Virtual Study Solutions: Health Care Fields

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<span style="font-family: "verdana" , sans-serif;">What is Big Data?</span></h3>
<span style="font-family: "verdana" , sans-serif;">The publications seem to relate more to healthcare and information systems more than computer science. Big data is an important topic of discussion in IT, research, medical field, economics and business field. The term big refers, large or immense; and Data signifies raw information’s that when analyzed and processed provides idea and meaning to object or matter. Both these words when combined together provide a clear picture of big data that is large and can be in structured or unstructured form. Here structured denotes, data with high degree of organization, whereas unstructured refers to unorganized data that lack proper model. Previously we sh</span><span style="font-family: "verdana" , sans-serif;">ared <a href="https://virtualstudysolutions.blogspot.com/2018/10/cs619-final-project-how-to-select-and-complete-final-project.html">What is CS619 Final Project? How to Select and Complete Final Project.</a></span><br />
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<tr><td class="tr-caption" style="text-align: center;"><span style="font-family: "verdana" , sans-serif;">Big Data Analytics Assignment | Data Analytics in Various Health Care Fields</span></td></tr>
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<span style="font-family: "verdana" , sans-serif;">In this article we will discuss the following:</span><br />
<ol style="text-align: left;">
<li><span style="font-family: "verdana" , sans-serif;">Published Papers Regarding Data Analytics in Various Health Care Field</span></li>
<li><span style="font-family: "verdana" , sans-serif;">Big Data Analytics Theories and Techniques In Health Care</span></li>
<li><span style="font-family: "verdana" , sans-serif;">Installing a Big Data Analytics framework (Hadoop or Spark) </span></li>
<li><span style="font-family: "verdana" , sans-serif;">Installing R - Step by Step</span></li>
<li><span style="font-family: "verdana" , sans-serif;">The Functionality Of R With Regard To Health Care</span></li>
</ol>
<b><span style="font-family: "verdana" , sans-serif;">Also</span></b><span style="font-family: "verdana" , sans-serif;"><b> Read :</b>  <a href="https://virtualstudysolutions.blogspot.com/2019/10/taking-action-on-adolescent-literacy.html">Summary Of Taking Action on Adolescent Literacy </a></span><span class="retitle"></span><br />
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<span style="font-family: "verdana" , sans-serif;">Uses of Big data analytics </span></h4>
<span style="font-family: "verdana" , sans-serif;">Big data is defined as the raw data obtained from number of medium; studying these data, analyzing it and obtaining meaningful result out of them is called big data analytics. Below are some of the uses of big data analytics.</span><br />
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<li><span style="font-family: "verdana" , sans-serif;">Enhancing the performance</span></li>
<li><span style="font-family: "verdana" , sans-serif;">Improvement in Research and health care</span></li>
<li><span style="font-family: "verdana" , sans-serif;"> Development in business</span></li>
<li><span style="font-family: "verdana" , sans-serif;">Strengthening Security and finding criminals</span></li>
<li><span style="font-family: "verdana" , sans-serif;">To bring development in nation</span></li>
</ul>
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<span style="font-family: "verdana" , sans-serif;">Advantages of Big Data Analytics</span></h4>
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<li><span style="font-family: "verdana" , sans-serif;">Error detection</span></li>
<li><span style="font-family: "verdana" , sans-serif;">Predicting events</span></li>
<li><span style="font-family: "verdana" , sans-serif;">Reduces time and effort</span></li>
<li><span style="font-family: "verdana" , sans-serif;">Increases efficiency and accuracy</span></li>
<li><span style="font-family: "verdana" , sans-serif;">Progress of company</span></li>
</ul>
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<span style="font-family: "verdana" , sans-serif;">Who uses Big Data? </span></h4>
<span style="font-family: "verdana" , sans-serif;">Presently, there are number of companies that have developed software to use big data to compete in the growing market. Beside this, these useful tools are also used in different fields to develop sense from big data specific to the finding.</span><br />
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<span style="font-family: "verdana" , sans-serif;">These are the few popular companies that uses big data to fulfill customer requirements and accomplish their goal.</span><br />
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<li><span style="font-family: "verdana" , sans-serif;">HP</span></li>
<li><span style="font-family: "verdana" , sans-serif;">Oracle</span></li>
<li><span style="font-family: "verdana" , sans-serif;">Microsoft</span></li>
<li><span style="font-family: "verdana" , sans-serif;">Splunk</span></li>
