R
Ritesh A. Ramdhani
Researcher at Hofstra University
Publications - 39
Citations - 535
Ritesh A. Ramdhani is an academic researcher from Hofstra University. The author has contributed to research in topics: Deep brain stimulation & Medicine. The author has an hindex of 10, co-authored 29 publications receiving 374 citations. Previous affiliations of Ritesh A. Ramdhani include Icahn School of Medicine at Mount Sinai & New York University.
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Journal ArticleDOI
Isolated Focal Dystonia as a Disorder of Large-Scale Functional Networks
Giovanni Battistella,Pichet Termsarasab,Ritesh A. Ramdhani,Stefan Fuertinger,Kristina Simonyan +4 more
TL;DR: It is suggested that isolated focal dystonias likely represent a disorder of large‐scale functional networks, where abnormal regional interactions contribute to network‐wide functional alterations and may underline the pathophysiology of isolated focal Dystonia.
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Diagnosis, treatment, and clinical outcomes in 43 cases with cerebrotendinous xanthomatosis.
P. Barton Duell,Gerald Salen,Florian Eichler,Andrea E. DeBarber,Sonja L. Connor,Lise Casaday,Suman Jayadev,Yasushi Kisanuki,Patamaporn Lekprasert,Mary J. Malloy,Ritesh A. Ramdhani,Paul Ziajka,Joseph F. Quinn,Kimmy G. Su,Andrew S. Geller,Margaret R. Diffenderfer,Ernst J. Schaefer +16 more
TL;DR: Health care providers seeing young patients with tendon xanthomas and relatively normal cholesterol levels, especially those with cataracts and learning problems, should consider the diagnosis of CTX so they can receive treatment.
Journal ArticleDOI
What’s special about task in dystonia? A voxel-based morphometry and diffusion weighted imaging study
Ritesh A. Ramdhani,Veena Kumar,Miodrag Velickovic,Steven J. Frucht,Michele Tagliati,Kristina Simonyan +5 more
TL;DR: Distinct microstructural patterns in task‐specific and non–task‐specific dystonias may represent neuroimaging markers and provide evidence that these two dystonia subclasses likely follow divergent pathophysiological mechanisms precipitated by different triggers.
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Optimizing Clinical Assessments in Parkinson's Disease Through the Use of Wearable Sensors and Data Driven Modeling.
TL;DR: The use of inertial sensors and machine learning algorithms in Parkinson's disease are reviewed, yielding novel classification and probabilistic clinical models that stand to change existing treatment paradigms, refine the application of advance therapeutics, and may facilitate the development and testing of disease modifying agents for this disease.
Journal ArticleDOI
Neural correlates of abnormal sensory discrimination in laryngeal dystonia.
Pichet Termsarasab,Ritesh A. Ramdhani,Giovanni Battistella,Estee Rubien-Thomas,Melissa Choy,Ian M. Farwell,Miodrag Velickovic,Andrew Blitzer,Steven J. Frucht,Richard B. Reilly,Michael Hutchinson,Laurie J. Ozelius,Kristina Simonyan +12 more
TL;DR: The behavioral and neuroimaging findings outline the relationship of abnormal sensory discrimination with the phenotype and genotype of isolated LD, suggesting the presence of potentially divergent pathophysiological pathways underlying different manifestations of this disorder.