This document discusses opportunities and challenges of big data in the healthcare sector. It begins by introducing big data - describing its volume, velocity and variety characteristics. It then outlines various sources of big data in healthcare like electronic health records, medical images, and sensor data. The document explores opportunities like decreasing costs, personalized medicine, and preventative care. Challenges discussed include privacy concerns, data aggregation issues, and the need for expert knowledge. Finally, it presents technologies that support big data analytics in healthcare such as Hadoop, Hive and Cassandra.
The application of big data in health care is a fast-growing field, with many discoveries and methodologies published in the last five years. Big data refers to datasets that are not only big but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Moreover, medical data is one of the most growing data, as it is obtained from Electronic Health Records (EHRs) or patients themselves. Due to the rapid growth of such medical data, we need to provide suitable tools and techniques in order to handle and extract value and knowledge from these datasets to improve the quality of patient care and reduces healthcare costs. Furthermore, such value can be provided using big data analytics, which is the application of advanced analytics techniques on big data. This paper presents an overview of big data content, sources, technologies, tools, and challenges in health care. It also intends to identify the strategies to overcome the challenges.
Big Data, CEP and IoT : Redefining Holistic Healthcare Information Systems an...Tauseef Naquishbandi
Healthcare industry has been a significant area for innovative application of various technologies over decades. Being an area of social relevance governmental spending on healthcare have always been on the rise over the years. Event Processing (CEP) has been in use for many years for situational awareness and response generation. Computing technologies have played an important role in improvising several aspects of healthcare. Recently emergent technology paradigms of Big Data, Internet of Things (IoT) and Complex Event Processing (CEP) have the potential not only to deal with pain areas of healthcare domain but also to redefine healthcare offerings. This paper aims to lay the groundwork for a healthcare system which builds upon integration of Big Data, CEP and IoT.
This white paper offers a detailed perspective on how big data is impacting the healthcare industry and its underlying implication on the industry as a whole. It outlines the role of big data in healthcare, its benefits, core components and challenges faced by the healthcare sector towards full-fledged adoption & implementation.
Application of Big Data in Medical Science brings revolution in managing heal...IJEEE
Big Data can be combined with new technology to bring about positive conversion in the health care segment. A technology aimed at making Big Data analytics a certainty will act as a key element in transforming the way the health care industry operates today. The study and analysis of Big Data can be used for tracking and managing population health care effectively and efficiently. In ten years, eighty percent of the work people do in medicine will be replaced by technology. And medicine will not look anything like what it does today. Healthcare will change enormously as it becomes a data-driven industry. But the magnitude of the data, the speed at which it’s growing and the threat it could pose to individual privacy mean mastering "big data" is one of biomedicine's most pressing challenges. Hiding within those mounds of data is knowledge that could change the life of a patient, or change the world. This also plays a vital role in delivering preventive care. Health care will change a great deal as it becomes a data- driven industry. But the size of the data, the speed at which it’s growing and the threat it could cause to individual privacy mean mastering it is one of biomedicine's most critical challenges. In this research paper we will discuss problems faced by big data, obstacles in using big data in the health industry, how big Data analytics can take health care to a new level by enhancing the overall quality of patient care.
Big Data Analytics for Smart Health CareEshan Bhuiyan
Healthcare big data refers to the vast quantities of data that is now available to healthcare providers.
As a response to the digitization of healthcare information and the rise of value-based care, the industry has taken advantage of big data and analytics to make strategic business decisions.
