Purpose: There are various neurogenic bladder patterns that occur in patients during stroke. Among these patterns, the focus was mainly on the patient’s facial parsy diagnosis. Stroke requires early response, and it is most important to identify initial symptoms such as facial parsy. There is an urgent need for a diagnostic technology that notifies patients and caregivers of the onset of disease in the early stages of stroke. We developed an artificial intelligence (AI) stroke early-stage analysis software that can alert the early stage of stroke through analysis of facial muscle abnormalities for the elderly neurogenic bladder prevention.Methods: The method proposed in this paper developed a learning-based deep learning analysis technology that outputs the initial stage of stroke after acquiring a high-definition digital image and then deep learning face analysis. The applied AI model was applied as a multimodal deep learning concept. The system is linked and integrated with the existing urine management integrated system to support patient management with a total-care concept.Results: We developed an AI stroke early-stage analysis software that can alert the early stage of stroke with 86% hit performance through analysis of facial muscle abnormalities in the elderly. This result shows the validation result of the landmark image learning model based on the distance learning model.Conclusions: We developed an AI stroke early-stage diagnostic system as a wellness personal medical service plan and prevent cases of missing golden time when existing stroke occurs. In order to secure and facilitate distribution of this, it was developed in the form of AI analysis software so that it can be mounted on various hardware products. In the end, it was found that using AI for these stroke diagnoses and making them quickly and accurately had a positive effect indirectly, if not directly, on the neurogenic bladder.
The United Nations refers to an aging society if the population aged 65 or older exceeds 7% of the total population, and refers to an aging society if it exceeds 14%, and classifies it as a super-aged society if it exceeds 20%. Korea is already classified as an aging society in 2000, and the United States entered 1942 and Japan entered 1970. In 2018, Korean society entered the aged society at a rapid pace from an aging society, and diseases of the elderly are also increasing social expenditure. In order to reduce these social costs, various diagnostic technologies are being introduced to prevent cardiovascular disease, which is more than 40% of the diseases that can occur in the elderly. Among cardiovascular diseases, stroke should
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.