COVID-19 Risk Prediction for Diabetic Patients Using Fuzzy Inference System and Machine Learning Approaches.

Aggarwal, Alok; Chakradar, Madam; Bhatia, Manpreet Singh; Kumar, Manoj; Stephan, Thompson; Gupta, Sachin Kumar; Alsamhi, S H; Al-Dois, Hatem

Aggarwal, Alok; Chakradar, Madam; Bhatia, Manpreet Singh; Kumar, Manoj; Stephan, Thompson; Gupta, Sachin Kumar; Alsamhi, S H; Al-Dois, Hatem.

Afiliación

Aggarwal A; School of Computer Science, University of Petroleum & Energy Studies (UPES), Bidholi, Dehradun, India.
Chakradar M; School of Computer Science, University of Petroleum & Energy Studies (UPES), Bidholi, Dehradun, India.
Bhatia MS; School of Computer Science, University of Petroleum & Energy Studies (UPES), Bidholi, Dehradun, India.
Kumar M; School of Computer Science, University of Petroleum & Energy Studies (UPES), Bidholi, Dehradun, India.
Stephan T; Department of Computer Science & Engineering, Amity School of Engineering and Technology, Amity University Uttar Pradesh, Noida, India.
Gupta SK; School of Electronics and Communication Engineering, Shri Mata Vaishno Devi University, Katra, India.
Alsamhi SH; Software Research Institute, Athlone Institute of Technology, TUS, Athlone, Ireland.
Al-Dois H; Department of Electrical Engineering, IBB University, Ibb, Yemen.

J Healthc Eng ; 2022: 4096950, 2022.

Article en En | MEDLINE | ID: mdl-35368915

Asunto(s)

COVID-19; Diabetes Mellitus; Algoritmos; Humanos; Modelos Logísticos; Aprendizaje Automático

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Diabetes Mellitus / COVID-19 Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: J Healthc Eng Año: 2022 Tipo del documento: Article País de afiliación: India Pais de publicación: Reino Unido

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