A Case Analysis on Involvement of Big Data during Natural Disaster and Pandem...YogeshIJTSRD
Big data is an upcoming technology and requires utmost care for an efficient and smooth implementation of the technology. In case of healthcare the most challenging part of big data is the privacy, data security, handling large volume of medical imaging data and data leakage. It can be useful to this sector when big data is made structured, relevant, smart and accessible and the managers should give importance to the strategic and business value of big data technology rather than only concentrating at the technological aspect of the implementation. The use of big data in natural disasters and pandemics helps to understand and make better decision with fast processing of the data that are collected through various sources such as social media, sensors and other internet activities. This paper tries to focus on effective involvement of Big Data in natural disaster and pandemic and also identify the current and future use of Big Data in health care sector. The paper identifies the critical aspects which are used for Big data implementation and describe ways to handle the challenges related to it. Mr. Bibin Mathew | Dr. Swati John "A Case Analysis on Involvement of Big Data during Natural Disaster and Pandemics and its Uses in the Health Care Sector" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd45049.pdf Paper URL: https://www.ijtsrd.com/management/other/45049/a-case-analysis-on-involvement-of-big-data-during-natural-disaster-and-pandemics-and-its-uses-in-the-health-care-sector/mr-bibin-mathew
Benefits of Big Data in Health Care A Revolutionijtsrd
Lifespan of a normal human is increasing with the world population and it produces new challenge in health care. big data change the method of data management ,leverage data and analyzing data.with the help of big data we can reduces the costs of treatment, reducing medication and provide better treatment with predictive analytics. Health related data collected from various sources like electronic health record EHR ,medical imaging system, genomic sequencing, pay of records, pharmaceutical research , and medical devices, etc. are refers to as big data in healthcare. Dr. Ritushree Narayan ""Benefits of Big Data in Health Care: A Revolution"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd22974.pdf
Paper URL: https://www.ijtsrd.com/computer-science/data-miining/22974/benefits-of-big-data-in-health-care-a-revolution/dr-ritushree-narayan
The application of big data in health care is a fast-growing field, with many discoveries and methodologies published in the last five years. Big data refers to datasets that are not only big but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Moreover, medical data is one of the most growing data, as it is obtained from Electronic Health Records (EHRs) or patients themselves. Due to the rapid growth of such medical data, we need to provide suitable tools and techniques in order to handle and extract value and knowledge from these datasets to improve the quality of patient care and reduces healthcare costs. Furthermore, such value can be provided using big data analytics, which is the application of advanced analytics techniques on big data. This paper presents an overview of big data content, sources, technologies, tools, and challenges in health care. It also intends to identify the strategies to overcome the challenges.
Big Data, CEP and IoT : Redefining Holistic Healthcare Information Systems an...Tauseef Naquishbandi
Healthcare industry has been a significant area for innovative application of various technologies over decades. Being an area of social relevance governmental spending on healthcare have always been on the rise over the years. Event Processing (CEP) has been in use for many years for situational awareness and response generation. Computing technologies have played an important role in improvising several aspects of healthcare. Recently emergent technology paradigms of Big Data, Internet of Things (IoT) and Complex Event Processing (CEP) have the potential not only to deal with pain areas of healthcare domain but also to redefine healthcare offerings. This paper aims to lay the groundwork for a healthcare system which builds upon integration of Big Data, CEP and IoT.
This white paper offers a detailed perspective on how big data is impacting the healthcare industry and its underlying implication on the industry as a whole. It outlines the role of big data in healthcare, its benefits, core components and challenges faced by the healthcare sector towards full-fledged adoption & implementation.
Application of Big Data in Medical Science brings revolution in managing heal...IJEEE
Big Data can be combined with new technology to bring about positive conversion in the health care segment. A technology aimed at making Big Data analytics a certainty will act as a key element in transforming the way the health care industry operates today. The study and analysis of Big Data can be used for tracking and managing population health care effectively and efficiently. In ten years, eighty percent of the work people do in medicine will be replaced by technology. And medicine will not look anything like what it does today. Healthcare will change enormously as it becomes a data-driven industry. But the magnitude of the data, the speed at which it’s growing and the threat it could pose to individual privacy mean mastering "big data" is one of biomedicine's most pressing challenges. Hiding within those mounds of data is knowledge that could change the life of a patient, or change the world. This also plays a vital role in delivering preventive care. Health care will change a great deal as it becomes a data- driven industry. But the size of the data, the speed at which it’s growing and the threat it could cause to individual privacy mean mastering it is one of biomedicine's most critical challenges. In this research paper we will discuss problems faced by big data, obstacles in using big data in the health industry, how big Data analytics can take health care to a new level by enhancing the overall quality of patient care.
Big Data Analytics for Smart Health CareEshan Bhuiyan
Healthcare big data refers to the vast quantities of data that is now available to healthcare providers.
As a response to the digitization of healthcare information and the rise of value-based care, the industry has taken advantage of big data and analytics to make strategic business decisions.
A Case Analysis on Involvement of Big Data during Natural Disaster and Pandem...YogeshIJTSRD
Big data is an upcoming technology and requires utmost care for an efficient and smooth implementation of the technology. In case of healthcare the most challenging part of big data is the privacy, data security, handling large volume of medical imaging data and data leakage. It can be useful to this sector when big data is made structured, relevant, smart and accessible and the managers should give importance to the strategic and business value of big data technology rather than only concentrating at the technological aspect of the implementation. The use of big data in natural disasters and pandemics helps to understand and make better decision with fast processing of the data that are collected through various sources such as social media, sensors and other internet activities. This paper tries to focus on effective involvement of Big Data in natural disaster and pandemic and also identify the current and future use of Big Data in health care sector. The paper identifies the critical aspects which are used for Big data implementation and describe ways to handle the challenges related to it. Mr. Bibin Mathew | Dr. Swati John "A Case Analysis on Involvement of Big Data during Natural Disaster and Pandemics and its Uses in the Health Care Sector" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd45049.pdf Paper URL: https://www.ijtsrd.com/management/other/45049/a-case-analysis-on-involvement-of-big-data-during-natural-disaster-and-pandemics-and-its-uses-in-the-health-care-sector/mr-bibin-mathew
Benefits of Big Data in Health Care A Revolutionijtsrd
Lifespan of a normal human is increasing with the world population and it produces new challenge in health care. big data change the method of data management ,leverage data and analyzing data.with the help of big data we can reduces the costs of treatment, reducing medication and provide better treatment with predictive analytics. Health related data collected from various sources like electronic health record EHR ,medical imaging system, genomic sequencing, pay of records, pharmaceutical research , and medical devices, etc. are refers to as big data in healthcare. Dr. Ritushree Narayan ""Benefits of Big Data in Health Care: A Revolution"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd22974.pdf
Paper URL: https://www.ijtsrd.com/computer-science/data-miining/22974/benefits-of-big-data-in-health-care-a-revolution/dr-ritushree-narayan
Gain insights from data analytics and take action! Learn why everyone is making a big deal about big data in healthcare and how data analytics creates action.