<li><span style="font-family: "verdana" , sans-serif;">Amazon    </span></li>
</ul>
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<span style="font-family: "verdana" , sans-serif;">1. Published Papers Regarding Data Analytics in Various Health Care Fields  </span></h3>
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<span style="font-family: "verdana" , sans-serif;">This paragraph will discuss the results found in this paper. The publications seem to relate more to healthcare and information systems more than computer science, since computer science involves professionals and doctors only in healthcare analytics, paying less attention to involve individuals and patients, as we believe involving individuals will lead for better decision making and more accurate results for the future. Most healthcare analytics papers were published in the US as it shown in geographical distribution in Figure 7, and linking this results to the research approach distribution in Figure 8, we can notice that most publications in healthcare analytics were quantitative studies, so if we take a look again, we can conclude and relate that to the reason of why papers were decreased in the last 2 years, because quantitative studies are very expensive and costly, as well as it is focusing on involving professionals in healthcare analytics systems rather than patients, which will effect on having many inaccurate studies results, and create many struggles with healthcare analytics and kills it’s future, therefore researchers will stop publishing papers as they lost their spirit in healthcare analytics, so we recommend to involve individuals, as it would help society to adopt and improve healthcare data analytics systems, as well as running these systems efficiently and smoothly. (Alkhatib, Talaei-Khoei & Ghapanchi, 2016)</span><br />
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<span style="font-family: "verdana" , sans-serif;">2. Big Data Analytics Theories and Techniques In Health Care. </span></h3>
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<span style="font-family: "verdana" , sans-serif;">Theory suggests that big data analysis technology, coupled with the proper business model (a topic for another blog), may be a disruption enabler in at least two ways:</span><br />
<ol style="text-align: left;">
<li><span style="font-family: "verdana" , sans-serif;"><b>Enabling technologies make powerful data analytics affordable and accessible.</b> Inexpensive data storage, massive computing power, and widespread information transfer infrastructures make predictive analytics available to small players than ever before. Patient population analytics, for example, used to be available only to the largest and wealthiest of health systems who could hire talented teams of statisticians. Now, solutions exist that are affordable even for small providers. </span></li>
<li><span style="font-family: "verdana" , sans-serif;"><b>Accessible and affordable analytics drive operating efficiencies.</b> One third to one half of U.S. health care spend is on <a href="http://www.healthaffairs.org/healthpolicybriefs/brief.php?brief_id=82" rel="nofollow" target="_blank">ineffective or inefficient care</a>– hundreds of billions of dollars each year. Theory-based big data solutions can help change this. For example, theory-based (rather than simply correlative) population health management analytics updated with the latest best clinical practices from medical journals could help test, validate, and adopt new standards of care much more quickly than the average adoption timeline of <a href="http://research.microsoft.com/en-us/collaboration/fourthparadigm/4th_paradigm_book_part2_gillam.pdf" rel="nofollow" target="_blank">17 years</a> and in so doing help obsolete outdated, wasteful, and expensive treatment methods  While perhaps not as headline-making as “The End of Theory,” “Save Hundreds of Billions of Dollars With Better Health Outcomes” is pretty close. (Bean, 2016)</span></li>
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<span style="font-family: "verdana" , sans-serif;">3. Installing a Big Data Analytics framework (Hadoop or Spark)</span></h3>
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<span style="font-family: "verdana" , sans-serif;"><b>Step 1: Install Java </b></span></h4>
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<span style="font-family: "verdana" , sans-serif;">Firstly you need to install java successfully and then run the following commands.</span><br />
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<li><span style="font-family: "verdana" , sans-serif;"> sudo apt-add-repository ppa:webupd8team/java </span></li>
<li><span style="font-family: "verdana" , sans-serif;">sudo apt-get update </span></li>
<li><span style="font-family: "verdana" , sans-serif;">sudo apt-get install oracle-java7-installer</span></li>
</ul>
<span style="font-family: "verdana" , sans-serif;">To check whether the Java is successfully installed or not, you need the run the command. <br /><br />·         $scala -version <br /><br />“”If the Java is installed then you will get to see the following: <br /><br />java version “1.7.0_71” <br /><br />Java(TM) SE Runtime Environment (build 1.7.0_71-b13) <br /><br />Java HotSpot(TM) Client VM (build 25.0-b02, mixed mode)””</span><span style="color: #444444;"></span><span style="font-family: "verdana" , sans-serif;"><br /></span><br />
