Changing Competitive Business Dynamics Through Sustainable Big Data Analysis

Artificial Intelligence (AI): A Metamorphic Transformation in Healthcare Services

Author(s): B.C.M. Patnaik, Ipseeta Satpathy* and S. K. Baral

Pp: 237-250 (14)

DOI: 10.2174/9789815256659124060018

* (Excluding Mailing and Handling)

Abstract

Artificial intelligence plays a key role in all aspects of human existence, and technology is meant to improve human well-being. In this aspect, healthcare is a major field, and artificial intelligence is us hering in rapid progress. Artificial intelligence has provided several solutions that were previously un attainable, such as diagnosis, treatment, prevention, and therapy. Medical experts have traditionally been responsible for prediction, forecasting, as well as identification or decision-making, which are the main objectives of Artificial Intelligence (AI). AI is capable of providing a better healthcare service in the form of smart devices. By integrating artificial intelligence with the Internet of Things (IoT), compact and mobile devices are now making human life more comfortable. Aside from diagnosing diseases such as Alzheimer's, these devices are also used to provide appropriate treatment for various brain disorders. Considering the relevance of the same, the study is undertaken to understand the patient's and healthcare provider’s (doctors and nursing staff) perception of AI. The scope of the study includes super specialty private hospitals in the capital region of Odisha and Vizag of Andhra Pradesh. Around 387 samples were collected for analyzing the data, which included 142 patients, 153 nursing staff, and the rest were doctors. The period of the study was six months, from December 2021 to May 2022. The entire analysis was done under nine parameters: Robot-assisted surgery, virtual nursing assistants, administrative workflow assistants, fraud detection, prescription error recognition, automated image diagnosis, cyber security, connected medical devices, and identification of clinical trial participants with 33 attributes. 

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