Predictive analysis of COVID-19 occurrence and vaccination impacts across the 50 US states.

Journal: Computers in biology and medicine
PMID: 39626459

Abstract

OBJECTIVE: This study aimed to outline a machine learning model to assess the effectiveness of vaccination in COVID-19 confirmed cases and fatalities. The proposed model was evaluated using external validation to ensure optimal protection of vaccinated populations, distinguishing between males and females.

Authors

  • Chinmayee Rayguru
    Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan. Electronic address: d610110001@tmu.edu.tw.
  • Atina Husnayain
    Department of Public Health, Monash University, Indonesia. Electronic address: Atina.Husnayain@monash.edu.
  • Hua-Sheng Chiu
    Department of Pediatrics, Baylor College of Medicine, Texas Children's Hospital Cancer Center, Houston, TX, USA. Electronic address: hchiu@bcm.edu.
  • Pavel Sumazin
    Department of Pediatrics, Baylor College of Medicine, Texas Children's Hospital Cancer Center, Houston, TX, USA. Electronic address: sumazin@bcm.edu.
  • Emily Chia-Yu Su
    Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan. emilysu@tmu.edu.tw.

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