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<span style="font-family: "verdana" , sans-serif;"><b>Step 2: Install Scala </b></span></h4>
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<span style="font-family: "verdana" , sans-serif;">Step two is to download the latest version of scala by visiting the <a href="http://www.scala-lang.org/" rel="nofollow" target="_blank">www.scala-lang.org</a> and then run the following commands.</span><span style="color: #444444;"></span>

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<li><span style="font-family: "verdana" , sans-serif;"> sudo mkdir /usr/local/src/scala </span></li>
<li><span style="font-family: "verdana" , sans-serif;">sudo tar -xvf scala-2.11.7.tgz -C /usr/local/src/scala/<br /> nano .bashrc </span></li>
<li><span style="font-family: "verdana" , sans-serif;">export SCALA_HOME=/usr/local/src/scala/scala-2.11.7 </span></li>
<li><span style="font-family: "verdana" , sans-serif;">export PATH=$SCALA_HOME/bin:$PATH<br /> .bashrc</span></li>
</ul>
<span style="font-family: "verdana" , sans-serif;">To check whether the Java is successfully installed or not, you need the run the command. <br /><br />·         $scala -version <br /><br />If the Scala is successfully installed then you will get to see. <br /><br />“”Scala code runner version 2.11.6 — Copyright 2002-2013, LAMP/EPFL””</span><span style="color: #444444;"></span><span style="font-family: "verdana" , sans-serif;"><br /></span><br />
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<span style="font-family: "verdana" , sans-serif;"><b>Step 3: Install Git </b></span></h4>
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<span style="font-family: "verdana" , sans-serif;">Next step is to install Git. Command is given below. </span><br />
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<li><span style="font-family: "verdana" , sans-serif;">sudo apt-get install git</span>

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<span style="font-family: "verdana" , sans-serif;"><b>Step 4: Build Spark </b></span></h4>
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<span style="font-family: "verdana" , sans-serif;">The final step is to download the latest version of spark by visiting the <a href="http://www.spark.apache.org/" rel="nofollow" target="_blank">www.spark.apache.org</a> </span><br />
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<li><span style="font-family: "verdana" , sans-serif;">tar -xvf spark-1.4.1.tgz </span></li>
<li><span style="font-family: "verdana" , sans-serif;">sbt/sbt assembly</span>

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</ul>
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<span style="font-family: "verdana" , sans-serif;">Issues and Recommendation </span></h4>
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<span style="font-family: "verdana" , sans-serif;">Although Spark is reported to work up to 100 times faster than Hadoop in certain circumstances, it does not provide its own distributed storage system. Spark does not include its own system for organizing files in a distributed way (the file system) so it requires one provided by a third-party. For this reason many Big Data projects involve installing Spark on top of Hadoop, where Spark’s advanced analytics applications can make use of data stored using the Hadoop Distributed File System (HDFS). (Marr, 2016)</span><br />
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<span style="font-family: "verdana" , sans-serif;">4. Installing R  </span><span style="color: black; mso-themecolor: text1;"></span><span style="font-family: "verdana" , sans-serif;">- Step by Step</span></h3>
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<ol style="text-align: left;">
<li><span style="font-family: "verdana" , sans-serif;">Once you have installed R on a Windows computer (following the steps above), you can install an additional package by following the steps below:</span></li>
<li><span style="font-family: "verdana" , sans-serif;">To start R, follow either step 2 or 3:</span></li>
<li><span style="font-family: "verdana" , sans-serif;">Check if there is an “R” icon on the desktop of the computer that you are using. If so, double-click on the “R” icon to start R. If you cannot find an “R” icon, try step 3 instead.</span></li>
<li><span style="font-family: "verdana" , sans-serif;">Click on the “Start” button at the bottom left of your computer screen, and then choose “All programs”, and start R by selecting “R” (or R X.X.X, where X.X.X gives the version of R, eg. R 2.10.0) from the menu of programs.</span></li>
<li><span style="font-family: "verdana" , sans-serif;">The R console (a rectangle) should pop up.</span></li>
