scholarly journals A Comprehensive Big Data Analytics Based Framework for Premature Recognition of Breast Cancer

2020 ◽  
Vol 9 (3) ◽  
pp. 2188-2192
Keyword(s):  
Breast Cancer ◽  
Big Data ◽  
Data Analytics ◽  
Predictive Analytics ◽  
Big Data Analytics ◽  
Machine Learning Algorithms ◽  
Massive Data ◽  
Healthcare Industry ◽  
Rapid Pace ◽  
Comprehensive Framework

Healthcare industry is fast growing and expanding in rapid pace. The volume and veracity of data generated in the industry is massive and requires huge storages and handling capability. Big data is empowered with such robust abilities and hence most suitable for handing large amount of data. Further, hese data could be utilized towards building predictive and forecasting models. Breast cancer is a deadly form of cancer majorly affecting women around the globe. The concept of big data and predictive analytics is being explored in the paper towards early diagnosis of breast cancer. This paper surveys various literatures available on application of big data analysis for breast cancer. Subsequently a comprehensive framework is being proposed based on the gaps identified. Different machine learning algorithms which can be applied in the framework is also detailed in the paper. Such frameworks when implemented will greatly help in handling the massive data available and aid in early detection of breast cancer.

scholarly journals REVIEW OF MACHINE LEARNING TECHNIQUES FOR VOLUMINOUS INFORMATION MANAGEMENT

2019 ◽  
Vol 2019 (2) ◽  
pp. 103-112
Author(s):  
Dr. Pasumpon pandian
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Data Analytics ◽  
Learning Algorithms ◽  
Big Data Analytics ◽  
Machine Learning Algorithms ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
Technological Growth ◽  
Rapid Pace

The recent technological growth at a rapid pace has paved way for the big data that denotes to the exponential growth of the information’s. The big data analytics are the trending concepts that have emerged as the promising technology that offers more enhanced perceptions from the huge set of the data that have been produced from the diverse areas. The review in the paper proceeds with the methods of the big-data-analytics and the machine-learning in handling, the huge set of data flow. The overview of the utilization of the machine-learning algorithms in the analytics of high voluminous data would provide with the deeper and the richer analysis of the huge set of information gathered to extract the valuable and turn it into actionable information’s. The paper is to review the part of machine-learning algorithms in the analytics of high voluminous data

Applications of Big Data Analytics in Healthcare Management Systems

2021 ◽  
Vol 23 (06) ◽  
pp. 1167-1182
Author(s):  
Shreyas Nopany ◽  
◽  
Prof. Manonmani S ◽  
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Healthcare Management ◽  
Healthcare Sector ◽  
Future Research ◽  
Healthcare Industry ◽  
Strategy Formulation ◽  
Data Governance ◽  
Number Of Patients

The healthcare industry has become increasingly demanding in recent years. The growing number of patients makes it difficult for doctors and staff to manage their work effectively. In order to achieve their objectives, data analysts collect a large amount of data, analyze it, and use it to derive valuable insights. Data analytics may become a promising solution as healthcare industry demands increase. The paper discusses the challenges of data analytics in the healthcare sector and the benefits of using big data for healthcare analytics. Aside from focusing on the opportunities that big data analytics has in the healthcare sector, the paper will also discuss data governance, strategy formulation, and improvements to IT infrastructure. Implementation techniques include Hadoop, HDFS, MapReduce, and Apache in Big Data Analytics. A Healthcare Management System can be categorized into five divisions, namely, Drug discovery, Disease prevention, diagnosis and treatment, Hospital operations, post-care, requiring comprehensive data management. Big Data analysis support transformation is identified as a required component in future research for the application of Big Data in HealthCare.