The main aim of this paper is to provide a deep analysis on the research field of healthcare data analytics., as well as highlighting some of guidelines and gaps in previous studies. This study has focused on searching relevant papers about healthcare analytics by searching in seven popular databases such as google scholar and springer using specific keywords, in order to understand the healthcare topic and conduct our literature review. The paper has listed some data analytics tools and techniques that have been used to improve healthcare performance in many areas such as medical operations, reports, decision making, and prediction and prevention system. Moreover, the systematic review has showed an interesting demographic of fields of publication, research approaches, as well as outlined some of the possible reasons and issues associated with healthcare data analytics, based on geographical distribution theme. Snober Jon | Shafqat Manzoor | Beenish Bashir | Monisa Nazir "Data Science in Healthcare" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-1 , December 2021, URL: https://www.ijtsrd.com/papers/ijtsrd47870.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/47870/data-science-in-healthcare/snober-jon
Big data is to be implemented in as full way in real-time; it is still in a research. People
need to know what to do with enormous data. Insurance agencies are actively participating for the
analysis of patient's data which could be used to extract some useful information. Analysis is done in
term of discharge summary, drug & pharma, diagnostics details, doctor’s report, medical history,
allergies & insurance policies which are made by the application of map reduce and useful data is
extracted. We are analysing more number of factors like disease Types with its agreeing reasons,
insurance policy details along with sanctioned amount, family grade wise segregation.
Keywords: Big data, Stemming, Map reduce Policy and Hadoop.
Big Data Risks and Rewards (good length and at least 3-4 references .docxtangyechloe
Big Data Risks and Rewards (good length and at least 3-4 references everything in APA 7 format)
When you wake in the morning, you may reach for your cell phone to reply to a few text or email messages that you missed overnight. On your drive to work, you may stop to refuel your car. Upon your arrival, you might swipe a key card at the door to gain entrance to the facility. And before finally reaching your workstation, you may stop by the cafeteria to purchase a coffee.
From the moment you wake, you are in fact a data-generation machine. Each use of your phone, every transaction you make using a debit or credit card, even your entrance to your place of work, creates data. It begs the question: How much data do you generate each day? Many studies have been conducted on this, and the numbers are staggering: Estimates suggest that nearly 1 million bytes of data are generated every second for every person on earth.
As the volume of data increases, information professionals have looked for ways to use big data—large, complex sets of data that require specialized approaches to use effectively. Big data has the potential for significant rewards—and significant risks—to healthcare. In this Discussion, you will consider these risks and rewards.
To Prepare:
Review the Resources and reflect on the web article
Big Data Means Big Potential, Challenges for Nurse Execs
.
Reflect on your own experience with complex health information access and management and consider potential challenges and risks you may have experienced or observed.
By Day 3 of Week 5
Post
a description of at least one potential benefit of using big data as part of a clinical system and explain why. Then, describe at least one potential challenge or risk of using big data as part of a clinical system and explain why. Propose at least one strategy you have experienced, observed, or researched that may effectively mitigate the challenges or risks of using big data you described. Be specific and provide examples.
By Day 6 of Week 5
Respond
to at least
two
of your colleagues
* on two different days
, by offering one or more additional mitigation strategies or further insight into your colleagues’ assessment of big data opportunities and risks.
Click on the
Reply
button below to reveal the textbox for entering your message. Then click on the
Submit
button to post your message.
*Note:
Throughout this program, your fellow students are referred to as colleagues.
Michea Discussion ( in APA 7 format and at least 2-3 references)
With the fast growing pace of technological advancement in the health care sector, daily operations of the institution helps generate millions of data that over time needs proper channels of transmission, storage, processing, assimilation and utilization. Following from the vast amount of data generated, some of its benefits includes but is not limited to functioning as a pattern discovery aid with relation to the amount of variance or similarity in .
