Electronic medical record emr database and big data using microsoft azure projec

VIETNAM NATIONAL UNIVERSITY, HANOI INTERNATIONAL SCHOOL GRADUATION PROJECT PROJECT NAME Electronic Medical Record (EMR) Database And Big Data Using Microsoft Azure Project Student’s name ĐỖ THỊ TÚ UYÊN Hanoi - Year 2020 VIETNAM NATIONAL UNIVERSITY, HANOI INTERNATIONAL SCHOOL    GRADUATION PROJECT PROJECT NAME Electronic Medical Record (EMR) Database And Big Data Using Microsoft Azure Project SUPERVISOR: Assoc Prof Dr Nguyễn Thanh Tùng STUDENT: Đỗ Thị Tú Uyên STUDENT ID: 16071317 COHORT: MIS2016A MAJOR: Management Information System Hanoi - Year 2020 FORM 3: LETTER OF DECLARATION I hereby declare that the Graduation Project “Electronic Medical Record (EMR) Database And Big Data Using Microsoft Azure” is the results of my own research and has never been published in any work of others During the implementation process of this project, I have seriously taken research ethics; all findings of this project are results of my own research and surveys; all references in this project are clearly cited according to regulations I take full responsively for the fidelity of the number and data and other contents of my graduation project Hanoi, (day) 06 (month) 06 (Year) 2020 Student (Signature and Full name) FORM 4: ACKNOWLEDGEMENT First of all, I would like to express my sincere thanks to all teachers in International School – Vietnam National University for teaching and imparting valuable knowledge to me during the four years of studying and training at the school I want to express my deep gratitude to the instructor - Assoc.Prof.Dr Nguyen Thanh Tung (and his assistants MR Vu Khanh Hoan), and my old teacher Mr.Phat, who enthusiastically guided me to implement this thesis as well as creating favorable conditions for me to have real contact, helping me gain more knowledge, practical and future job requirements With my limited knowledge and research time, my thesis cannot avoid shortcomings I look forward to receiving comments and suggestions from teachers It will be a valuable experience for me to improve myself later Sincerely thank! FORM 5: TABLE OF CONTENT CHAPTER 1: OVERVIEW OF BIG DATA ON THE CLOUD COMPUTER PLATFORM I Cloud Computing I.1 Introduction about Cloud Computing I.2 Components and structure of cloud computing I.3 The Services of Cloud Computing I.3.1 SaaS: Software as a Service I.3.2 PaaS: Platform as a Service I.3.3 IaaS: Infrastructure as a Service I.4 Models of Cloud Computing 12 I.4.1 Public Cloud 12 I.4.2 Private Cloud (“Businesses” Cloud) 13 I.4.3 Hybrid Cloud 13 I.4.4 Community Cloud 14 I.5 The advantages/disadvantages of Cloud Computing and introduce some applications of its 14 I.5.1 The advantages and Disadvantages: 14 I.5.2 Some applications of Cloud Computing 17 I.6 Typical cloud applications 17 I.6.1 Google App Engine 17 I.6.3 Amazon Web Services 18 I.6.2 Windows Azure 19 I.7 The situation of apply Cloud Computing in the world and Vietnam 19 II Big Data - Overview And Its Impact On Health Care 24 II.1 The definition of Big Data and What is Big Data in Health Care System and Why we need it? 24 II.1.1 The Definition Of Big Data 24 II.1.2 What Is Big Data In Health Care System? And Why We Need It? 24 II.2 The Characteristics Of Big Data 25 II.3 Stored in Big Data Analysis System 26 II.4 The advantages and challenges of using Big Data 31 II.3.1 The advantages of Big Data 31 II.3.2 The challenges of using Bing Data 32 II.5 The application and important of Big Data in Health Care System 34 II.2.2 The important of Big Data in Health Care 34 II.2.3 Examples of Big Data 37 II.6 III What is NoSQL System? Why did I choose it? 37 Overview about Cassandra Cosmos DB 40 III.1 Introduction, Definition, and features 40 III.2 Strength and Weakness 42 CHAPTER 2: APPLICATION AND RESULTS ACHIEVED 43 I II Introduction about the tool Microsoft Azure 43 I.1 Introduction 43 I.2 Services of Microsoft Azure 43 I.3 Why did I choose Microsoft Azure? 