Discrepancies in Stroke Distribution and Dataset Origin in Machine Learning for Stroke

Machine learning algorithms depend on accurate and representative datasets for training in order to become valuable clinical tools that are widely generalizable to a varied population. We aim to conduct a review of machine learning uses in stroke literature to assess the geographic distribution of datasets and patient cohorts used to train these models and compare them to stroke distribution to evaluate for disparities.

Source: Journal of Stroke and Cerebrovascular Diseases - April 30, 2021 Category: Neurology Authors: Lohit Velagapudi, Nikolaos Mouchtouris, Michael P. Baldassari, David Nauheim, Omaditya Khanna, Fadi Al Saiegh, Nabeel Herial, M. Reid Gooch, Stavropoula Tjoumakaris, Robert H. Rosenwasser, Pascal Jabbour Source Type: research