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3. Critical Survey (Report) Each team should choose an available & real world dataset and survey papers that studied that data set US Government Data https://www.data.gov/ (you can also apply on UAE...

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3. Critical Survey (Report)

Each team should choose an available & real world dataset and survey papers that studied that data set

  • US Government Data https://www.data.gov/ (you can also apply on UAE Government Data http://opendata.fcsa.gov.ae/ )
  • Word net https://wordnet.princeton.edu/wordnet/download/
  • Google N-gram https://books.google.com/ngrams
  • Flow Cytometry https://flowrepository.org/

An individual needs to survey at least 10 papers. A team of two needs to survey at least 16 papers. Use google scholar and other online resources in order to obtain high-quality papers. It is recommended to use the CORE ranking for journals and conferences (A or B only), or impact factor (1 and above) or number of citations (5 and above).

Deliverables:

A survey, no more than 5000 words, single column, describing briefly and precisely

· Title of the topic (to be surveyed) and the team members (name and ID of each).

· In case of team, division of work: what did each team member do?

· Survey: summarize the different papers, highlighting what analysis was conducted on the data and what patterns were discovered

· the more integrated the survey is, the better (i.e., not simple collection of paper summaries.)

· Proposal: From what you read, what ideas you think are worth pursuing?

4. Critical Survey (Presentation)

30 minutes presentation about the critical survey that is uploaded, as a video, on the blackboard. The presentation should include:

    • Brief introduction
      • Data set
      • Why is it important
    • Overview
      • Group surveyed papers XXXXXXXXXXinto themes/clusters and briefly highlight them
    • Papers
      • 1-2 slides for each XXXXXXXXXXpaper
      • Main results, analysis & findings
    • Conclusion
      • What are the main lessons

5. Research Project (report with demo/presentation)

Choose an idea from the previous report to pursue in further detail. It is important to make sure the data you need is available. Analyze your data set and report the results.

Deliverables:

1. a report, no more than 7000 words, single column, describing briefly:

· Title of the topic.

· In case of team, division of work: what did each team member do?

· Methods

o What tools did you use?

o Any preprocessing of the data?

o What measurements/algorithms did you use?

· Results:

o What have you discovered? Be creative in visualizing and try to find interesting patterns.

· Discussion:

o Comments on the results and the whole experience (be scientific and precise, e.g. you may mention some ideas that you investigated but did not turn out to be interesting, etc.).

  1. A video, uploaded to the blackboard along with the report, summarizing the findings and/or providing a demo.

7. Important Notes

a) More than one team can choose the same topic.

b) All deliverables to be submitted through the blackboard.[1]

c) Acknowledge all assistance on assignments and all references.

d) Use blackboard for questions

8. Late submission

According to the university policy, every day late you lose (-) 2%, up to 5 working days excluding the weekend and holidays. If you are late more than the 5 days you will get zero.

Notice that. It is the student responsibility to make sure that the deliverable satisfies the requirements.


Marking Scheme

The grading will be broken down based on the following criteria:

Deliverable

Criterion

Max

Actual

Survey

Clarity & quality of writing

15%

Quantity & Quality of surveyed papers

15%

Originality of proposed ideas

10%

Presentation

10%

Total for Survey

50%

Report

difficulty of the problem (amount of work) & originality of the solution (how it differs from related work)

10%

Overall organization, readability & academic writing style

20%

Results, Depth of analysis, Critical evaluation of own work (discussion of results & conclusion)

20%

Total for the report

50%



[1] Turnitin is used to detect plagiarism. Plagiarism is a very serious offence that can lead to being expelled from the programme.

