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- W4308985491 abstract "As a result of smart wearable health devices and internet of things (IoT)-enabled smart home devices, healthcare monitoring systems are becoming more common. By shifting healthcare from face-to-face consultations to telemedicine, deep learning algorithms are preferred for reducing illnesses in the health sector. During training and games, accurate monitoring of physiological indications is critical for safeguarding athletes from life-threatening serious diseases and injuries. To track vital signs, advanced wearable sensors are deployed, and machine learning techniques are used to retrieve meaningful data. Even if doctors aren't there, deep learning algorithms assist specialists in accurately identifying these athletes' illnesses and administering the appropriate drugs." @default.
- W4308985491 created "2022-11-20" @default.
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- W4308985491 date "2022-11-15" @default.
- W4308985491 modified "2023-09-26" @default.
- W4308985491 title "Deep Learning Algorithms for Real-Time Healthcare Monitoring Systems" @default.
- W4308985491 doi "https://doi.org/10.1201/9781003355960-1" @default.
- W4308985491 hasPublicationYear "2022" @default.
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