Identification of gene profiles related to the development of oral cancer using a deep learning technique.

Journal: BMC medical genomics
PMID: 36849997

Abstract

BACKGROUND: Oral cancer (OC) is a debilitating disease that can affect the quality of life of these patients adversely. Oral premalignant lesion patients have a high risk of developing OC. Therefore, identifying robust survival subgroups among them may significantly improve patient therapy and care. This study aimed to identify prognostic biomarkers that predict the time-to-development of OC and survival stratification for patients using state-of-the-art machine learning and deep learning.

Authors

  • Leili Tapak
    Modeling of Noncommunicable Diseases Research Center, Hamadan University of Medical Sciences, Hamadan, Iran.
  • Mohammad Kazem Ghasemi
    Department of Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.
  • Saeid Afshar
    Research Center for Molecular Medicine, Hamadan University of Medical Science, Hamadan, Iran.
  • Hossein Mahjub
    Research Center for Health Sciences and Department of Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.
  • Alireza Soltanian
    Department of Biostatistics, School of Public Health and Modeling of Noncommunicable Diseases Research Center, Hamadan University of Medical Sciences, Hamadan, Iran.
  • Hassan Khotanlou
    Department of Computer Engineering, Bu-Ali Sina University, Hamedan, Iran.

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