Answered Same Day May 18, 2020 Swinburne University of Technology

Solution

Amit answered on May 26 2020
115 Votes
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Table of Contents
1.    Selection of data set    3
2.    Title of topic: Big data analytics in healthcare    5
3.    Title of topic: Big data analytics in healthcare    6
4.    Title of topic: Big data analytics in healthcare: promise and potential    6
5.    Title of topic: Big Data Analytics for Healthcare. In High-Performance Big-Data Analytics    7
6.    Title of topic: An integrated big data analytics-enabled transformation model: Application to health care. Information & Management    8
7.    Title of topic: A survey of big data analytics in healthcare and government.    9
8.    Title of topic: Beyond the hype: Big data concepts, methods, and analytics    9
9.    Title of topic: Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations    10
10.    Title of topic: Big data in health care: using analytics to identify and manage high-risk and high-cost patients.    11
11.    Title of topic: Research directions on the adoption, usage, and impact of the internet of things through the use of big data analytics    12
12.    Final conclusion    12
13.    References:    13
1. Selection of data set
The selection of publically available data base is very critical task. There are so many different databases available on https:
www.data.gov/education/ . These databases are related to different things like education, agriculture, climate, consumers, energy, finance, health etc. The health databases are very commonly used with big data implementation. The screen shot to show these data sets in health care field is as given below:
To view the available data set, the user is required to just click on given button of “view this Data set”. The obtained screen of viewing this selected data set is as given below:
When, user click on “view Data”, the desired data set is available for analysis and implementation work. The screen shot of this data set is as given below:
The user is allowed to make management of this data set, more views of this data set, visualization of this data set and can also export any selected data set for further use of analysis work. This is an implementation of big data in healthcare field. The public availability of this data set makes in easy approach for analysis work. The developed ngram for big data nad health care is as given below:
Different research works are being conducted by different researchers in healthcare field by using the same data sets. As big data is huge area and implementation of big data in health care field combines so many opportunities for researchers. This complete analysis work of big data implementation in health care field by using ten different research papers which are presented in time period of 2014 to 2018 is completed by me only. Any help from team member is not taken. The complete analysis of ten different papers in area of health care through big data implementation is explained in below sections. All of these papers are available on Google scholar, so, their impact factor is more than 1.
2. Title of topic: Big data analytics in healthcare
Authors of this paper: Belle, Thiagarajan, Soroushmehr, Navidi, Beard, & Najarian, 2015
Survey results: This paper defines the role of big data in health care field. The data analytics generated through big data analysis are providing pivotal role in different evaluations of potential research work. The provided tools of big data for managing, analyzing, assimilating and accumulating the generated structured as well as unstructured data in field of health care are playing distinct role as compare to traditional systems. The role of big data for exploration of diseases and delivering the care is increased in recent era. The paradigm of big data implementation contains some issues like manipulation of images, manipulation of signals and manipulation of analytics based on genomics in its implementation. This paper provides finding related to above given issues in implementation of big data in field of health care.
Proposal on finds: My proposal on findings of this paper suggest that the multimodal data sets can be placed in different data sets for proper utilization of big data and solving the issues of signal, implementation of analytics based on genomics and signal manipulation can easily be solved.
3. Title of topic: Big data analytics in healthcare
Authors of this paper: Vibha Ganjir, Dr. B.K. Sarkar, & Ravi Ranjan Kumar, 2016
Survey results: This paper defines the role of big data in health care field. The challenges, characteristics and advantages of big data in health care field are analyzed in this paper. The five ‘V’ of big data: volume, variety, veracity, value and velocity are explained in this paper. The role and impact of analysis created on big data tools for the health care field with five ‘R’: right living, right care, right provider, right value and right innovation are properly explained. This paper provides the benefits and limitations of big data in field of health care.
Proposal on finds: The use of five ‘V’ and five ‘R’ shows then importance of different dimensions in development of big data for health care field. But any specific conclusion is not archived by this paper. The scope of rapid implementation of big data in different fields of healthcare requires further research.
4. Title of topic: Big data analytics in healthcare: promise and potential
Authors of this paper: Wullianallur Raghupathi and Viju Raghupathi, 2014
Survey results: This paper defines the role of big data in health care field. This paper provides a conceptual view of big data source, big data transformation, big data tools and platform and applications to perform analytics on big data in field of health care. The use of different tools like HDFS, PIG Latin, HIVE, JAQL etc with descriptions is provided in this paper. The steps of...
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