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    Recommender Diagnosis System with Fuzzy Logic in Cloud Environment

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    Author
    ElKafrawy, Passent cc
    Elnemr, Rasha
    Aboghazalah, Maie
    Elsayed, Nedaa
    elsayed, Ayman
    Subject
    Medical diagnostic imaging
    Electrocardiography
    Recommender systems
    Date
    2023-01
    
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    Abstract
    Recommendation systems are now used in a wide range in many fields. In the medical field, recommendation systems have a great stature to both doctors and patients for its accurate prediction. It can reduce the time and efforts spent by doctors and patients. The present work introduces a simple and effective methodology for medical recommendation system based on fuzzy logic. Fuzzy logic is an important method to be used based on fuzzy input data. The input data for each patient are not the same, on which recommendation can differ. This work aims to develop techniques for handling the patient data to urge accurate lifestyle recommendations to the patient. Fuzzy logic is utilized to form different recommendations for the patient like lifestyle recommendations, medicine recommendations, and sports recommendations based on different patient factors like age, gender and patient diseases. After evaluating the system its efficiency reached 94%. This Experiment is the final module in a four modules recommendation system. The first one is responsible for diagnosing chest diseases using ECG signals. The second one makes diagnosis using X-ray images. The third is utilizing the security of the whole system through encryption when sending user data over the cloud.
    Department
    Computer Science
    Publisher
    IEEE
    DOI
    https://doi.org/10.1109/ESOLEC54569.2022.10009214
    ae974a485f413a2113503eed53cd6c53
    https://doi.org/10.1109/ESOLEC54569.2022.10009214
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