Big Data Analytics using in Healthcare Management Systemijtsrd
Big data is the new technology for healthcare management system. Present day's big data analytics are using in everywhere because of its good data management and its large storage capacity. In hospital managements the patients and doctors record keeping safe is the important role in healthcare system. In worldwide the big data method is extended use in the area of medicine and healthcare system. In this sector so many problems are there in implementing big data in healthcare system especially in relation to securities, privacy matters, standard records, good governance, managing of data, data storing and maintenance, etc. It is critical that these challenges to overcome before big data can be implemented successfully in healthcare. The amount of data being digitally collected and stored safely in big data Hadoop clusters. This paper introduces healthcare data, big data in healthcare systems, applications, advantages, issues of Big Data analytics in healthcare sector. Gagana H. S | Bhavani B. T | Gouthami H. S "Big Data Analytics using in Healthcare Management System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31014.pdf Paper Url :https://www.ijtsrd.com/computer-science/other/31014/big-data-analytics-using-in-healthcare-management-system/gagana-h-s
Call for Research Articles - 5th International Conference on Artificial Intel...ijistjournal
5th International Conference on Artificial Intelligence and Machine Learning (CAIML 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and Machine Learning. The Conference looks for significant contributions to all major fields of the Artificial Intelligence, Machine Learning in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Computer Science, Engineering and Applications.
Online Paper Submission - International Journal of Information Sciences and T...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
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Gain insights from data analytics and take action! Learn why everyone is making a big deal about big data in healthcare and how data analytics creates action.
The main aim of this paper is to provide a deep analysis on the research field of healthcare data analytics., as well as highlighting some of guidelines and gaps in previous studies. This study has focused on searching relevant papers about healthcare analytics by searching in seven popular databases such as google scholar and springer using specific keywords, in order to understand the healthcare topic and conduct our literature review. The paper has listed some data analytics tools and techniques that have been used to improve healthcare performance in many areas such as medical operations, reports, decision making, and prediction and prevention system. Moreover, the systematic review has showed an interesting demographic of fields of publication, research approaches, as well as outlined some of the possible reasons and issues associated with healthcare data analytics, based on geographical distribution theme. Snober Jon | Shafqat Manzoor | Beenish Bashir | Monisa Nazir "Data Science in Healthcare" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-1 , December 2021, URL: https://www.ijtsrd.com/papers/ijtsrd47870.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/47870/data-science-in-healthcare/snober-jon
Big data is to be implemented in as full way in real-time; it is still in a research. People
need to know what to do with enormous data. Insurance agencies are actively participating for the
analysis of patient's data which could be used to extract some useful information. Analysis is done in
term of discharge summary, drug & pharma, diagnostics details, doctor’s report, medical history,
allergies & insurance policies which are made by the application of map reduce and useful data is
extracted. We are analysing more number of factors like disease Types with its agreeing reasons,
insurance policy details along with sanctioned amount, family grade wise segregation.
Keywords: Big data, Stemming, Map reduce Policy and Hadoop.
Big Data Risks and Rewards (good length and at least 3-4 references .docxtangyechloe
Big Data Risks and Rewards (good length and at least 3-4 references everything in APA 7 format)
When you wake in the morning, you may reach for your cell phone to reply to a few text or email messages that you missed overnight. On your drive to work, you may stop to refuel your car. Upon your arrival, you might swipe a key card at the door to gain entrance to the facility. And before finally reaching your workstation, you may stop by the cafeteria to purchase a coffee.
From the moment you wake, you are in fact a data-generation machine. Each use of your phone, every transaction you make using a debit or credit card, even your entrance to your place of work, creates data. It begs the question: How much data do you generate each day? Many studies have been conducted on this, and the numbers are staggering: Estimates suggest that nearly 1 million bytes of data are generated every second for every person on earth.
As the volume of data increases, information professionals have looked for ways to use big data—large, complex sets of data that require specialized approaches to use effectively. Big data has the potential for significant rewards—and significant risks—to healthcare. In this Discussion, you will consider these risks and rewards.
To Prepare:
Review the Resources and reflect on the web article
Big Data Means Big Potential, Challenges for Nurse Execs
.
Reflect on your own experience with complex health information access and management and consider potential challenges and risks you may have experienced or observed.
By Day 3 of Week 5
Post
a description of at least one potential benefit of using big data as part of a clinical system and explain why. Then, describe at least one potential challenge or risk of using big data as part of a clinical system and explain why. Propose at least one strategy you have experienced, observed, or researched that may effectively mitigate the challenges or risks of using big data you described. Be specific and provide examples.
