Expression of Salivary miRNAs, Clinical, and Demographic Features in the Early Detection of Gastric Cancer: A Statistical and Machine Learning Analysis.

Journal: Journal of gastrointestinal cancer
Published Date: Nov 9, 2024

Abstract

OBJECTIVE: Gastric cancer ranks as one of the top five deadliest cancers worldwide and is often diagnosed at late stages. Analysis of saliva may provide a non-invasive approach for detection of malignancies in organs associated with the oral cavity. This research aims to analyze salivary microRNA expression together with clinical and demographic features with the aim of diagnosing gastric cancer.

Authors

  • Maryam Koopaie
    Department of Oral Medicine, School of Dentistry, Tehran University of Medical Sciences, North Kargar St, P.O.BOX:14395-433, