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Xiao Hu

Emory University

$15,500,109
Attributed
$41,491,147
Total exposure
11
Grants
10
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 $13.8M · FY200725
$20M$15M$10M$5M$0
'07
'08
'09
'10
'11
'12
'13
'14
'15
'16
'17
'18
'19
'20
'21
'22
'23
'24
'25

Funding mix

By agency

NIH$41,491,147 · 11

By mechanism

OT2$24,565,446 · 1
R01$13,337,876 · 6
RF1$2,575,013 · 1
R21$1,012,812 · 3

Most similar at Emory University

Same institution · by research overlap

Others in their field

Top investigators on “Algorithms

Research focus

AlgorithmsSignal TransductionMonitorMachine LearningPhysiologicalIntracranial PressurePatternEventValidationBaseLeadLearningPredictive ModelingTrainingPerformanceData SetBlood Flow VelocityAcuteCerebrovascular CirculationAdoptionCerebral IschemiaDiagnosisPhysiologic PulseElectronic Health Record

Grant awards (39)

Bridge2AI: Bridge2AI: Patient-Focused Collaborative Hospital Repository Uniting Standards (CHoRUS) for Clinical Care AI$6,205,212
OT2 · FY2025 · OD
Bridge2AI: Patient-Focused Collaborative Hospital Repository Uniting Standards (CHoRUS) for Equitable AI$6,109,654
OT2 · FY2025 · OD
Novel Algorithm and Data Strategies to detect and Predict atrial fibrillation for post-stroke patients (NADSP)$659,406
R01 · FY2025 · HL · contact PI
Learning to Predict Delayed Cerebral Ischemia with Novel Continuous Cerebral Arterial State Index$616,932
R01 · FY2025 · NS · contact PI
Using AI on Routine Clinical and Imaging Data from Acute Stroke Encounter to Predict Post-Stroke Vascular Contributions to Cognitive Impairment (AI - RESPECT)$234,750
RF1 · FY2025 · NS · contact PI
Using AI on Routine Clinical and Imaging Data from Acute Stroke Encounter to Predict Post-Stroke Vascular Contributions to Cognitive Impairment (AI - RESPECT)$2,340,263
RF1 · FY2024 · NS · contact PI
Novel Algorithm and Data Strategies to detect and Predict atrial fibrillation for post-stroke patients (NADSP)$671,647
R01 · FY2024 · HL · contact PI
Bridge2AI: Patient-Focused Collaborative Hospital Repository Uniting Standards (CHoRUS) for Equitable AI$6,370,280
OT2 · FY2023 · OD
Novel Algorithm and Data Strategies to detect and Predict atrial fibrillation for post-stroke patients (NADSP)$700,615
R01 · FY2023 · HL · contact PI
Learning to Predict Delayed Cerebral Ischemia with Novel Continuous Cerebral Arterial State Index$620,610
R01 · FY2023 · NS · contact PI
Bridge2AI: Patient-Focused Collaborative Hospital Repository Uniting Standards (CHoRUS) for Equitable AI$5,880,300
OT2 · FY2022 · OD
Learning to Predict Delayed Cerebral Ischemia with Novel Continuous Cerebral Arterial State Index$580,324
R01 · FY2022 · NS · contact PI
Integrate Dynamic System Model and Machine Learning for Calibration-Free Noninvasive ICP$531,607
R01 · FY2022 · NS · contact PI
Learning to Predict Delayed Cerebral Ischemia with Novel Continuous Cerebral Arterial State Index$582,524
R01 · FY2021 · NS · contact PI
Integrate Dynamic System Model and Machine Learning for Calibration-Free Noninvasive ICP$544,156
R01 · FY2021 · NS · contact PI
Learning to Predict Delayed Cerebral Ischemia with Novel Continuous Cerebral Arterial State Index$612,984
R01 · FY2020 · NS · contact PI
Integrate Dynamic System Model and Machine Learning for Calibration-Free Noninvasive ICP$529,544
R01 · FY2020 · NS · contact PI
Integrate Dynamic System Model and Machine Learning for Calibration-Free Noninvasive ICP$608,229
R01 · FY2019 · NS · contact PI
Develop&validate SuperAlarm to detect patient deterioration with few false alarms$627,896
R01 · FY2018 · HL · contact PI
Integrate Dynamic System Model and Machine Learning for Calibration-Free Noninvasive ICP$614,615
R01 · FY2018 · NS · contact PI
Develop&validate SuperAlarm to detect patient deterioration with few false alarms$717,609
R01 · FY2017 · HL · contact PI
Develop&validate SuperAlarm to detect patient deterioration with few false alarms$483,615
R01 · FY2016 · HL · contact PI
Develop&validate SuperAlarm to detect patient deterioration with few false alarms$56,694
R01 · FY2016 · HL · contact PI
Develop&validate SuperAlarm to detect patient deterioration with few false alarms$531,284
R01 · FY2015 · HL · contact PI
ICP Elevation Alerting Based on a Predictive Model Hosting Platform$442,019
R01 · FY2015 · NS · contact PI
ICP Elevation Alerting Based on a Predictive Model Hosting Platform$435,641
R01 · FY2014 · NS · contact PI
ICP Elevation Alerting Based on a Predictive Model Hosting Platform$227,168
R01 · FY2013 · NS · contact PI
ICP Elevation Alerting Based on a Predictive Model Hosting Platform$182,560
R01 · FY2013 · NS · contact PI
ICP Elevation Alerting Based on a Predictive Model Hosting Platform$429,539
R01 · FY2012 · NS · contact PI
Continuous-Signal Driven Predictive Models in Neurological Intensive Care Units$330,138
R01 · FY2012 · NS · contact PI
Continuous-Signal Driven Predictive Models in Neurological Intensive Care Units$330,138
R01 · FY2011 · NS · contact PI
Continuous-Signal Driven Predictive Models in Neurological Intensive Care Units$333,507
R01 · FY2010 · NS · contact PI
Continuous-Signal Driven Predictive Models in Neurological Intensive Care Units$336,875
R01 · FY2009 · NS · contact PI
Intracranial Pressure Latency as a Biomarker of Cerebral Vasculature Status$168,438
R21 · FY2009 · NS · contact PI
Data Mining Based Noninvasive Intracranial Pressure Assessment$168,984
R21 · FY2008 · NS · contact PI
A Data Fusion Method for Bedside Monitoring of Lumped Cerebral Arterial Radii$168,984
R21 · FY2008 · NS · contact PI
Intracranial Pressure Latency as a Biomarker of Cerebral Vasculature Status$168,438
R21 · FY2008 · NS · contact PI
Data Mining Based Noninvasive Intracranial Pressure Assessment$168,984
R21 · FY2007 · NS · contact PI
A Data Fusion Method for Bedside Monitoring of Lumped Cerebral Arterial Radii$168,984
R21 · FY2007 · NS · contact PI