Automated PET tracer classification in multi-site, multi-cohort studies using deep learning
Deep learning classifies brain PET radiotracers directly from scans across sites and cohorts, improving metadata quality control.
robel-k.-gebre
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Regional diffusion imaging measures to disentangle SVD-related hypertensive arteriopathy versus cerebral amyloid angiopathy
A study of diffusion MRI signatures linked to hypertensive arteriopathy and cerebral amyloid angiopathy in cerebral small vessel disease.
sheelakumari-raghavan
Precise disease heterogeneity and progression quantification in MSA and Parkinson's disease using machine learning
We developed a machine learning framework to quantify disease heterogeneity and progression in multiple system atrophy and Parkinson's disease using structural and diffusion MRI.
robel-k.-gebre
Chapter 8 - Artificial intelligence: Relevance and applications in dementia
A book chapter reviewing AI applications in dementia research including imaging biomarkers, machine learning classification, and disease progression modeling.
sheelakumari-raghavan
Diffusion Imaging Measures to Disentangle SVD-related Hypertensive Arteriopathy versus Cerebral Amyloid Angiopathy
We used diffusion imaging measures to distinguish between hypertensive arteriopathy and cerebral amyloid angiopathy contributions to small vessel disease.
sheelakumari-raghavan
Can integration of Alzheimer's plasma biomarkers with MRI, cardiovascular, genetics, and lifestyle measures improve cognition prediction?
MRI, plasma biomarkers, genetics, cardiovascular risk, and lifestyle measures were compared for predicting cognitive decline.
robel-k.-gebre
Advancing Tau PET Quantification in Alzheimer Disease with Machine Learning: Introducing THETA, a Novel Tau Summary Measure
THETA is a machine-learning tau PET measure that captures the spatial pattern of tau deposition across the brain in Alzheimer's disease.
robel-k.-gebre
Mapping neuroimaging using artificial intelligence to detect hypersomnia and its neurobiological correlates
We applied AI methods to neuroimaging data to detect hypersomnia and characterize its neurobiological correlates.
diego-carvalho
Machine Learning Models of Polygenic Risk for Enhanced Prediction of Alzheimer Disease Endophenotypes
We developed machine learning models integrating polygenic risk scores for enhanced prediction of Alzheimer's disease imaging and fluid biomarker endophenotypes.
nathaniel-b.-gunter
Vascular risk, gait, behavioral, and plasma indicators of VCID
We examined vascular risk factors, gait measures, behavioral symptoms, and plasma biomarkers as indicators of vascular contributions to cognitive impairment and dementia.
sheelakumari-raghavan
Genetic risk scores enhance the diagnostic value of plasma biomarkers of brain amyloidosis
We demonstrated that genetic risk scores enhance the diagnostic accuracy of plasma biomarkers for detecting brain amyloidosis.
vijay-k.-ramanan
White Matter Degeneration Pathways Associated With Tau Deposition in Alzheimer Disease
We characterized white matter degeneration pathways associated with regional tau deposition in Alzheimer's disease.
jianqiao-tian
Cross-scanner harmonization methods for structural MRI may need further work: A comparison study
A systematic comparison questions the reliability of widely used cross-scanner harmonization methods for structural MRI.
robel-k.-gebre
Detecting hip osteoarthritis on clinical CT: A deep learning application based on 2-D summation images derived from CT
We developed the first deep learning application for detecting hip osteoarthritis from 2-D summation images derived from routine clinical CT scans.
robel-k.-gebre
Preparation of filter by alkali activation of blast furnace slag and its application for dye removal
We developed a filter using alkali-activated blast furnace slag for dye removal from wastewater.
mohammad-amzad-hossain-bhuyan
Discrimination of Low-Energy Acetabular Fractures from Controls Using Computed Tomography-Based Bone Characteristics
We identified CT-based bone structural characteristics that discriminate patients with low-energy acetabular fractures from matched controls.
robel-k.-gebre
Structural risk factors for low-energy acetabular fractures
We identified structural risk factors for low-energy acetabular fractures in the elderly using computed tomography.
robel-k.-gebre