Abstract
In the medical industry, patients must wait a long time for a health check-up at the hospital because the number of patients is too large for the hospital to accommodate. As a result, by employing technologies such as machine learning, the medical industry will be able to speed up the process of identifying diseases. The data and results can help people and serve as a reference in predicting a problem. In this study, the use of this machine learning method is seen to help patients and the medical industry predict disease based on symptom data. Moreover, it also will create an interface to make it easy for user to choose symptom and to display the results using Python. A confusion matrix will be used to evaluate the dataset's accuracy so that more accurate results may be generated.
Metadata
Item Type: | Book Section |
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Creators: | Creators Email / ID Num. Mohd Faisol, Muhammad Faiz UNSPECIFIED Osman, Mohd Nizam UNSPECIFIED |
Subjects: | Q Science > Q Science (General) > Machine learning Q Science > QA Mathematics > Mathematical statistics. Probabilities > Prediction analysis |
Divisions: | Universiti Teknologi MARA, Perlis > Arau Campus > Faculty of Computer and Mathematical Sciences |
Page Range: | pp. 85-86 |
Keywords: | Cost, time, disease, machine learning |
Date: | 2023 |
URI: | https://ir.uitm.edu.my/id/eprint/100524 |