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Mayte Suarez-Farinas
Icahn School Of Medicine At Mount Sinai
$1,313,309
Attributed
$2,957,819
Total exposure
3
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.
Funding over time
peak $1.6M · FY2024–25$2M$1.5M$1M$500K$0
'24
'25
Funding mix
By agency
NIH$2,957,819 · 3
By mechanism
R01$2,957,819 · 3
Top collaborators
- Girish Nitin Nadkarni3 shared
- Neomi A Shah3 shared
- Ankit Ashok Parekh1 shared
Most similar at Icahn School Of Medicine At Mount Sinai
Same institution · by research overlap
- Joseph Solomon Ross$20,762,764
- Girish Nitin Nadkarni$10,989,187
- Joel Stein$2,463,015
- Jenny J. Lin$6,197,650
- Juan P Wisnivesky$34,328,417
Others in their field
Other Rising Stars on “Data Set”
- Rebecca Montalvan · Westat, Inc.$86,600,000
- Gary Mays · Axle Informatics, Llc$50,929,860
- Jeffrey Leintz · National Opinion Research Center$40,628,545
- Brian Zavertnik · Palantir Technologies, Inc.$37,240,166
- Jinsy Andrews · Columbia University Health Sciences$21,294,649
- Suma Babu · Massachusetts General Hospital$15,865,175
Research focus
Data SetPhysiciansPredictive ModelingPersonalized PredictionsCohortPatient PopulationPatient-Focused OutcomesPersonalized MedicineMedicineHeterogeneityCardiovascular DiseasesClinical PracticeAffectContinuous Positive Airway PressureNovel StrategiesCardiovascular Risk FactorCardiovascular Disorder RiskCardiovascular SystemCharacteristicsEventHigh RiskClassificationCaringEffectiveness
Grant awards (4)
Enhancing Cardiovascular Risk Prediction and Treatment Response in Sleep Apnea Patients Using Advanced AI-based Transformer Models in Multi-Modal Sleep Data$816,472
R01 · FY2025 · HL
Application of Machine Learning to Identify Obstructive Sleep Apnea Subgroups at Risk for Atherosclerosis Progression and Cardiovascular Disease Events (OSA-GRANDE)$743,757
R01 · FY2025 · HL
Application of Machine Learning to Identify Obstructive Sleep Apnea Subgroups at Risk for Atherosclerosis Progression and Cardiovascular Disease Events (OSA-GRANDE)$804,477
R01 · FY2024 · HL
Integrating genomic and clinical data to predict disease phenotypes using heterogeneous ensembles$593,113
R01 · FY2024 · HG · contact PI