An Edge-Based Multi-Technology Architecture Healthcare Industry 4.0

Author:

C Mariya Aksharin Jesme 1,Mrs. T. Adlin 2,Akhila Kenz 3

Affiliation:

1. PG Scholar, Department of CSE, Ponjesly College of Engineering, Nagercoil, India

2. Professor, Department of CSE, Ponjesly College of Engineering, Nagercoil, India

3. M. Tech, Department of CSE, Ponjesly College of Engineering, Nagercoil, India

Abstract

Healthcare Industry 4.0 refers to intelligent operation processes in the medical sector. With the development of information technology, large-scale group decision making (GDM), which enables a greater number of decision makers (DMs) from various location or sectors to participate in decision making, has been quickly developed and been applied in Healthcare Industry 4.0 to aid in make decisions effectively and strategically. This study examined numerous actual examples of AI applications in healthcare in addition to doing a thorough analysis of the literature. The findings show that large hospitals are currently utilizing AI-enabled systems to support medical staff in patient diagnostic and treatment activities for a variety of disorders. Additionally, AI technologies are enhancing the effectiveness of administrative and healthcare tasks. Healthcare professionals are welcoming AI, but its uses can be seen from both utopian and dystopian perspectives. In order to generate a thorough understanding of GDM in Healthcare Industry 4.0 and to identify potential future development directions, this study conducts an overview. According to the paradigm of the general GDM process, which involves information representation, dimension reduction, establishing consensus, and result elicitation, the implementations of GDM methods in Healthcare Industry 4.0 are evaluated. We also discuss present research obstacles and potential future developments in relation to medicinal GDM. Our work is believed to be useful for researchers looking into GDM in Healthcare Industry 4.0. Also, discuss the details of those opportunities and challenges to provide a balanced view of the value of AI applications in healthcare. It is clear that rapid advances of AI and related technologies will help care providers create new value for their patients and improve the efficiency of their operational processes.

Publisher

Technoscience Academy

Subject

Cardiology and Cardiovascular Medicine

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