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Context-Aware Systems and Applications, and Nature of Computation and Communication. 9th EAI International Conference, ICCASA 2020, and 6th EAI International Conference, ICTCC 2020, Thai Nguyen, Vietnam, November 26–27, 2020, Proceedings

Research Article

Predicting the Level of Hypertension Using Machine Learning

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  • @INPROCEEDINGS{10.1007/978-3-030-67101-3_9,
        author={Pham Thu Thuy and Nguyen Thanh Tung and Chu Duc Hoang},
        title={Predicting the Level of Hypertension Using Machine Learning},
        proceedings={Context-Aware Systems and Applications, and Nature of Computation and Communication. 9th EAI International Conference, ICCASA 2020, and 6th EAI International Conference, ICTCC 2020, Thai Nguyen, Vietnam, November 26--27, 2020, Proceedings},
        proceedings_a={ICCASA \& ICTCC},
        year={2021},
        month={1},
        keywords={Machine learning Data mining Healthcare Hypertension},
        doi={10.1007/978-3-030-67101-3_9}
    }
    
  • Pham Thu Thuy
    Nguyen Thanh Tung
    Chu Duc Hoang
    Year: 2021
    Predicting the Level of Hypertension Using Machine Learning
    ICCASA & ICTCC
    Springer
    DOI: 10.1007/978-3-030-67101-3_9
Pham Thu Thuy1, Nguyen Thanh Tung2,*, Chu Duc Hoang
  • 1: Science and Technology Department
  • 2: International School
*Contact email: tungnt@isvnu.vn

Abstract

In recent years, data mining has been put into research and application in many different areas in the world such as economy, education, sports, telecommunications, etc. And the health - health care [1] sector is not out of this trend. If it is possible to successfully analyze the data [2,3,4] from the huge amount of data of diseases, patients and hospitals every day, it can help a lot of doctors in the process of diagnosis, examination and treatment of diseases for patients. The problem raised here is whether we can accurately diagnose the patient’s disease based on the information provided. The information provided may be age, gender, occupation, symptoms, test information, etc. from which it is necessary to achieve the most accurate diagnosis possible to minimize the work pressure for the medical team as well as minimize the time of diagnosis.

Keywords
Machine learning Data mining Healthcare Hypertension
Published
2021-01-13
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-67101-3_9
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