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International Advanced Research Journal in Science, Engineering and Technology
International Advanced Research Journal in Science, Engineering and Technology A Monthly Peer-Reviewed Multidisciplinary Journal
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← Back to VOLUME 8, ISSUE 5, MAY 2021

Predicting COPD, Diabetes and Heart Disease Using Machine Learning Algorithm

Kandigati John Prajwal, Likitha U K, Kosur Shriyaa Saivijya, Kavalakuntla Manikanta Reddy, Sushmita Kumari

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Abstract: This project mainly contains python, machine learning and web related concepts. The main aim of this project is to predict Chronic obstructive pulmonary disease, Diabetes and Heart disease using machine learning techniques and algorithms. In this project the Doctors/Patients/User can register in the webpage which we developed and again then can login. All their information will store it in the database. Once they login into the webpage they can choose which disease to predict like they will get options COPD, Diabetes and Heart. The selected disease prediction page will open and they can enter the patient details, mail id and the parameters asked in the webpage required to predict that particular disease. Once entering all the details, if they click on predict means they will get final results in the webpage like they have that particular disease or not, stage of the disease and treatment should be taken for that disease will be displayed on the final results. The same predicted results also send to the patient email whatever entered by the user/doctor/patient while entering their details. You can also see the data stored in the database in this project.

Keywords: Department, Presidency Tree, k-nn algorithm.

How to Cite:

[1] Kandigati John Prajwal, Likitha U K, Kosur Shriyaa Saivijya, Kavalakuntla Manikanta Reddy, Sushmita Kumari, “Predicting COPD, Diabetes and Heart Disease Using Machine Learning Algorithm,” International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2021.8548

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License.