NAL News:

​

(2021) Christina Dintica, PhD, a postdoctoral scholar in the UCSF Department of Psychiatry and member of the Kristine Yaffe Lab, has been awarded an Alzheimer's Association Research Fellowship! Under the mentorship of Dr. Yaffe and UT Health San Antonio's Dr. Mohamad Habes.

​

(2021) Jon Toledo and Tanweer Rashied presented the SPARE-tau work at the AAIC2021.

​

(2021) Our AI-dementia project, funded by the SAMF was featured in the UTHSA news.

​

(2021) Tanweer’s paper DeepMIR detecting cerebral microbleeds and iron deposits using MRI, advanced quantitative methods and Deep Learning has been accepted in Scientific Reports https://rdcu.be/co79B. Congrats Tanweer Rashid for the excellent work.

​

(2021) We have received the San Antonio Medical Foundation (SAMF) grant in collaboration with UTSA (Dhireesha Kudithipudi) and the VA (Adetoun Musa) to apply artificial intelligence to MRI and EEG data and subtype dementia patterns.

​

(2020) We published our work "The Brain Chart of Aging MachineLearning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 harmonized MR scans" in Alzheimer’s and dementia, the journal of Alzheimer’s Association.

​

(2020) We presented our workshop “Machine learning in neuroimaging”  at the MICCAI 2020.

​

(2020) Our paper comparing multi atlas based segmentation (MUSE) to FreeSurfer is online in Neuroimage.

​

(2020) We had a great featured research session with people excited about AI and its emerging role in uncovering dementia at the virtual AAIC2020.

(2020) Tanweer Rashid presented his work on deep learning for cerebral microbleeds and iron deposits detection in MRI.

(2020) Our paper Biological Psychiatry was featured in the UTHSA news.

​

(2020) Hangfan Liu presented his work on detecting microbleeds in MRI scans.

​

(2020) Our paper is now online in Biological Psychiatry ” Disentangling Heterogeneity in Alzheimer's Disease and Related Dementias Using Data-Driven Methods”, summarizing precision medicine approaches to subtyping Alzheimer's disease with advanced machine learning methods, applied on neuroimaging and other phenotyping data, for future care!

​