biostudies-literatureUnknown87Cheng B<h4>Background</h4>The National Institutes of Health Stroke Scale (NIHSS) is the most frequently applied clinical rating scale for standardized assessment of neurological deficits in acute stroke in both clinical and research settings. Notwithstanding this prominent role, important questions regarding its validity remain insufficiently addressed: Investigations of the underlying dimensional structure of the NIHSS yielded inconsistent results that are largely not generalizable across studies. Neurobiological validations by linking measured deficit dimensions to brain anatomy and function are missing.<h4>Methods</h4>We, therefore, employ advanced machine learning to identify an optimal representation of the dimensional structure of the NIHSS across two independent and heterogeneous stroke daEBioMedicine104425https://www.ebi.ac.uk/biostudies/studies/S-EPMC9800288biostudies-literatureMapping the deficit dimension structure of the National Institutes of Health Stroke Scale.PMC9800288Rimmele LThomalla GPatil KRChen JGerloff CCheng BEickhoff SBMayer CKonigsberg AfalseMapping the deficit dimension structure of the National Institutes of Health Stroke Scale.<h4>Background</h4>The National Institutes of Health Stroke Scale (NIHSS) is the most frequently applied clinical rating scale for standardized assessment of neurological deficits in acute stroke in both clinical and research settings. Notwithstanding this prominent role, important questions regarding its validity remain insufficiently addressed: Investigations of the underlying dimensional structure of the NIHSS yielded inconsistent results that are largely not generalizable across studies. Neurobiological validations by linking measured deficit dimensions to brain anatomy and function are missing.<h4>Methods</h4>We, therefore, employ advanced machine learning to identify an optimal representation of the dimensional structure of the NIHSS across two independent and heterogeneous stroke da2022-01-01T00:00:00Z2022 Dec2025-04-21T15:16:45.554Z2025-04-21T15:16:45.554ZS-EPMC98002883656348810.1016/j.ebiom.2022.104425