Caitlin Cassidy
6 Papers
2 Citations
Caitlin Cassidy is an academic researcher. The author has contributed to research in topics: Rehabilitation & Medicine. The author has an hindex of 2, co-authored 3 publications.
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Papers
Canadian stroke best practice recommendations: Stroke rehabilitation practice guidelines, update 2015
Debbie Hebert,M. Patrice Lindsay,M. Patrice Lindsay,Amanda McIntyre,Adam Kirton,Peter Rumney,Stephen D. Bagg,Mark Bayley,Dar Dowlatshahi,Sean P. Dukelow,Maridee Garnhum,Ev Glasser,Mary-Lou Halabi,Ester Kang,Marilyn MacKay-Lyons,Rosemary Martino,Annie Rochette,Sarah Rowe,Nancy M. Salbach,Brenda Semenko,Bridget D. Stack,Luchie Swinton,Valentine Weber,Matthew Mayer,Sue Verrilli,Gabrielle deVeber,John Andersen,Karen M. Barlow,Caitlin Cassidy,Marie-Emmanuelle Dilenge,Darcy Fehlings,Ryan Hung,Jerome Iruthayarajah,Laura Lenz,Annette Majnemer,Jacqueline Purtzki,Mubeen F. Rafay,Lyn K Sonnenberg,Ashleigh Townley,Shannon Janzen,Norine Foley,Robert Teasell +41 more
TL;DR: The 2015 update of the Canadian Stroke Best Practice Recommendations: Stroke Rehabilitation Practice Guidelines is a comprehensive summary of current evidence-based recommendations for all members of multidisciplinary teams working in a range of settings, who provide care to patients following stroke.
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A Systematic Review of the Scientific Literature for Rehabilitation/Habilitation Among Individuals With Pediatric-Onset Spinal Cord Injury.
Amanda McIntyre,Cristina L. Sadowsky,Andrea L. Behrman,Rebecca Martin,Marika Augutis,Caitlin Cassidy,Randal R. Betz,Per Ertzgaard,M.J. Mulcahey +8 more
TL;DR: The evidence for rehabilitation/habilitation of pediatric-onset SCI is extremely limited; nearly all studies are level 4-5 evidence and future studies across several domains should be conducted with novel approaches to research design to alleviate issues related to sample sizes and heterogeneity.
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Journal Article
Covid-19 Knowledge Deconstruction and Retrieval: Solutions of Intelligent Bibliometrics
TL;DR: A research framework is proposed to assist scientists in identifying, retrieving, and visualizing the emerging Covid-19 knowledge and incorporates principal topic decomposition, text analytics-based knowledge model, and the hierarchical topic tree (HTT) method to profile the research landscape, retrieve knowledge of specific interest, and visualize the knowledge structures.
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COVID-19 knowledge deconstruction and retrieval: an intelligent bibliometric solution
TL;DR: Wang et al. as discussed by the authors proposed a research framework and developed a dashboard that can assist scientists in identifying, retrieving, and understanding COVID-19 knowledge from the ocean of scholarly articles.