336
R01 · FY2024 · AI · contact PI
Measuring and Predicting Appropriate Antibiotic Use to Combat Resistant Bacteria$794,489
R01 · FY2023 · AI · contact PI
Machine Learning Clinical Order Recommendations for Specialty Consultation Care$394,250
R56 · FY2020 · LM · contact PI
Data-Mining Clinical Decision Support from Electronic Health Records$178,606
K01 · FY2019 · ES · contact PI
Data-Mining Clinical Decision Support from Electronic Health Records$178,606
K01 · FY2018 · ES · contact PI
Data-Mining Clinical Decision Support from Electronic Health Records$178,606
K01 · FY2017 · ES · contact PI
Data-Mining Clinical Decision Support from Electronic Health Records$178,606
K01 · FY2016 · ES · contact PI
Data-Mining Clinical Decision Support from Electronic Health Records$178,606
K01 · FY2015 · ES · contact PI