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Developing univariate neurodegeneration biomarkers with low-rank and sparse subspace decomposition

Jan 2, 2021 | Computational methods for biomarker discovery

Sponsor: NIH Cognitive decline due to Alzheimer’s disease (AD) is closely associated with brain structure alterations captured by structural magnetic resonance imaging (sMRI). It supports the validity to develop sMRI-based univariate neurodegeneration biomarkers...

Predicting Brain Amyloid Using Multivariate Morphometry Statistics, Sparse Coding, and Correntropy

Jan 2, 2021 | Computational methods for biomarker discovery

Sponsors: NIH, AZ Alzheimer Consortium Biomarker assisted preclinical/early detection and intervention in Alzheimer’s disease (AD) may be the key to therapeutic breakthroughs. One of the presymptomatic hallmarks of AD is the accumulation of beta-amyloid (Aβ) plaques...

Inverse Mapping of Spatial-Temporal Molecular Heterogeneity from Imaging Phenotype

Oct 21, 2020 | AI in medicine and imaging

Sponsor NSF A significant challenge in treating some aggressive cancers and neurological diseases is the lack of understanding regarding the spatial-temporal molecular heterogeneity of the diseased tissue/organ. Molecular characteristics and interaction vary...

Imaging the migraine brain pre-and post-erenumab: an MRI study

Oct 21, 2020 | AI in medicine and imaging

Sponsor: Amgen Inc. This study will investigate longitudinal changes in brain structure and function in high frequency episodic and chronic migraine patients who are responding to erenumab treatment compared to those patients who are non-responders. In addition,...

Noninvasive MRI techniques to detect pathology in murine models of renal disease

Oct 21, 2020 | AI in medicine and imaging

Sponsor: DOD The broad, long-term goal of this multi-disciplinary collaborative of biomedical engineers and physician- scientists is to develop early, non-invasive methods to identify individuals at risk of developing chronic kidney disease (CKD). Current methods to...
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Research Areas

  • AI in Medicine and Imaging
  • Health information technology
  • Computational methods for biomarker discovery
  • Computational methods for design and discovery in nanotechnology
  • Biosensing for personalized health and rehabilitation
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