National Health Insurance Service Ilsan Hospital Reports Findings in Stroke (Use of machine learning techniques for identifying ischemic stroke instead of the rule-based methods: a nationwide population-based study): Cerebrovascular Diseases and Conditions – Stroke

South Korea Daily Report

2024 JAN 17 (NewsRx) -- By a News Reporter-Staff News Editor at South Korea Daily Report -- New research on Cerebrovascular Diseases and Conditions - Stroke is the subject of a report. According to news originating from Goyang, South Korea, by NewsRx correspondents, research stated, “Many studies have evaluated stroke using claims data; most of these studies have defined ischemic stroke using an operational definition following the rule-based method. Rule-based methods tend to overestimate the number of patients with ischemic stroke.”

Our news journalists obtained a quote from the research from National Health Insurance Service Ilsan Hospital, “We aimed to identify an appropriate algorithm for identifying stroke by applying machine learning (ML) techniques to analyze the claims data. We obtained the data from the Korean National Health Insurance Service database, which is linked to the Ilsan Hospital database (n = 30,897). The performance of prediction models (extreme gradient boosting [XGBoost] or gated recurrent unit [GRU]) was evaluated using the area under the receiver operating characteristic curve (AUROC), the area under precision-recall curve (AUPRC), and calibration curve. In total, 30,897 patients were enrolled in this study, 3145 of whom (10.18%) had ischemic stroke. XGBoost, a tree-based ML technique, had the AUROC was 94.46% and AUPRC was 92.80%. GRU showed the highest accuracy (99.81%), precision (99.92%) and recall (99.69%). We proposed recurrent neural network-based deep learning techniques to improve stroke phenotyping.”

According to the news editors, the research concluded: “This can be expected to produce rapid and more accurate results than the rule-based methods.”

For more information on this research see: Use of machine learning techniques for identifying ischemic stroke instead of the rule-based methods: a nationwide population-based study. European Journal of Medical Research, 2024;29(1):6. European Journal of Medical Research can be contacted at: Bmc, Campus, 4 Crinan St, London N1 9XW, England. (BioMed Central - http://www.biomedcentral.com/; European Journal of Medical Research - www.eurjmedres.com)

The news correspondents report that additional information may be obtained from Youngmin Park, Dept. of Family Medicine, National Health Insurance Service Ilsan Hospital, Goyang, South Korea. Additional authors for this research include Hyunsun Lim, Jung Hwa Hong, Ki-Bong Yoo and Kwon-Duk Seo.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1186/s40001-023-01594-6. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

The publisher’s contact information for the European Journal of Medical Research is: Bmc, Campus, 4 Crinan St, London N1 9XW, England.