<li><span style="font-family: "verdana" , sans-serif;">Once you have started R, you can now install an R package (eg. the “rmeta” package) by choosing “Install package(s)” from the “Packages” menu at the top of the R console. This will ask you what website you want to download the package from, you should choose “Ireland” (or another country, if you prefer). It will also bring up a list of available packages that you can install, and you should choose the package that you want to install from that list (eg. “rmeta”).</span></li>
<li><span style="font-family: "verdana" , sans-serif;">This will install the “rmeta” package.</span></li>
<li><span style="font-family: "verdana" , sans-serif;">The “rmeta” package is now installed. Whenever you want to use the “rmeta” package after this, after starting R, you first have to load the package by typing into the R console:</span></li>
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<span style="font-family: "verdana" , sans-serif;"><span style="color: #666666; letter-spacing: 0.2pt;">></span><span style="color: black; letter-spacing: 0.2pt;"> </span><b><span style="color: #007020; letter-spacing: 0.2pt;">library</span></b><span style="color: black; letter-spacing: 0.2pt;">(</span><span style="color: #4070a0; letter-spacing: 0.2pt;">"rmeta"</span><span style="color: black; letter-spacing: 0.2pt;">)</span></span></div>
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<span style="font-family: "verdana" , sans-serif;">Issues and recommendation</span></h4>
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<span style="font-family: "verdana" , sans-serif;">In my healthcare data, I wanted to convert dollar values to integers (ie. $21,000 to 21000), and I used gsub  .  wanted to focus on the Payment estimate. </span><br />
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<li><span style="font-family: "verdana" , sans-serif;">So I used the melt() function that is part of reshape2. </span></li>
<li><span style="font-family: "verdana" , sans-serif;">With my data melted, I wanted to get the average estimate for heart attack patients by state.</span></li>
</ul>
<span style="font-family: "verdana" , sans-serif;">Now that my data is in perfect shape to visualize with a map overlay, ggplot2 and maps are two other R packages that would be useful (Parmar, 2016) </span><br />
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<span style="font-family: "verdana" , sans-serif;">5. The Functionality Of R With Regard To Health Care </span></h3>
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<span style="font-family: "verdana" , sans-serif;">Researcher introduces the utilization of R as a tool for analyzing their data. In the past 5 years since the inception of this book, the number of R applications has exploded. It is not possible to do justice to R’s diverse capabilities in a few words. Using R to analyze the data, because of the ease of interactive exploration and making visualizations. (Seefeld & Linder, 2016)</span><span style="color: black; font-family: "symbol"; mso-bidi-font-family: Symbol; mso-fareast-font-family: Symbol; mso-themecolor: text1;"><span style="mso-list: Ignore;"><span style="font: 7.0pt "Times New Roman";">       
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<span style="color: black; font-family: "times new roman" , "serif"; font-size: 12.0pt; line-height: 115%;"><b><span style="font-family: "verdana" , sans-serif;">Refrences:</span></b></span></h4>
<span style="font-family: "verdana" , sans-serif;">Alkhatib, M., Talaei-Khoei, A., & Ghapanchi, A. (2016). Analysis of Research in Healthcare Data Analytics. arXiv preprint arXiv:1606.01354. <br /><br />Bean, D. (2016). Big Data: The end of theory in healthcare? - Christensen Institute. Christensen Institute. Retrieved 31 October 2016, from <a href="http://www.christenseninstitute.org/blog/big-data-the-end-of-theory-in-healthcare/" rel="nofollow" target="_blank">http://www.christenseninstitute.org/blog/big-data-the-end-of-theory-in-healthcare/</a> <br /><br />Marr, B. (2016). Forbes Welcome. Forbes.com. Retrieved 31 October 2016, from <a href="http://www.forbes.com/sites/bernardmarr/2015/06/22/spark-or-hadoop-which-is-the-best-big-data-framework/#1bfc431d532c" rel="nofollow" target="_blank">http://www.forbes.com/sites/bernardmarr/2015/06/22/spark-or-hadoop-which-is-the-best-big-data-framework/#1bfc431d532c</a> <br /><br />Seefeld, K. & Linder, E. (2016). Statistics Using R with Biological Examples. https://cran.r-project.org. Retrieved 31 October 2016, from <a href="https://cran.r-project.org/doc/contrib/Seefeld_StatsRBio.pdf" rel="nofollow" target="_blank">https://cran.r-project.org/doc/contrib/Seefeld_StatsRBio.pdf</a> <br /><br />Parmar, D. (2016). R Packages: A Healthcare Application. Datasciencecentral.com. Retrieved 31 October 2016, from <a href="http://www.datasciencecentral.com/profiles/blogs/r-packages-a-healthcare-application" rel="nofollow" target="_blank">http://www.datasciencecentral.com/profiles/blogs/r-packages-a-healthcare-application</a></span></div>
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Big Data Analytics Assignment | Data Analytics in Various Health Care Fields

What is Big Data? The publications seem to relate more to healthcare and information systems more than computer science. Big data is an i...

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