By Day 6 of Week 5
Respond
to at least
two
of your colleagues
* on two different days
, by offering one or more additional mitigation strategies or further insight into your colleagues’ assessment of big data opportunities and risks.
Click on the
Reply
button below to reveal the textbox for entering your message. Then click on the
Submit
button to post your message.
*Note:
Throughout this program, your fellow students are referred to as colleagues.
Michea Discussion ( in APA 7 format and at least 2-3 references)
With the fast growing pace of technological advancement in the health care sector, daily operations of the institution helps generate millions of data that over time needs proper channels of transmission, storage, processing, assimilation and utilization. Following from the vast amount of data generated, some of its benefits includes but is not limited to functioning as a pattern discovery aid with relation to the amount of variance or similarity in .
Big Data Analytics using in Healthcare Management Systemijtsrd
Big data is the new technology for healthcare management system. Present day's big data analytics are using in everywhere because of its good data management and its large storage capacity. In hospital managements the patients and doctors record keeping safe is the important role in healthcare system. In worldwide the big data method is extended use in the area of medicine and healthcare system. In this sector so many problems are there in implementing big data in healthcare system especially in relation to securities, privacy matters, standard records, good governance, managing of data, data storing and maintenance, etc. It is critical that these challenges to overcome before big data can be implemented successfully in healthcare. The amount of data being digitally collected and stored safely in big data Hadoop clusters. This paper introduces healthcare data, big data in healthcare systems, applications, advantages, issues of Big Data analytics in healthcare sector. Gagana H. S | Bhavani B. T | Gouthami H. S "Big Data Analytics using in Healthcare Management System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31014.pdf Paper Url :https://www.ijtsrd.com/computer-science/other/31014/big-data-analytics-using-in-healthcare-management-system/gagana-h-s
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Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Computer Science, Engineering and Applications.
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This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
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This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
International Journal of Information Sciences and Techniques (IJIST)ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
BRAIN TUMOR MRIIMAGE CLASSIFICATION WITH FEATURE SELECTION AND EXTRACTION USI...ijistjournal
Feature extraction is a method of capturing visual content of an image. The feature extraction is the process to represent raw image in its reduced form to facilitate decision making such as pattern classification. We have tried to address the problem of classification MRI brain images by creating a robust and more accurate classifier which can act as an expert assistant to medical practitioners. The objective of this paper is to present a novel method of feature selection and extraction. This approach combines the Intensity, Texture, shape based features and classifies the tumor as white matter, Gray matter, CSF, abnormal and normal area. The experiment is performed on 140 tumor contained brain MR images from the Internet Brain Segmentation Repository. The proposed technique has been carried out over a larger database as compare to any previous work and is more robust and effective. PCA and Linear Discriminant Analysis (LDA) were applied on the training sets. The Support Vector Machine (SVM) classifier served as a comparison of nonlinear techniques Vs linear ones. PCA and LDA methods are used to reduce the number of features used. The feature selection using the proposed technique is more beneficial as it analyses the data according to grouping class variable and gives reduced feature set with high classification accuracy.
Research Article Submission - International Journal of Information Sciences a...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
A MEDIAN BASED DIRECTIONAL CASCADED WITH MASK FILTER FOR REMOVAL OF RVINijistjournal
In this paper A Median Based Directional Cascaded with Mask (MBDCM) filter has been proposed, which is based on three different sized cascaded filtering windows. The differences between the current pixel and its neighbors aligned with four main directions are considered for impulse detection. A direction index is used for each edge aligned with a given direction. Minimum of these four direction indexes is used for impulse detection under each masking window. Depending on the minimum direction indexes among these three windows new value to substitute the noisy pixel is calculated. Extensive simulations showed that the MBDCM filter provides good performances of suppressing impulses from both gray level and colored benchmarked images corrupted with low noise level as well as for highly dense impulses. MBDCM filter gives better results than MDWCMM filter in suppressing impulses from highly corrupted digital images.
DECEPTION AND RACISM IN THE TUSKEGEE SYPHILIS STUDYijistjournal
During the twentieth century (1932-1972), white physicians representing the United States government
conducted a human experiment known as the Tuskegee Syphilis Study on black syphilis patients in Macon
County, Alabama. The creators of the study, who supported the idea of black inferiority and the concept
that black people’s bodies functioned differently from white people’s, observed the effects of a disease
called syphilis on untreated black patients in order to collect data for further research on syphilis. Black
individuals involved with the study believed that they were receiving treatment, although in truth,
treatments for syphilis were purposely held back from them. Not only this, but fluids from their bodies, such
as blood and spinal fluid, were extracted to serve as research material without their awareness of the
purpose of the collection. The physicians justified their approach by positioning it as mere observation,
asserting that they were not actively intervening with the patients participating in the experiment. However,
despite their claims of passivity, these white physicians engaged in various morally improper actions,
including deceit, which ultimately resulted in the deaths of numerous black patients who might have had a
chance at survival.
