scholarly journals BIG DATA ANALYTICS IN HEALTHCARE SERVICES

2019 ◽  
Vol 1 (2) ◽  
pp. 22-24
Author(s):  
GUNASEKAR THANGARASU ◽  
KAYALVIZHI SUBRAMANIAN

This study addresses the healthcare services problems which focus on the upcoming and promising areas of medical research and proposed a novel approach integrating in big data analytics and Apache. The proposed approach will improve the healthcare services fastly and efficiently. The big data analytics can continually evaluate clinical data in order to improve the effective practices of physicians and improved patient care

Author(s):  
Koppula Srinivas Rao ◽  
Saravanan S. ◽  
Pattem Sampath Kumar ◽  
Rajesh V. ◽  
K. Raghu

The benefits of data analytics and Hadoop in application areas where vast volumes of data move in and out are examined and exposed in this report. Developing countries with large populations, such as India, face several challenges in the field of healthcare, including rising costs, addressing the needs of economically disadvantaged people, gaining access to hospitals, and conducting medical research, especially during epidemics. This chapter discusses the role of big data analytics and Hadoop, as well as their effect on providing healthcare services to all at the lowest possible cost.


Author(s):  
Gunasekar Thangarasu ◽  
Kayalvizhi Subramanian

<p class="0abstract">The big data analytics plays a pivotal role in the field of healthcare services and research to facilitate better service to the patients. It has provided tools to accumulate, manage, analysis the structured and unstructured data produced by the healthcare systems. Recently the utilization of big data analytics has been increased in the healthcare industry for assisting the process of diagnosing diseases and care delivery. However, the adoption and research development of big data analysis in the healthcare industry is still slow down due to facing some fundamental problems inherent within the big data paradigm. In this study, addresses these problems which focus on the upcoming and promising areas of medical research and proposed a novel big data analytics approach using Apache Spark. The proposed approach will improve care delivery in the healthcare industry. Big data analytics can continually evaluate clinical data in order to improve the effective practices of physicians and improved patient care.</p>


Author(s):  
Pijush Kanti Dutta Pramanik ◽  
Saurabh Pal ◽  
Moutan Mukhopadhyay

Like other fields, the healthcare sector has also been greatly impacted by big data. A huge volume of healthcare data and other related data are being continually generated from diverse sources. Tapping and analysing these data, suitably, would open up new avenues and opportunities for healthcare services. In view of that, this paper aims to present a systematic overview of big data and big data analytics, applicable to modern-day healthcare. Acknowledging the massive upsurge in healthcare data generation, various ‘V's, specific to healthcare big data, are identified. Different types of data analytics, applicable to healthcare, are discussed. Along with presenting the technological backbone of healthcare big data and analytics, the advantages and challenges of healthcare big data are meticulously explained. A brief report on the present and future market of healthcare big data and analytics is also presented. Besides, several applications and use cases are discussed with sufficient details.


Author(s):  
Mohd Vasim Ahamad ◽  
Misbahul Haque ◽  
Mohd Imran

In the present digital era, more data are generated and collected than ever before. But, this huge amount of data is of no use until it is converted into some useful information. This huge amount of data, coming from a number of sources in various data formats and having more complexity, is called big data. To convert the big data into meaningful information, the authors use different analytical approaches. Information extracted, after applying big data analytics methods over big data, can be used in business decision making, fraud detection, healthcare services, education sector, machine learning, extreme personalization, etc. This chapter presents the basics of big data and big data analytics. Big data analysts face many challenges in storing, managing, and analyzing big data. This chapter provides details of challenges in all mentioned dimensions. Furthermore, recent trends of big data analytics and future directions for big data researchers are also described.


Author(s):  
Zhaohao Sun ◽  
Andrew Stranieri

Intelligent analytics is an emerging paradigm in the age of big data, analytics, and artificial intelligence (AI). This chapter explores the nature of intelligent analytics. More specifically, this chapter identifies the foundations, cores, and applications of intelligent big data analytics based on the investigation into the state-of-the-art scholars' publications and market analysis of advanced analytics. Then it presents a workflow-based approach to big data analytics and technological foundations for intelligent big data analytics through examining intelligent big data analytics as an integration of AI and big data analytics. The chapter also presents a novel approach to extend intelligent big data analytics to intelligent analytics. The proposed approach in this chapter might facilitate research and development of intelligent analytics, big data analytics, business analytics, business intelligence, AI, and data science.


Author(s):  
Mimoh Ojha

Abstract: This paper gives an insight of how information and communications technology (ICT) in combination with big data analytics can help to improve healthcare services in Madhya Pradesh, which is a state in India having approximately 75 million populations. With ongoing projects like ‘Digital India’ which will allow computerization of hospitals and digitization of healthcare data. Digital India coupled with ICT, can play an indispensable role in providing effective healthcare services through e-health application like electronic health record, e-prescription, computerized physician order entry, telemedicine, mhealth along with the network like State wide area network (SWAN) and National health information network which will allow sharing of healthcare records across the network. Data stored through e-health application is of huge size having different formats which makes it difficult to perform analytics on it. But with big data analytics we can perform analytics on large voluminous healthcare data and useful result obtained from data analytics, patients can be given better and specific treatments. It will also help doctors to exchange their knowledge and treatment practices. This paper also illustrates a case study on M.Y. hospital located in Indore, Madhya Pradesh. Keywords: ICT, E-health, Digital India, SWAN, CUG, Big Data Analytics.


Sign in / Sign up

Export Citation Format

Share Document