Big Data Analytics for Improved Care Delivery in the Healthcare Industry (original) (raw)

Apache Spark and Hadoop Based Big Data Processing System for Clinical Research

2018

Usage of big data which is related to medical filed is gaining popularity among healthcare services and for clinical research. Medical field is one of the largest areas which is generating enormous amount and varieties of data. Traditional systems are incapable of handling such big data which is characterized by volume, variety, velocity, veracity and values (5 V’s). To process this vast amount of data we need a framework which can parallel process the data by utilizing the clusters of commodity hardware. This hardware should be reliable, faulttolerant. Apache Spark is a fast, in-memory data processing engine with elegant and expressive development APIs to allow data workers to efficiently execute streaming, machine learning or SQL workloads that require fast iterative access to datasets. In the Hadoop framework we can develop MapReduce applications which can scale up from single node to thousands of machines. This paper investigates the big data which is used in clinical research t...

Application of Big data for medical data analysis using Hadoop Environment20200218 79769 1im121u

Springer, 2018

Big Data (BDA) is progressively turning into a slanting practice that numerous associations are receiving with the motivation behind developing important data from Big Data. The term Big Data is likewise used to catch the openings and difficulties confronting all scientists in overseeing, examining, and incorporating datasets of differing information compose. In this paper we mention how the healthcare factor become more advance in modern world. This includes that the health care data should be properly analyzed so that we can deduce that in which group or gender, diseases attack the most. This beneficial outputs which include: getting the health care analysis in various forms. Thus this concept of analytics should be implemented with a view of future use. Beyond improving profits and cutting down on wasted overhead, Big Data in healthcare is being used to predict epidemics, cure disease, improve quality of life and avoid preventable deaths. With the world's population increasing and everyone living longer, models of treatment delivery are rapidly changing, and many of the decisions behind those changes are being driven by data. The drive now is to understand as much about a patient as possible, as early in their life as possible hopefully picking up warning signs of serious illness at an early enough stage that treatment is far more simple (and less expensive) than if it had not been spotted until later. Abstract. Big Data (BDA) is progressively turning into a slanting practice that numerous associations are receiving with the motivation behind developing important data from Big Data. The term Big Data is likewise used to catch the openings and difficulties confronting all scientists in overseeing, examining, and incorporating datasets of differing information compose. In this paper we mention how the healthcare factor become more advance in modern world. This includes that the health care data should be properly analyzed so that we can deduce that in which group or gender, diseases attack the most. This beneficial outputs which include: getting the health care analysis in various forms. Thus this concept of analytics should be implemented with a view of future use. Beyond improving profits and cutting down on wasted overhead, Big Data in healthcare is being used to predict epidemics, cure disease, improve quality of life and avoid preventable deaths. With the world's population increasing and everyone living longer, models of treatment delivery are rapidly changing, and many of the decisions behind those changes are being driven by data. The drive now is to understand as much about a patient as possible, as early in their life as possible hopefully picking up warning signs of serious illness at an early enough stage that treatment is far more simple (and less expensive) than if it had not been spotted until later.

Big Data Analytics in Healthcare: A survey

Like Oxygen, the world is surrounded by data today. The quantity of data that we harvest and eat up is thriving aggressively in the digitized world. Increasing use of new innovations and social media generate vast amount of data that can earn splendid information if properly analyzed. This large dataset generally known as big data, do not fit in traditional databases because of its' rich size. Organizations need to manage and analyze big data for better decision making and outcomes. So, big data analytics is receiving a great deal of attention today. In healthcare, big data analytics has the possibility of advanced patient care and clinical decision support. In this paper, we review the background and the various methods of big data analytics in healthcare. This paper also elaborates various platforms and algorithms for big data analytics and discussion on its advantages and challenges. This survey winds up with a discussion of challenges and future directions.

Apache Spark in Healthcare: Advancing Data-Driven Innovations and Better Patient Care

International Journal of Advanced Computer Science and Applications

The enormous amounts of data produced in the healthcare sector are managed and analyzed with the help of Apache Spark, an open-source distributed computing system. This case study examines how Spark is utilized in the healthcare industry to produce data-driven innovations and enhance patient care. The report gives a general introduction of Spark's architecture, advantages, and healthcare use cases, such as managing electronic health records, predictive analytics for disease outbreaks, individualized medicine, medical image analysis, and remote patient monitoring. Additionally, it contains several case studies that highlight Spark's effects on lowering hospital readmission rates, detecting sepsis earlier, enhancing cancer research and therapy, and speeding up drug discovery. The report also identifies obstacles with data security and privacy, scalability and infrastructure, data integration and quality, labor and skills shortages, and other aspects of employing Spark in healthcare. Spark has overcome these obstacles by enabling efficient data-driven decision-making processes and enhancing patient outcomes, revolutionizing healthcare solutions. Additionally, the study looks at potential future advancements in healthcare, including the use of Spark with AI and ML, real-time analytics, the Internet of Medical Things (IoMT), enhanced interoperability and data sharing, and ethical standards. In conclusion, healthcare businesses can fully utilize Spark to transform their data into actionable insights that will enhance patient care and boost the efficiency of healthcare systems.