Online Paper Submission - International Journal of Information Sciences and T...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
A NOVEL APPROACH FOR SEGMENTATION OF SECTOR SCAN SONAR IMAGES USING ADAPTIVE ...ijistjournal
The SAR and SAS images are perturbed by a multiplicative noise called speckle, due to the coherent nature of the scattering phenomenon. If the background of an image is uneven, the fixed thresholding technique is not suitable to segment an image using adaptive thresholding method. In this paper a new Adaptive thresholding method is proposed to reduce the speckle noise, preserving the structural features and textural information of Sector Scan SONAR (Sound Navigation and Ranging) images. Due to the massive proliferation of SONAR images, the proposed method is very appealing in under water environment applications. In fact it is a pre- treatment required in any SONAR images analysis system. The results obtained from the proposed method were compared quantitatively and qualitatively with the results obtained from the other speckle reduction techniques and demonstrate its higher performance for speckle reduction in the SONAR images.
Call for Papers - International Journal of Information Sciences and Technique...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
The A318, A319, A320 and A321 are twin-engine subsonic medium range aircraft.
The family offers a choice of engines
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
A BIG DATA REVOLUTION IN HEALTH CARE SECTOR: OPPORTUNITIES, CHALLENGES AND TECHNOLOGICAL ADVANCEMENTS
1. International Journal of Information Sciences and Techniques (IJIST) Vol.6, No.1/2, March 2016
DOI : 10.5121/ijist.2016.6216 155
A BIG DATA REVOLUTION IN HEALTH CARE
SECTOR: OPPORTUNITIES, CHALLENGES AND
TECHNOLOGICAL ADVANCEMENTS
Sanskruti Patel and Atul Patel
Faculty of Computer Science & Applications, CHARUSAT, Changa, India
ABSTRACT
Health care sector grows tremendously in last few decades. The health care sector has generated huge
amounts of data that has huge volume, enormous velocity and vast variety. Also it comes from a variety of
new sources as hospitals are now tend to implemented electronic health record (EHR) systems. These
sources have strained the existing capabilities of existing conventional relational database management
systems. In such scenario, Big data solutions offer to harness these massive, heterogeneous and complex
data sets to obtain more meaningful and knowledgeable information.
This paper basically studies the impact of implementing the big data solutions on the healthcare sector, the
potential opportunities, challenges and available platform and tools to implement Big data analytics in
health care sector.
KEYWORDS
Big Data, Health Care, Big Data Analytics
1. INTRODUCTION
The health care sector grows rapidly in last 30 years. The healthcare industry historically has
generated large amounts of data, driven by record keeping, compliance & regulatory
requirements and patient care. While most data is stored in hard copy form, the current trend is
towards the rapid digitization of these large amounts of data. There are different types of data
sources which generates these enormous amounts of data. Big data in healthcare refers to
electronic health care records (EHR) that is quite large and complex that they are difficult to
manage with traditional software and/or hardware. Also, they are not easily managed with
traditional or common data management tools and methods. Using the technologies that able to
deal with such “Big Data” will offer many potential opportunities to the healthcare sector.
This research paper aims to deal with the main opportunities and challenges of the big data and
its analytics in healthcare. It also discusses the current technological platform and tools that can
help to utilize big data effectively. Section 1 of the paper gives brief introduction about Big data
and its characteristics. Section 2 provides information on health care sector and Big data. Section
3 provides an insight of Big data analytics. Section 4 demonstrates the main opportunities of Big
data in health care sector, while section 5 discusses the major challenges and threats of Big data
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implementation in health care sector. The available platform and tools for Big data
implementation is presented in Section 6. Finally, the paper’s conclusion is in Section 7.
1.1 Big Data: Background and its Sources
Big data is a term that is used to describe large volume of data. Data may in form of structured or
unstructured. The analytics of Big data leads to any organization towards better decision making
and strategic steps. Giant companies in sectors like retail, manufacture and government agencies
are using Big data to meet their business and strategic objectives. The Big data analytics also
plays a vital role for small and medium size industries to capitalize their business.
Industry analyst Doug Laney originally coined the concept of Big data while referring to the
challenge of data management [8]. According to that, there are three important dimensions of the
Big data concept illustrated below [5].
