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Novel Approach for Predicting COVID-19 Symptoms using ARM based APRIORI Algorithm
6th International Conference on Computing Methodologies and Communication, ICCMC 2022 ; : 1577-1580, 2022.
Article in English | Scopus | ID: covidwho-1840252
ABSTRACT
Based on several pre-defined standard symptoms, a model that can determine the coronavirus illness as positive is developed. Guidelines for these symptoms have been issued by the World Health Organization (WHO) and India's Ministry of Health and Family Welfare. In this model the various symptoms of the illnesses is given to the system. It allows users to discuss their symptoms, with the algorithm predicting a condition based on factual information. This factual information is then evaluated using the ARM based Apriori algorithm to get the most accurate results. Other conventional models such as Support Vector Machine (SVM), Artificial Neural Networks (ANNs), and Random Forests (RF) are considered and have analyzed the predictions and have found that the proposed algorithm predicts a higher accuracy score. © 2022 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Prognostic study Language: English Journal: 6th International Conference on Computing Methodologies and Communication, ICCMC 2022 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Prognostic study Language: English Journal: 6th International Conference on Computing Methodologies and Communication, ICCMC 2022 Year: 2022 Document Type: Article