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Aneesh B. Singhal

Researcher at Harvard University

Publications -  242
Citations -  18970

Aneesh B. Singhal is an academic researcher from Harvard University. The author has contributed to research in topics: Stroke & Medicine. The author has an hindex of 60, co-authored 213 publications receiving 16746 citations. Previous affiliations of Aneesh B. Singhal include Spaulding Rehabilitation Hospital & Partners HealthCare.

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The International Classification of Headache Disorders, 3rd edition (beta version)

Jes Olesen, +131 more
- 01 Jul 2013 - 
TL;DR: The International Classification of Headache Disorders, 3 edition (beta version), may be reproduced freely for scientific, educational or clinical uses by institutions, societies or individuals as mentioned in this paper. But the authors require the permission of the International Headache Society.
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Narrative review: reversible cerebral vasoconstriction syndromes.

TL;DR: This narrative review, by specialists in the field of rheumatology, headache, and stroke, will outline the cause and pathophysiology, symptoms and signs, diagnosis, treatment, and prognosis of RCVS and areas of uncertainty.
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An evidence-based causative classification system for acute ischemic stroke

TL;DR: An algorithm that incorporated recent advances in stroke imaging and epidemiology to identify the most probable TOAST category in the presence of evidence for multiple mechanisms successfully classifies patients with acute ischemic stroke into determined etiologic categories without sacrificing reliabilty.
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Reversible Cerebral Vasoconstriction Syndromes: Analysis of 139 Cases

TL;DR: Patients with reversible cerebral vasoconstriction syndromes have a unique set of clinical imaging features, with no significant differences between subgroups, and the effects of empirical treatment with calcium channel blockers and glucocorticoids are investigated.
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A Computerized Algorithm for Etiologic Classification of Ischemic Stroke: The Causative Classification of Stroke System

TL;DR: An automated version of the SSS-TOAST, the Causative Classification System (CCS), is presented to facilitate its utility in multicenter settings and allows rapid analysis of patient data with excellent intra- and inter-examiner reliability, suggesting a potential utility in improving the fidelity of stroke classification in multicEnter trials or research databases in which accurate subtyping is critical.