45 Application in the project - health care system 51 II.1 About the data of the topic 51 II.2 Setup Big Data 54 II.3 Demo the result 63 III Conclusion 65 III.1 Assessment Of Project 65 III.2 Contributions of the project: 65 III.3 The Limitations of the project 67 References 69 FORM 6: TABLE OF NOTATIONS AND ABBREVIATIONS Abbreviation Meaning MAZ Microsoft Azure ASL Apache Software License Version DB Database IaaS Infrastructure as a service PaaS Platform as a service SaaS Software as a Service GAE Google App Engine JVM Java virtual machine AWS Amazon Web Services API Application Programming Interface Choose the server location closest to you, here I choose Korea 13-create Big Data After creating successfully, you will see interface as follows: 14-create Big Data 10 58 STEP 2: CREAT TABLE We can see the "add table" in the right corner of the screen Here, select "create new" to create a new table and fill in the name and properties of the table For example, the picture is the “ThongTin" table 15-Create Table in Big Data Clicking OK will display the following screen: 16-Create Table in Big Data 59 In the same way, we create all the necessary tables of Big Data we need STEP 3: INPUT DATA INTO EACH TABLE With Azure Cosmos DB, data is automatically loaded from monitors to fields that were originally created in big data Or enter manually by pressing the "Add" button on that table as shown: 17-Input data STEP 4: CONNECT DB WITH WEBSITE To complete this topic, in addition to using Big Data, I also need to use html to make demo websites and nodejs as back-end to help connect the database - Environment preparation: In addition to installing the appropriate language driver, we also need to install the library Here I use Cassandra-driver and libraries: + path: help manipulate file path and file name such as get the path pointing to the directory, get the file name in the path, get the file extension, + express: Express is the most popular Node.js web framework and is the basic library for some other popular Node.js frameworks Express provides the mechanism Write handlers for requests with different HTTP methods at different URL paths (router) 60 Integrate the "view" display tool to create feedback by inserting data into the views Add middleware processing requests at any point to the request processing flow + hbs: Template created by Handlebars, a web template system; contains a template written in HTML code and embedded with handlebars expressions; same as the HANDLEBARS file 18-Connect to Cassandra - Connect to Cassandra The two most important factors here are the host - the path to the server, the username and the password - the big data login on it The information is listed as code below 61 19-Connect to Cassandra - Query data: 62 The following is a simple example when I query data from Cassandra down 20-query data II.3 Demo the result 63 This is the image when posting on the web: 21-demo When you need to see details about a patient's situation, click "View Detailed": 22-demo 64 III Conclusion III.1 Assessment Of Project III.1.1 Outputs of the health care system The system was able to store the patient's information in real time, and display the information on the website Apply the outstanding advantages of Big Data on cloud computing platform to store and optimize patient information in the hospital Helping the hospital reduce risks and costs, as well as help patients keep track of their disease, thereby preventing related complications Thanks to Microsoft Azure and Cassandra database management system, the previously difficult problems were solved Now, there is no need to go to the place of examination, no need for paperwork, just look through the website instantly anytime, anywhere III.1.2 Knowledge gained after experiment - Learn new technologies, namely Big Data on Cloud Computing platform There are also WEB, HTML, NODEJS to apply in practice - System design: Learn how to optimize and rationalize the database according to Cassandra Cosmos DB model to store and synchronize data - Processing and building data: view, discover new variables, have an important role for the project How to structure in NoSQL format III.2 Contributions of the project: The dissertation has studied the overview of big data, definitions, characteristics and architecture, and build empirical data model for databases and websites  Main results achieved in the report are: - Overview of some Big Data and Cloud Computing architecture issues, big data models, predictive analytical models 65 - State the organization