Big data analytics in the health sector: challenges and potentials

Management:Journal of Sustainable Business and Management Solutions in Emerging Economies, 2019

The introduction of the Big Data concept in the healthcare sector points to a major challenge and potential. Motivation: Our goal is to indicate the importance of analyzing and processing large amounts of data that go beyond the typical ways of storing and processing information. Тhе data have their own characteristics: volume, velocity and variety. There are different structures. Analysis of these data is possible with the Big Data concept. Its importance is most evident in the health sector, because the preservation of the health status of the population depends on adequate data analysis. Idea: The idea of the paper is that big health data analytics contributes to a better quality provision of health services. The process is more efficient and effective. Data: Health analytics suggests that more and more resources are being utilized globally. In order to achieve improvements, health analytics and Big data concepts play a vital role in overcoming the obstacles, working more efficiently and aiming at providing adequate medical care. Tools: The Big data concept will help identify patients with developed chronic diseases. Big data can identify outbreaks of flu or other epidemics in real time. In this way, they are managed by the healthcare system, reducing overall healthcare costs over time, and increasing revenues. Findings: A key policy challenge is to improve the outcomes of the healthcare system, data collection and analysis, security, storage and transfers. Big data are the potential to improve quality of care, improve predictions of diseases, improve the treatment methods, reduce costs. Contribution: This paper points to the challenges and potentials of Big Health Data analytics and formulates good reasons to apply the Big Data concept in healthcare.

Big Data Analysis and Management in Healthcare

International Research Journal on Advanced Science Hub, 2021

Basically, Big Data means large volumes of data that can be used to solve problems. It has piqued people's attention over the past two decades because of the enormous potential it holds. Big data is generated, stored, and analyzed by a variety of public and private sector industries in order to enhance the services they provide. Hospital reports, patient medical records, medical test outcomes, and internet of things applications are all examples of big data outlets in the healthcare industry. Biomedical research often produces a large amount of big data that is pertinent to public health. To extract useful information from this data, it must be properly managed and analyzed. Otherwise, finding solutions by analyzing big data quickly becomes impossible. The ability to identify trends and transform large amounts of data into actionable information for precision , medicine and decision makers is at the heart of Big Data's potential in healthcare. In a variety of areas, the use of Big Data in healthcare is now offering solutions for optimizing patient care and creating value in healthcare organizations. In this paper, some big data solutions are provided for healthcare. Big Data Analytics strategies to mitigate covid-19 health disparities are provided. Finally we analyse some of the challenges with big data in healthcare.

BigData Analysis in Healthcare: Apache Hadoop , Apache spark and Apache Flink

Frontiers in Health Informatics, 2019

Introduction: Health care data is increasing. The correct analysis of such data will improve the quality of care and reduce costs. This kind of data has certain features such as high volume, variety, high-speed production, etc. It makes it impossible to analyze with ordinary hardware and software platforms. Choosing the right platform for managing this kind of data is very important. The purpose of this study is to introduce and compare the most popular and most widely used platform for processing big data, Apache Hadoop MapReduce, and the two Apache Spark and Apache Flink platforms, which have recently been featured with great prominence.Material and Methods: This study is a survey whose content is based on the subject matter search of the Proquest, PubMed, Google Scholar, Science Direct, Scopus, IranMedex, Irandoc, Magiran, ParsMedline and Scientific Information Database (SID) databases, as well as Web reviews, specialized books with related keywords and standard. Finally, 80 arti...

Big Data Analytics for Medical Applications

International Journal of Modern Education and Computer Science, 2018

Big Data is an accumulation of data sets which are abundant and intricate in character. They comprise both structured and unstructured data that evolve abundant, so speedy they are not convenient by classical relational database systems or current analytical tools. Big Data Analytics is not linearly able to expand. It is a predefined schema. Now big data is very helpful for backup of data not for everything else. There is always a data introducing. It also helps to solve India's big problems. It also helps to fill the data gap. Health care is the conservation or advancement of health along the avoidance, interpretation and medical care of disorder, bad health, abuse, and other substantial and spiritual deterioration in mortal. Health care is expressed by health experts in united health experts, specialists, physician associates, midwife , nursing, antibiotic, pharmacy, psychology and other health. This paper focuses on providing information in the area of big data analytics and its application in medical domain. Further it includes introduction, Challenging aspects and concerns, Big Data Analytics in use, Technical Specification, Research application, Industry application and Future applications.

BIG DATA ANALYTICS IN HEALTHCARE : A SURVEY Gemson

2015

Like Oxygen, the world is surrounded by data today. The quantity of data that we harvest and eat up is thriving aggressively in the digitized world. Increasing use of new innovations and social media generate vast amount of data that can earn splendid information if properly analyzed. This large dataset generally known as big data, do not fit in traditional databases because of its’ rich size. Organizations need to manage and analyze big data for better decision making and outcomes. So, big data analytics is receiving a great deal of attention today. In healthcare, big data analytics has the possibility of advanced patient care and clinical decision support. In this paper, we review the background and the various methods of big data analytics in healthcare. This paper also elaborates various platforms and algorithms for big data analytics and discussion on its advantages and challenges. This survey winds up with a discussion of challenges and future directions.

Big Data Analytics in Healthcare: A Review

2021

In recent years, huge amounts of structured, unstructured, and semi-structured data have been generated by various sectors around the world and, neither of this data is homogeneous. This enormous amount of data, referred to as ‘big data’, has started to play a pivotal role in the evolution of healthcare practices and research. In this paper, we discuss how by rapid digitalization along with other factors, the health industry has been confronted with the need to handle the big data being produced rapidly at an exponential speed. Big data analytics tools play an essential role to analyze and integrate large volumes of data, which otherwise might have become useless or taken more time to give value. The usage and challenges of big data in healthcare is also addressed. Keywords—Big Data, Big Data Analytics, Hadoop, Healthcare