Public health nurse perspectives on predicting nonattendance for cervical cancer screening through classification, ensemble, and deep learning models.

Journal: Public health nursing (Boston, Mass.)
PMID: 38757647

Abstract

OBJECTIVES: Women's attendance to cervical cancer screening (CCS) is a major concern for healthcare providers in community. This study aims to use the various algorithms that can accurately predict the most barriers of women for nonattendance to CS.

Authors

  • Seeta Devi
    Symbiosis College of Nursing (SCON), Symbiosis International Deemed University (SIDU), Pune- 412115, India.
  • Rupali Gangarde
    Symbiosis Institute of Technology (SIT), Symbiosis International Deemed University (SIDU), Pune, India.
  • Shubhangi Deokar
    Symbiosis Institute of Technology (SIT), Symbiosis International Deemed University (SIDU), Pune, India.
  • Sayyed Faheemuddin Muqeemuddin
    Symbiosis Institute of Technology (SIT), Symbiosis International Deemed University (SIDU), Pune, India.
  • Sanidhya Rajendra Awasthi
    Symbiosis Institute of Technology (SIT), Symbiosis International Deemed University (SIDU), Pune, India.
  • Sameer Shekhar
    Symbiosis Institute of Technology (SIT), Symbiosis International Deemed University (SIDU), Pune, India.
  • Raghav Sonchhatra
    Symbiosis Institute of Technology (SIT), Symbiosis International Deemed University (SIDU), Pune, India.
  • Sonopant Joshi
    Symbiosis College of Nursing (SCON), Symbiosis International Deemed University (SIDU), Pune, India.

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