A cross-sectional study of parental perspectives on children about COVID-19 and classification using machine learning models.

Journal: Frontiers in public health
PMID: 39882116

Abstract

BACKGROUND AND OBJECTIVE: This study delves into the parenting cognition perspectives on COVID-19 in children, exploring symptoms, transmission modes, and protective measures. It aims to correlate these perspectives with sociodemographic factors and employ advanced machine-learning techniques for comprehensive analysis.

Authors

  • Fahmida Kousar
    Department of Amraze Atfal, A and U Tibbia College & Hospital, Delhi University, New Delhi, India.
  • Arshiya Sultana
    Department of Ilmul Qabalat wa Amraze Niswan, National Institute of Unani Medicine, Ministry of AYUSH, Bengaluru, Karnataka, India.
  • Marwan Ali Albahar
    Computer Science Department, Umm Al-Qura University, Mecca, Saudi Arabia.
  • Manoj Shamkuwar
    Department of Panchkarma, A and U Tibbia College & Hospital, Delhi University, New Delhi, India.
  • Md Belal Bin Heyat
    CenBRAIN Neurotech Center of Excellence, School of Engineering, Westlake University, Hangzhou, Zhejiang, China.
  • Mohd Ammar Bin Hayat
    College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, China.
  • Saba Parveen
    College of Electronics and Information Engineering, Shenzhen University, Shenzhen, China.
  • John Irish G Lira
    National University Manila, Manila, Philippines.
  • Khaleequr Rahman
    Department of Ilmul Saidla, National Institute of Unani Medicine, Ministry of AYUSH, Government of India, Bengaluru, Karnataka, India.
  • Abdullah Alammari
    Faculty of Education, Curriculums and Teaching Department, Umm Al-Qura University, Makkah, Saudi Arabia.
  • Eram Sayeed
    Triveni Rai Kisan Mahila Mahavidyalaya, D. D. U. Gorakhpur University, Kushinagar, India.

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