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CAREER: Towards Gaze-guided Medical Image Analysis — NSF Award to SUNY at Stony Brook (NY, $345,207)

Medical image interpretation is a complex, context-dependent process that requires nuanced reasoning and decision-making, honed through years of clinical experience. Eye gaze patterns, a rich source of implicit expert knowledge, reveal how clinicians systematically identify and interpret critical features in medical im

Award titleCAREER: Towards Gaze-guided Medical Image Analysis
Award ID2442053
AwardeeSUNY at Stony Brook
CitySTONY BROOK
StateNY
Amount obligated$345,207
Principal investigatorPrateek Prasanna
ProgramInfo Integration & Informatics
Start date06/15/2025
AbstractMedical image interpretation is a complex, context-dependent process that requires nuanced reasoning and decision-making, honed through years of clinical experience. Eye gaze patterns, a rich source of implicit expert knowledge, reveal how clinicians systematically identify and interpret critical features in medical images. This project seeks to integrate these expert visual search patterns into machine learning (ML) frameworks, addressing the current gap in how ML models interpret medical image
SourceNSF Awards

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