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UID:0-5023@eng.ufl.edu
DTSTART;TZID=America/New_York:20220418T150000
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URL:https://www.eng.ufl.edu/news-events/events/bme-seminar-artificial-inte
 lligence-in-cognitive-aging-novel-diagnosis-and-precision-intervention/
SUMMARY:BME Seminar: Artificial Intelligence in Cognitive Aging: Novel Diag
 nosis and Precision Intervention
DESCRIPTION:Ruogu Fang\, Ph.D.\, Assistant Professor\, Department of Biomed
 ical Engineering\, University of Florida\nWith the Cambrian explosion of m
 edical data and the rise in computing power\, artificial intelligence (AI)
  has embraced an unprecedented era to fully exert its potential in driving
  healthcare transformations\, especially in the aging population. Unfortun
 ately\, today’s medical approaches for cognitive aging and neurodegenera
 tive diseases are inadequate to close the gap between brain health span an
 d lifespan. Conventional diagnosis and “one size fits all” strategy ha
 ve led to misdiagnosis\, response heterogeneity\, and trial failures inter
 vention in understanding\, preventing\, diagnosing\, and treating brain di
 seases. In this talk\, I will first present a study on artificial intellig
 ence for Alzheimer’s Disease diagnosis from retinal imaging. Our study s
 heds light on modular\, data-economic\, and explainable AI for novel appro
 aches to early diagnosis of neurodegenerative diseases. I will then introd
 uce our AI-empowered precision intervention to prevent dementia through in
 dividualized brain anatomy modeling. Finally\, I will discuss our recent w
 ork on brain-inspired AI that uses neuroscience theories and principles to
  inspire the next-generation AI system that percepts and “thinks” like
  a human brain.\nBio:\nAn AI researcher in medicine and healthcare\, Dr. R
 uogu Fang is a tenure-track Assistant Professor in the J. Crayton Pruitt F
 amily Department of Biomedical Engineering and Associate Director of Intel
 ligent Critical Care Center (IC3) at the University of Florida. Her resear
 ch theme is artificial intelligence (AI)-empowered precision brain health 
 and brain/bio-inspired AI. She focuses on questions such as: How to use ma
 chine learning to quantify brain dynamics\, early diagnose Alzheimer’s d
 isease through novel imagery\, predict individualized treatment outcomes\,
  and design precision intervention. Fang’s current research is rooted in
  the confluence of AI and multimodal medical image analysis. She is the PI
  of NIH NIA RF1 (R01-equivalent)\, NSF Research Initiation Initiative (CRI
 I) Award\, NSF CISE IIS Award\, Ralph Lowe Junior Faculty Enhancement Awar
 d from Oak Ridge Associated Universities (ORAU). She has also received num
 erous recognitions. She was selected as the Inaugural recipient of the Rob
 in Sidhu Memorial Young Scientist Award from the Society of Brain Mapping 
 and Therapeutics\, Best Paper Award from the IEEE International Conference
  on Image Processing\, University of Florida Herbert Wertheim College of E
 ngineering Faculty Award for Excellence in Innovation\, UF BME Faculty Res
 earch Excellence Award\, among others. Fang’s research has been featured
  by Forbes Magazine\, The Washington Post\, ABC\, RSNA\, and published in 
 Lancet Digital Health. She served as Track Chairs and Area Chairs at natio
 nal and international conferences\, including BMES and MICCAI. She is an A
 ssociate Editor for Journal Medical Image Analysis\, Guest Editor for Comp
 uterized Medical Imaging and Graphics from Elsevier\, and Topic Editor for
  Frontiers in Human Neuroscience. Her research has been supported by NSF\,
  NIH\, Oak Ridge Laboratory\, DHS\, DoD\, NVIDIA\, and the University of F
 lorida. Dr. Fang directs SMILE lab\, standing for Smart Medical Informatic
 s Learning and Evaluation\, which also reflects her aspiration for every m
 ember in the lab to smile while exploring artificial intelligence in preci
 sion brain health.
CATEGORIES:Seminars
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