← Leaderboards
Muhammad Khalid Khan Niazi
Wake Forest University Health Sciences
$1,085,487
Attributed
$2,170,974
Total exposure
2
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 $776.2K · FY2021–25$1M$750K$500K$250K$0
'21
'22
'23
'24
'25
Funding mix
By agency
NIH$2,170,974 · 2
By mechanism
R01$1,550,974 · 1
R21$620,000 · 1
Top collaborators
- Wei Chen3 shared
- Scott Segal3 shared
Most similar at Wake Forest University Health Sciences
Same institution · by research overlap
- Scott Segal$310,000
Others in their field
Other Emerging Leaders on “Systems Analysis”
- Sonia M Thomas · Research Triangle Institute$701,865,642
- Tracy L Nolen · Research Triangle Institute$474,487,152
- Marlene Ann Cooper · Harvard University D/B/A Harvard School Of Public Health$71,912,072
- Yunda Huang · Fred Hutchinson Cancer Center$70,764,772
- Martha Hering · Westat, Inc.$57,098,843
- John Hobbs · Suny At Stony Brook$41,857,417
Research focus
Systems AnalysisStatistical Data InterpretationPerformancePatient CareSoftware ToolsScientistDeep LearningImageInterobserver VariabilityNovel StrategiesPublic HealthAutomated Image AnalysisReproducibilityRisk StratificationComputer-Assisted Image AnalysisConsumptionDisorder RiskDiagnosticImage AnalysisInnovationMissionMortalityCessation Of LifeTraining
Grant awards (6)
An ensemble deep learning model for tumor bud detection and risk stratification in colorectal carcinoma.$492,621
R01 · FY2025 · CA
An ensemble deep learning model for tumor bud detection and risk stratification in colorectal carcinoma.$514,691
R01 · FY2024 · CA
An ensemble deep learning model for tumor bud detection and risk stratification in colorectal carcinoma.$543,662
R01 · FY2023 · CA
Development of quantitative tools to predict patients with difficult intubation to minimize treatment related complications$232,500
R21 · FY2023 · EB · contact PI
Development of quantitative tools to predict patients with difficult intubation to minimize treatment related complications$193,750
R21 · FY2022 · EB · contact PI
Development of quantitative tools to predict patients with difficult intubation to minimize treatment related complications$193,750
R21 · FY2021 · EB · contact PI