Author:
Hunter Elizabeth,Kelleher John D.
Abstract
Predicting an individual's risk of primary stroke is an important tool that can help to lower the burden of stroke for both the individual and society. There are a number of risk models and risk scores in existence but no review or classification designed to help the reader better understand how models differ and the reasoning behind these differences. In this paper we review the existing literature on primary stroke risk prediction models. From our literature review we identify key similarities and differences in the existing models. We find that models can differ in a number of ways, including the event type, the type of analysis, the model type and the time horizon. Based on these similarities and differences we have created a set of questions and a system to help answer those questions that modelers and readers alike can use to help classify and better understand the existing models as well as help to make necessary decisions when creating a new model.
Funder
Horizon 2020
Science Foundation Ireland
Subject
Computer Science Applications,Biomedical Engineering,Neuroscience (miscellaneous)
Cited by
2 articles.
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1. Stroke Prediction based on Integrated Models of Biological Risk Factors;Proceedings of the 2023 4th International Symposium on Artificial Intelligence for Medicine Science;2023-10-20
2. Determining the Proportionality of Ischemic Stroke Risk Factors to Age;Journal of Cardiovascular Development and Disease;2023-01-23