method, how to implement the Big Data system and formulate experimental scenarios to store and use patient information - Instructions for using Microsoft Azure tool with Cassandra Cosmos DB database system - List the advantages / disadvantages of Big Data and the situation of implementation in Vietnam and other countries in the world  Development trend of the report: - Complete the database, tools, website and actual deployment of Health Care system, effective use in diagnosis and monitoring of disease - Integrate this tool into the Big Data ecosystem of the Ministry of Health or hospitals, considering it as one of the main tools in the health care system In addition, regularly optimizing database storage model to monitor and forecast diseases with increasingly accurate and easier rates  Some suggestions for future research on this field The first is that using MC.Azure is very costly, so it will be more suitable for large organizations, large hospitals that have high affordability to research and apply the project in practice Secondly, the system deployment should be in parallel with the current software in hospitals because our country's health sector has not been synchronized into a common system like other developed countries The third is to build the Big Data collection system We need to build software, applications or devices that can connect to the server to transmit information and data The difficulty here is that Big Data comes in many different formats from structured, semi-structured, and unstructured, so the Big Data collection system must be advanced and integrate new technologies to collect data If the system cannot read the data, it will not be available for later analysis The fourth is the construction of web storage systems and data extraction If the hospital does not weigh, or accurately predicts, the amount of data it will build an unreasonable system In addition, the confidentiality of hospital information and data will be difficult 66 III.3 The Limitations of the project In the process of implementing this project, I also encountered many difficulties The first is the limited time, so the completion of the project will not be perfect but only meet the basic requirements of storing and displaying information The second is connecting the driver to Cassandra From the beginning, I chose the language PHP, but in the middle of the project, when I installed the driver, I learned that Microsoft Azure has stopped supporting this language, so I had to build the library myself However, due to my limited ability, I chose to change to the new language, NODEJS Despite the rushing time, I finished it as quickly as possible The third is the creation and construction of Big Data database system on Cassandra I had a hard time while the tool need to paying a fee to try out the service (demo before I connected to the real database) with the funding is not small for students Next, self-learning a new language - Big Data While universities often teach traditional databases like MySQL, in order for me to build this database, I have to learn more about BIG DATA and its commands and queries even though it is just stop at the most basic level Finally, Due to the data security of the hospital, I could not bring a large data to demo However, the main of the problem is to show how Big Data works and how it applies to health care so I can still demo with a few records Although with some samples, its data volume is still very large Each patient will have 1800 records in hour So day with patients will has reached 216000 records In addition, using MC.Azure requires a fee based on traffic and data queries So even if I could bring actual data from the hospital into my data schema, I wouldn't be able to pay this fee for such a huge amount of data Although the demo data is very small, it is still complete and fully meets the requirements of an initial problem given 67 Although I encountered many difficulties, but I still completed the project as completely as possible Those difficulties teach me many lessons to gain experience 68 References [1] Amazone website, https://aws.amazon.com/ec2/faqs/ [2] Infortech Report, https://infotech.report/allresources.aspx?Vendor=blog%20article [3] https://sbtech.cloud/cloud-computing/ [4] https://www.hindawi.com/journals/mpe/2014/496843/ [5] Definition of Big Data, https://searchdatamanagement.techtarget.com/definition/big-data [6] Wikipedia Big Data, https://en.wikipedia.org/wiki/Big_data [7] https://www.passeidireto.com/arquivo/68437186/big-data-fundamentals- concepts-drivers-techniques/28 [8] Hardware Engineering Program Manager, https://careers.microsoft.com/us/en/job/844575/Hardware-Engineering-ProgramManager [9] Microsoft Azure Website, What is Azure, https://www.serversdirect.co.uk/content/microsoft-azure [10] Vicloud.vn, su phat trien cua dien toan dam may, https://vicloud.vn/community/su-phat-trien-cua-dien-toan-dam-may-348.html (2018) [11] Y Chen, C Xu, W Rao, H Min - Octopus: Hybrid big data integration engine, (2015) [12] M Matti, T Kvernvik - Ericsson Review [PDF], Applying big-data technologies to network architecture, (2012) [13] I Malaka, I Brown, Challenges to the organisational adoption of big data analytics: a case study in the South African telecommunications industry, (2015) [14] E Baştuğ, M Bennis, E Zeydan - Big Data meets telcos: A proactive caching perspective, (2015) [15] Marek Obitko, Industry 4.0 and BigData, http://www stech.cz/ Portals/0/ Konference/ 2015/ 03%20Industry-/ PDF/03_ obitko.pdf 69 [16] Digistar.vn, lich su dien toan dam may, https://www.digistar.vn/lich-su- dien-toan-dam-may/ [17] E Zeydan, E Bastug, M Bennis, BigData caching for networking: Moving from cloud to edge, (2016) [18] PK Dalvi, SK Khandge, A Deomore, Analysis of customer churn prediction in telecom industry using decision trees and logistic regression, (2016) [19] N Lu, H Lin, J Lu, G Zhang, A customer churn prediction model in telecom industry using boosting (2012) [20] Lò Thị Phương Nhung & Nguyễn Mai Phương, BigData: Tac dong va xu huong phat trien (2017) [21] Vũ Đức Thi, Cong nghe tri thuc, Hanoi, page 17-20 70 ĐẠI HỌC QUỐC GIA HÀ NỘI KHOA QUỐC TẾ CỘNG HÒA XÃ HỘI CHỦ NGHĨA VIỆT NAM Độc lập – Tự – Hạnh phúc BIÊN BẢN GIẢI TRÌNH CÁC ĐIỂM CHỈNH SỬA/ BỔ SUNG THEO QUYẾT ĐỊNH CỦA HỘI ĐỒNG CHẤM KHÓA LUẬN TỐT NGHIỆP CÁC CHƯƠNG TRÌNH ĐÀO TẠO DO ĐHQG HÀ NỘI CẤP BẰNG Họ tên sinh viên: ĐỖ THỊ TÚ UYÊN Đề tài: Electronic Medical Record (EMR) Database And Big Data Using Microsoft Azure Project Mã số sinh viên: 16071317 Ngành học: Management Information System Khóa học: 2016-2020 Căn Quyết định số …… QĐ/KQT, ngày … tháng … năm …… Khoa Quốc tế việc thành lập Hội đồng chấm khóa luận tốt nghiệp sinh viên chương trình đào tạo cử nhân ĐHQGHN cấp bằng, sinh viên bổ sung sửa chữa khóa luận sau: TT Yêu cầu chỉnh sửa Nội dung điều chỉnh bổ sung Điều chỉnh số thuật ngữ chuyên ngành Tại lựa chọn MS.Azure tools khác Amazone? Thêm tài liệu tham khảo khoa học, xếp, điền đầy đủ thông tin báo tham khảo Các tài liệu tham khảo cần tham chiếu đầy đủ viết Chỉnh sửa số tên thuật ngữ ngữ pháp toàn I.3 Why did I choose Microsoft Azure? Thêm giải thích so sánh thêm hai tools mục I.3 Cập nhật thêm thông tin phần thu thập liệu, phần minh họa hệ thống cho rõ Thêm tài liệu trích dẫn vào mục “References” Đồng thời đánh số mục ví dụ [1], [2], Trang All 48 69 II.1 About the data of the topic Đề cập thêm vấn đề thu thập data minh họa hệ thống phần II.1 51 Đưa thêm lý giải liệu III.3 The Limitations of the project thu thập không đủ lớn (vì hệ Đưa thêm mục hạn chế size Data thống hướng tới big data) vào cuối phần III.3 Đưa số gợi ý cho nghiên cứu tương lai lĩnh vực 67 III.2 Contributions of the project: Thêm mục “Some suggestions for future research on this field” vào mục III.2 Ý kiến Giảng viên hướng dẫn (Ký ghi rõ họ tên) Ý kiến Phản biện (Nếu Hội đồng yêu cầu Phản biện thông qua) 66 Hà Nội, ngày 02 tháng 07 năm 2020 Sinh viên (Ký ghi rõ họ tên) Ý kiến Chủ tịch Hội đồng (Kí ghi rõ họ tên) ... UNIVERSITY, HANOI INTERNATIONAL SCHOOL    GRADUATION PROJECT PROJECT NAME Electronic Medical Record (EMR) Database And Big Data Using Microsoft Azure Project SUPERVISOR: Assoc Prof Dr Nguyễn Thanh... hereby declare that the Graduation Project ? ?Electronic Medical Record (EMR) Database And Big Data Using Microsoft Azure? ?? is the results of my own research and has never been published in any... 7-create Big Data 54 8-create Big Data 54 9-create Big Data 55 10-create Big Data 55 11-create Big Data 56 12-create Big Data