Figure 1. Three Vs of Big Data
Today, many organizations are gathering, storing, and analyzing huge amounts of data. These
data is known as a Big data as it has Volume, Velocity and Variety. Gartner [2012] predicts that
by 2015 the need to support big data will create 4.4 million IT jobs globally, with 1.9 million of
them in the U.S.[9]
1.2 BIG DATA SOURCES
There is variety of sources from where the Big Data is generated. Social Media sources such as
Facebook, Instagram, Twitter generates terabytes of data on every day. Machines such as desktop
computer, laptop generates tremendous amount of data. Geospatial data is generated by cell
phones and even from satellites. The IoT (Internet of Things) devices like sensors, pocket
computers are also generating a massive amount of data. Data is also generated as an output of
research projects like Large Hadron Collider (LHC) at CERN in Switzerland and France output
an enormous amount of data - over 200 petabytess [15].
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Several sectors are benefited from the Big Data analytics like The Financial Services Industry,
The Automotive Industry, Supply Chain, Logistics, and Industrial Engineering, Retail, Health
care, Entertainment etc. Combining Big Data with Analytics leads to any organization towards
many tasks like determining root causes of collapses, issues and defects in near-real time,
generating coupons based on the customer’s buying habits at the point of sale, recalculating entire
risk portfolios in minutes, detecting fraudulent behavior before it affects your organization etc.
[17]
2. HEALTH CARE AND BIG DATA
An information and communications technology (ICT) is playing a vital role in improving health
care for individuals and communities. It helps to improve health system efficiencies and prevent
medical errors. With an invent of new and efficient mechanisms for storing and accessing
information, ICT helps to serve a society in a better way. ICT powered health mechanisms are
often known as eHealth.
One of the characteristic that health care sector possesses is its data richness. With the
development in diagnostic and treatment, health care sector evolved so quickly in last few
decades. There are many sources in this sector from where the data is generated. These data is
undoubtedly in the form of Big Data. The data came from many sources and categorized as
follows:
1. Web and social media data: Data captured from Facebook, Twitter, LinkedIn, blogs, and
the like. It can also include health plan websites, smartphone apps etc. [14]
2. Machine-to-machine (M2M) device generated data: readings from remote sensors,
meters, and other devices [6].
3. Biometric data: Data may in form of retinal scans, x-ray images, finger prints, genetics,
handwriting, other medical images, blood pressure and other similar types of data [14].
4. Human-generated data: In the form of unstructured and semi-structured data. Some of the
examples are EMRs, Doctor’s notes and paper documents [14].
Genomic Data: data in the form of DNA sequence [2].
3. BIG DATA ANALYTICS
Big Data analytics is the process of exploring huge data sets that may contain a variety of data
types to reveal hidden patterns, unknown correlations, market trends, customer preferences and
other useful business information [1]. Big data analytics has emerged from two distinct concepts:
big data and analytics. Big Data analytics in Healthcare is fundamentally a set of methodologies,
procedures, frameworks and technologies which are used to transform raw data into meaningful
as well as useful information. These set of information are used to make decision making tasks
more effective whether they are strategic, tactical & operational. The following figure 1[10]
depicted the key components playing a role in Big Data analytics for health care sector [10].
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Figure 1. Big Data Analytics in Health Care: Key Components
As per the figure 1, data produces from variety of sources like hospitals, medical groups, payers
or other data providers. These data first needed to be aggregated. Moreover, many processes like
extraction, cleaning, conformation, transformation and loading are executed on data during this
phase. Finally, some meaningful and useful information are generated which can be used by
variety of users and purpose as shown in figure 1.
4. OPPORTUNITIES OF BIG DATA IN HEALTHCARE
This section discusses the various opportunities of Big data in health care.
Decreasing Healthcare Costs to Get Financial Profit
Big data can help decrease the cost of providing medical treatment in many ways. Moreover,
analysis on data gives insight to health care providers to determine populations at risk for illness.
By doing so, proactive steps can be taken initially. Data and its analytics are easier than ever to
share. Big data can more accurately pinpoint where education and prevention is needed to
produce healthier populations at lower costs. Treatment is more evidence based using Big Data
analytics[4].
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Promotes Research and Innovation
By analytics on data, the current state of health of patients provides insight to them to take more
ownership of their healthcare. The information sharing mechanism increases productivity and
reducing overlapping of data. By thus, it is enhancing the coordination of care. [4].
Personalized Medicine
In past few years, it is possible to predict the lifestyle diseases through genetic blue prints. Big
data will further personalize medicine by determining the tests and treatments needed for each
patient. The provision of earlier treatment can reduce the health costs and can eliminate the risk
of chronic diseases [4].
Strengthen the Preventive Care
Prevention is always better than cure. Following this thumb of rule, with the advent of Big Data
analytics, it is easy to capture, analyze and compare patient symptoms earlier to offer a
preventive care in a better way.
Virtual Care and Wearable Health Care Technologies
Technology is helping providers make virtual care initiatives that increase quality of care and
provide patients with more access [3].
