11 citations · 29 across the 5 of their papers we have counts for
6 papers · 1 filter
Self-Supervised Longitudinal Neighbourhood Embedding
Jiahong Ouyang, Qingyu Zhao, Ehsan Adeli +4
Longitudinal MRIs are often used to capture the gradual deterioration of brain structure and function caused by aging or neurological diseases. Analyzing this data via machine lear…
Representation Disentanglement for Multi-modal brain MR Analysis
Jiahong Ouyang, Ehsan Adeli, Kilian M. Pohl +2
Multi-modal MRIs are widely used in neuroimaging applications since different MR sequences provide complementary information about brain structures. Recent works have suggested tha…
Vision-based Estimation of MDS-UPDRS Gait Scores for Assessing Parkinson's Disease Motor Severity
Mandy Lu, Kathleen Poston, Adolf Pfefferbaum +5
Parkinson's disease (PD) is a progressive neurological disorder primarily affecting motor function resulting in tremor at rest, rigidity, bradykinesia, and postural instability. Th…
Representation Learning with Statistical Independence to Mitigate Bias
Ehsan Adeli, Qingyu Zhao, Adolf Pfefferbaum +4
Presence of bias (in datasets or tasks) is inarguably one of the most critical challenges in machine learning applications that has alluded to pivotal debates in recent years. Such…
End-To-End Alzheimer's Disease Diagnosis and Biomarker Identification
Soheil Esmaeilzadeh, Dimitrios Ioannis Belivanis, Kilian M. Pohl +1
As shown in computer vision, the power of deep learning lies in automatically learning relevant and powerful features for any perdition task, which is made possible through end-to-…
End-to-End Parkinson Disease Diagnosis using Brain MR-Images by 3D-CNN
Soheil Esmaeilzadeh, Yao Yang, Ehsan Adeli
In this work, we use a deep learning framework for simultaneous classification and regression of Parkinson disease diagnosis based on MR-Images and personal information (i.e. age,…