Digital Health in Primordial and Primary Stroke Prevention: A Systematic Review
Stroke 53:1008-1019, Feigin, V.L.,et al, 2022
Reliability of Real-Time Video Smartphone for Assessing National Institutes of Health Stroke Scale Scores in Acute Stroke Patients
Stroke 43:3271-3277, Demaerschalk, B.,et al, 2012
Evaluation of Medical Decision Support Systems (DDX Generators) Using Real Medical Cases of Varying Complexity and Origin
BMC Med Inform Dcis Mak 22:254, Fritz,P.,et al, 2022
Rapid Implementation of Virtual Neurology in Response to the COVID-19 Pandemic
Neurol 94:1077-1087, Grossman, S.N.,et al, 2020
Automated DWI analysis can identify patients within the thrombolysis time window of 4.5 hours
Neurol 90:e1570-e1577, Wouters, A.,et al, 2018
Using Artificial Intelligence to Reduce the Risk of Nonadherence in Patients on Anticoagulation Therapy
Stroke 48:1416-1419, Labovitz, D.L.,et al, 2017
National Randomized Controlled Trial of Virtual House Calls for Parkinson Disease
Neurol 89:1152-1161,1103, Beck, C.A.,et al, 2017
A Review of the Evidence for the Use of Telemedicine Within Stroke Systems of Care: A Scientific Statement from the American Heart Association/American Stroke Association
Stroke 40:2616-2634, Schwamm,L.H.,et al, 2009
Recommendations for the Implementation of Telemedicine Within Stroke Systems of Care: A Policy Statement From the American Heart Association
Stroke 40:2635-2660, Schwamm,L.H.,et al, 2009