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BEGIN:VEVENT
DTSTAMP:20260915T200535Z
LAST-MODIFIED:20210408T144248Z
DTSTART:20210429T130000Z
DTEND:20210429T143000Z
UID:event2420@bu.edu
URL:http://physics.bu.edu/internal/events/show/2420
SUMMARY:Deep learning for Alzheimer's disease assessment
DESCRIPTION:Featuring Shangran Qiu\, Boston University\, Physics Department
	\n\nPart of the Preliminary Oral Exam.\n\nDespite the recent prosperity of 
	machine learning research in medicine\, its clinical applications remain ch
	allenging. Current clinical diagnosis of Alzheimer’s disease (AD) is comp
	licated and requires expert doctors to carefully review patient’s medical
	 history\, various neuropsychological and functional tests\, and brain imag
	ing scans. Efficient\, accurate and interpretable AI-aided diagnostic metho
	d for AD is thus in urgent demand. We created an interpretable deep learnin
	g framework to generate AD risk maps on brain MRI scans and validated our a
	pproach with independent datasets. Ongoing work is focused on incorporating
	 this framework for the diagnosis of the pre-dementia stage\, AD dementia\,
	 and other forms of dementia. The broad diagnostic spectrum makes the curre
	nt project a potential tool to fit in the clinical environment.
LOCATION: \, \, 
STATUS:CONFIRMED
CLASS:PUBLIC
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