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26Using Deep Learning to Characterize Persistent Physiological Parameters in Patient Monitoring Systems

DHYANENDRA JAIN¹, ANJANI GUPTA², AMIT KUMAR PANDEY³, PRASHANT VATS⁴

¹ CSE - AI & ML, ABES Engineering College, Ghaziabad, India

² Department of Computer Science and Engineering, IMS Engineering College, Ghaziabad, India

³ Department of Computer Science and Engineering (Data Science), ABES Engineering College, Ghaziabad, India

⁴ Department of Engineering & Technology, SGT University, India

Email: [e-mail], [e-mail], [e-mail], [e-mail]

Abstract

Deep learning offers great promise in medicine for enhancing illness diagnosis, decision support systems, and operational efficiency. In this chapter, we look at documented and prospective uses of machine learning for surveillance in the healthcare setting. We offer use scenarios and also discuss numerous problems related to the use of artificial intelligence to assess the massive amounts of complicated information that doctors need to know for continuous health monitoring of critical patients. Deep learning and machine intelligence, particularly when used in tandem with multimodal electronic medical record knowledge, have the ability to extract considerably more additional necessary details from such a presently underutilized source of data at the macro level. As more than just an information entity, machine intelligence along with deep learning relies on a large number ...