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• W3120408037 abstract "In the current era of technology, Artificial Intelligence (AI) is playing a vital role in the health care sector especially cardiac disease detection which is a major cause of sudden death. Both the elderly and young are at the risk of sudden cardiac death at the ratio of 1-2% all around the world. Although AI technology with wearable technology is being used to detect heart diseases for quite some time now, sometimes it fails due to multiple reasons which include algorithm failure, high cost of treatment, limited battery time wearable device, data training issues, security and privacy issue in IoT, slow working of devices, poor internet or patients don't reach the hospital on time. Which gives rise to false results. Security and privacy issues in the old devices are the biggest flaws due to which old devices work slowly and the internet issues are common, it helps us to check their heart parameters anytime and anywhere in the world which reduces the hospital's workload, cost issues and to line onward. Meanwhile, these problems can be overcome by using modern models such as ECG assessment, AI-based guidelines, Visy's model which can recognize five critical diseases. A Wearable ECG patch is a very lightweight model that provides high accuracy and efficiency. These devices are trained by using a machine learning algorithm, and AI plays a prime role to detect the diseases. It helps us to check their heart parameters anytime and anywhere in the world which reduces the hospital's workload and cost issues, and the devices provide updated information as real-time data is stored online and secured with firebase authentication. It is concluded that all modern devices are more efficacious, cost-effective, user friendly, and more secure." @default.
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• W3120408037 date "2020-11-06" @default.
• W3120408037 modified "2023-10-16" @default.
• W3120408037 title "Severe Analysis of Cardiac Disease Detection using the Wearable Device by Artificial Intelligence" @default.
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• W3120408037 doi "https://doi.org/10.1109/inocon50539.2020.9298388" @default.
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