Health Trend Analysis
By using different analytical approaches including data mining and text mining techniques, health
trend analysis and comprehensive patient management is more easy using Big Data Analytics [7]
Identification and Tracking of Patients
The identification and tracking of patients with type 2 diabetes is discussed in recent article [6].
The author suggests to use a two-step process to identify subsets of patients that have similar
clinical indications and care patterns. In a first step, patients are divided into groups based on the
primary diagnosis. Then after, a statistical clustering method is applied to further divide the
subsets. This method uses readily available administrative datasets. Also, patients must be
tracked longitudinally to determine the patterns for treatment. Therefore, the method is applicable
in scenarios where patient data is available over time and across providers [16].
Studying Drug Efficacy
Electronic health record (EHR) data may also be used to study drug efficacy. Researchers at the
University of Pennsylvania School of Medicine [15] compared the results of randomized
controlled trials versus using an EMR to compare cardiovascular outcomes. It has been observed
that the cost of randomized controlled trials is much higher than the cost of using readily
available EHR data to compare treatment modalities [16].
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5. CHALLENGES OF BIG DATA IN HEALTH CARE
Some of the challenges which make Big Data analytics difficult to use in health care are
discussed below.
Protecting the Patient’s Privacy
One of the significant challenges in leveraging health care’s big data to its full extent is policies
that protect the privacy of patient’s data. Many laws protect the patient’s data and not reveal the
patient’s identity that makes the big data analytics difficult.
On the contrary, sometimes health care providers are themselves are reluctant to share data
because of market competition. A physician many not want their competitors to know exactly
how many and which types of procedures they performed and where. Also, the demographics of
hospitals provide one hospital a financial advantage over another. Some of the datasets are
publicly available but these data sources are typically historical data or limited to government
payers[16].
Data Aggregation
In health care sector, the data is in unstructured form. These unstructured data is in the form of
images, graphs, notes of doctor’s etc. Apart from this, the nature of structured data is mostly
heterogeneous. These may lead a huge problem at the time of aggregation of these data. Natural
language processing and free-text software could solve this problem at some extent but it is in its
initial stage.
Cost Incurred for Establishment of Big Data Architecture
To have a benefit through Big Data analytics, it requires organization level management and
analysis as well as a large-scale investment.
Requirement of Expert Knowledge
Big Data systems require data scientists with specialized experience to support design,
implementation, and continued use. The McKinsey Global Institute estimates that there will be a
more than 100,000 person shortage through 2020. It means that mean 50–60% of data scientist
positions may go vacant. Data scientists need highly technical skill sets. They must possess soft
skills such as communication, collaboration, leadership, creativity and more [11].
Security Concern
Health data is a very much personal data. Patients expected extra privacy protection if they are
going to fully participate in Big Data analytics projects. In such types of projects, users should be
authorized at different levels and time periods. These will prevent unauthorized access to medical
records is nearly impossible [12].
6. TECHNOLOGY SUPPORT FOR BIG DATA ANALYTICS IN HEALTH CARE
There are varieties of platforms and tools are available for Big Data analytics in healthcare. Some
of these are mentioned in the table 1.
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Table 1. Platforms and Tools for Big Data Analytics
Cloud Storage Cloud storage uses a network of remote servers. These servers are hosted
on the Internet to store, manage, and process data. There are many vendors
that provide cloud storage. For example Google Cloud Storage is a key
part of storing and working with Big Data on Google Cloud Platform. For
Bigquery and Hadoop, using a Google Cloud Storage bucket is
optional but recommended.
Column oriented
databases
Column-oriented databases basically stores data sets as segments of
columns of data rather than as rows of data. It allows huge data
compression and very fast query times.
NoSQL databases In relational databases tabular relations are used while a NoSQL (Not only
SQL) database provides a different method for storage and retrieval of
data. It focuses on storage and retrieval of huge volumes of semi-
structured, unstructured or even structured data.
Hadoop System Hadoop is so far the most popular implementation of MapReduce
methodology. It is an entirely open source platform for handling Big Data.
Hive Hive is a runtime Hadoop support architecture that leverages Structure
Query Language (SQL) with the Hadoop platform.
PIG PIG consists of a "Perl-like" language. Instead of a "SQL-like" language, it
allows for query execution over data stored on a Hadoop cluster.
Cassandra Cassandra is also a distributed database system. It is designated as a top-
level project modelled to handle big data distributed across many utility
servers.
7. CONCLUSION
We may consider Big data as a latest evolution in the field of decision support data management
systems. On the other side, the digitalization in health care sector is in peak. As we discussed in
the paper, there are several opportunities for Big data in health care sector. Meanwhile, the
technological advancement is rapidly going on towards the implementation of Big data analytics.
In near future, there will be widespread implementation of big data analytics across the health
care organization and the healthcare industry. The Big data solutions could definitely save
millions of life and improve patient services.
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