Validation of the Machine Learning-Based Stroke Impact Scale With a Cross-Cultural Sample

CONCLUSIONS AND RELEVANCE: The ML-SIS provides scores mostly identical to those of the original measure, with similar test-retest reliability, except for the Emotion domain. Thus, it is a promising alternative that can be used to lessen the burden of routine assessments and provide scores comparable to those of the original SIS 3.0. Plain-Language Summary: The machine learning-based Stroke Impact Scale (ML-SIS) is as reliable as the original Stroke Impact Scale-Third Edition, except for the Emotion domain. Thus, the ML-SIS can be used to improve the efficiency of clinical assessments and also relieve the burden on people with stroke who are completing the assessments.PMID:38271640 | DOI:10.5014/ajot.2024.050356
Source: The American Journal of Occupational Therapy - Category: Occupational Health Authors: Source Type: research