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Analysis of Diabetes and Heart Disease in Big Data Using MapReduce Framework

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International Conference on Innovative Computing and Communications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1165))

Abstract

MapReduce is a programming algorithm which is used for generating a simplified and relative collection of large datasets such as Big Data. In our paper, we relate MapReduce to the healthcare system to make the effective and spontaneous decision making. In life science, an enormous amount of data is generated on a daily basis. But most space is occupied by routinely generated data of non-communicable diseases like blood pressure, diabetes, etc. Diabetes and heart-related diseases are one of the most commonly found around the world. These non- communicable diseases are usually caused by changing lifestyle, food that we eat, stress is becoming the causes of growth in the non-communicable diseases, and so with an increasing number of patients comes, the number of patients records to be handled, this huge amount of data is made useful through a technique called Big Data which contains one such algorithm called MapReduce. By applying MapReduce, the huge clinical data is filtered in different categories which can be easily read for future reference. The main purpose of our paper is to focus on filtering various parameters of diabetes as well as heart diseases, putting clinical data into developing medical intelligence for creating a patient-centered healthcare system. Considering our dataset, 45–54 Age group of people have maximum prone to diabetes and when it comes to heart-related disorders, people above the age of 65 are mostly suffering from this disease.

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Acknowledgements

We wish to show our gratitude and sincere thanks to our mentor Dr. Ankur Saxena, Amity Institute of Biotechnology, Noida, for his guidance, assistance, insights, and expertise. We also express our sincere thanks to the Amity Institute of Biotechnology, Amity University, Noida, for providing us this opportunity and a great platform to work on.

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Authors and Affiliations

  1. Amity Institute of Biotechnology, Amity University, Noida, Uttar Pradesh, India

    Manpreet Kaur Saluja, Isha Agarwal, Urvija Rani & Ankur Saxena

Authors
  1. Manpreet Kaur Saluja
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  2. Isha Agarwal
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  3. Urvija Rani
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  4. Ankur Saxena
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Correspondence to Ankur Saxena .

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Editors and Affiliations

  1. Maharaja Agrasen Institute of Technology, Rohini, Delhi, India

    Deepak Gupta

  2. Maharaja Agrasen Institute of Technology, Rohini, Delhi, India

    Ashish Khanna

  3. CHRIST (Deemed to be University), Bengaluru, Karnataka, India

    Siddhartha Bhattacharyya

  4. Department of Information Technology, Faculty of Computers and Information, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  5. Department of Computer Science, Shaheed Sukhdev College of Business Studies, University of Delhi, Rohini, Delhi, India

    Sameer Anand

  6. Department of Computer Science, Shaheed Sukhdev College of Business Studies, University of Delhi, Rohini, Delhi, India

    Ajay Jaiswal

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Saluja, M.K., Agarwal, I., Rani, U., Saxena, A. (2021). Analysis of Diabetes and Heart Disease in Big Data Using MapReduce Framework. In: Gupta, D., Khanna, A., Bhattacharyya, S., Hassanien, A.E., Anand, S., Jaiswal, A. (eds) International Conference on Innovative Computing and Communications. Advances in Intelligent Systems and Computing, vol 1165. Springer, Singapore. https://doi.org/10.1007/978-981-15-5113-0_3

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