AA
Anupa A Vijayakumari
Cleveland Clinic Lerner College of Medicine, Cleveland Clinic, National Institute of Mental Health and Neurosciences, SRM Institute of Science and Technology, University of Pennsylvania
Research areas: Medicine · Neurology · Neurological disorders and treatments · Parkinson's Disease Mechanisms and Treatments · Dementia and Cognitive Impairment Research
0000-0001-7041-9454
Employment
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Cleveland Clinic Lerner College of Medicine Assistant Professor2026 - Present
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Cleveland Clinic Research Associate2022 - Present
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Cleveland Clinic Postdoctoral fellow2021 - Present
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University of Pennsylvania Postdoctoral fellow2019 - 2021
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Thomas Jefferson University Clinical Neuroimaging Post-doctoral Fellow2018 - 2019
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Sree Chitra Thirunal Institute for Medical Sciences and Technology Postdoctoral fellow2016 - 2018
Education
- 2011 - 2016
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SRM Institute of Science and Technology Master of Technology, Postgraduate Engineering Degree2006 - 2008
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University of Kerala Bachelor of Technology, Undergraduate Engineering Degree2002 - 2006
Projects & Funding
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Biochemical and functional investigation of dorsolateral prefrontal cortex in mild cognitive impairment using functional magnetic resonance spectroscopy and functional magnetic resonance imaging. Science and Engineering Research Board, Department of Science & Technology, Government of India2016 - 2018
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AI-Driven Prediction of Motor Progression in Parkinson’s Disease: A Multi-Cohort Validation Approach Neurological Institute Emerging Science Career Award
Publications (41)
- Data-driven subtyping of Parkinson’s disease using MRI: current insights, challenges, and future directions Save
- Clinical relevance of MRI-informed motor progression phenotypes in early Parkinson’s disease Save
- Data-driven neurobiological subtyping of Parkinson's disease using diffusion MRI-derived isotropic diffusion. Save
- Evaluating an MRI-Based Machine Learning Classifier for Parkinson’s Progression Using Real-World Clinical Measures Save
- Extracellular Fluid Patterns in the Basal Ganglia Reveal Distinct Motor Phenotypes in Parkinson’s Disease: A Machine Learning Approach Save
- Impact of STN-DBS on Kinesthetic Illusion Processing in Parkinson’s Disease: An fMRI Study Save
- Data-Driven Neurobiological Subtyping of Parkinson’s Disease Using Diffusion MRI-Derived Isotropic Diffusion Save
- Longitudinal Effects of Initial Deep Brain Stimulation Settings on Force-Tracking Brain Activation and Motor Performance in Parkinson’s Disease Save
- Machine Learning Analysis of DTI-Derived Free Water Reveals Distinct Parkinson’s Disease Subtypes: A Two-Year Longitudinal Study Save
- Neuroanatomical heterogeneity drives divergent cognitive and motor trajectories in Parkinson's disease subtypes Save
- Parkinson’s disease subtypes and their association with probable rapid eye movement sleep behavior disorder severity: a brainstem tractography and machine learning investigation Save
- Developing a Supervised Machine Learning Model for Long-Term Cognitive Status Prediction in Parkinson Disease Save
- STN-DBS Frequency Effects in Parkinson’s: An fMRI Study Save
- Can Baseline Diffusion Tensor Imaging Analysis Along the Perivascular Space Predict Motor Progression at 5 Years in Parkinson Disease? Save
- Can Baseline Diffusion Tensor Imaging Analysis Along the Perivascular Space Predict Motor Progression at 5 Years in Parkinson Disease? Save
- Brainstem Tractography and Machine Learning Reveal Subtypes Linked to Variable REM Sleep Behavior Disorder Severity in Parkinson's Disease Save
- A novel MRI-based volumetric index for monitoring the motor symptoms in Parkinson's disease. Save
- Understanding cognitive changes in patients with Parkinson's disease using novel fiber quantification techniques. Save
- Leveraging MRI and machine-learning for early detection of cognitive impairment in Parkinson’s disease Save
- Data-driven Approach to Identify Subtypes and Progression of Parkinson’s disease using Multimodal Imaging Data (P6-11.006) Save