Big Data Analytics in the Healthcare Industry

2020 ◽  
pp. 160-178
Author(s):  
Arulkumar Varatharajan ◽  
Selvan C. ◽  
Vimalkumar Varatharajan
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Human Services ◽  
Big Data Analytics ◽  
Healthcare Industry ◽  
Multimodal Data ◽  
Design Structure ◽  
Costs Of Treatment ◽  
The Way

Big Data has changed the way we manage, analyze and impact the data information in any industry. A champion among the most promising zones where it will, in general, be associated with takeoff progress is therapeutic medicinal administrations. Administration examinations can diminish costs of treatment, foresee flare-ups of pestilences, keep up a key separation from preventable diseases and improve individual fulfillment overall. The chapter depicts the beginning field of a huge information investigation in human services, talks about the advantages, diagrams a design structure and approach, portrays models revealed in the writing, quickly examines the difficulties, and offers ends. A continuous examination which targets the utilization of tremendous volumes of remedial data information while combining multimodal data information from various sources is discussed. Potential locales of research inside this field which can give noteworthy impact on medicinal administrations movement are in like manner dissected.

Big Data Applications in Healthcare

Big Data ◽  
2016 ◽  
pp. 1247-1259 ◽  
Author(s):  
Jayanthi Ranjan
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Healthcare Industry ◽  
Big Data Applications ◽  
Business Functions ◽  
Automated Algorithms ◽  
Almost All ◽  
Tools And Techniques ◽  
Research Centres

Big data is in every industry. It is being utilized in almost all business functions within these industries. Basically, it creates value by converting human decisions into transformed automated algorithms using various tools and techniques. In this chapter, the authors look towards big data analytics from the healthcare perspective. Healthcare involves the whole supply chain of industries from the pharmaceutical companies to the clinical research centres, from the hospitals to individual physicians, and anyone who is involved in the medical arena right from the supplier to the consumer (i.e. the patient). The authors explore the growth of big data analytics in the healthcare industry including its limitations and potential.

Big Data Analytics in Healthcare

2021 ◽  
pp. 85-98
Author(s):  
Sam Goundar ◽  
Karpagam Masilamani ◽  
Akashdeep Bhardwaj ◽  
Chandramohan Dhasarathan
Keyword(s):  
Big Data ◽  
Big Data Analytics ◽  
Health Data ◽  
Massive Data ◽  
Healthcare Industry ◽  
Health Records ◽  
Healthcare Data ◽  
Data Formats ◽  
Analytical Tools ◽  
Different Sources

This chapter provides better understanding and use-cases of big data in healthcare. The healthcare industry generates lot of data every day, and without proper analytical tools, it is quite difficult to extract meaningful data. It is essential to understand big data tools since the traditional devices don't maintain this vast data, and big data solves the major issue in handling massive healthcare data. Health data from numerous health records are collected from various sources, and this massive data is put together to form the big data. Conventional database cannot be used in this purpose due to the diversity in data formats, so it is difficult to merge, and so it is quite impossible to process. With the use of big data this problem is solved, and it can process highly variable data from different sources.

Business Analytics and Big Data

2015 ◽  
pp. 1-11 ◽  
Author(s):  
Dennis T. Kennedy ◽  
Dennis M. Crossen ◽  
Kathryn A. Szabat
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Quantitative Methods ◽  
Business Processes ◽  
Predictive Analytics ◽  
Big Data Analytics ◽  
Database Systems ◽  
Three Dimensions ◽  
Business Analytics ◽  
The People

Big Data Analytics has changed the way organizations make decisions, manage business processes, and create new products and services. Business analytics is the use of data, information technology, statistical analysis, and quantitative methods and models to support organizational decision making and problem solving. The main categories of business analytics are descriptive analytics, predictive analytics, and prescriptive analytics. Big Data is data that exceeds the processing capacity of conventional database systems and is typically defined by three dimensions known as the Three V's: Volume, Variety, and Velocity. Big Data brings big challenges. Big Data not only has influenced the analytics that are utilized but also has affected technologies and the people who use them. At the same time Big Data brings challenges, it presents opportunities. Those who embrace Big Data and effective Big Data Analytics as a business imperative can gain competitive advantage.

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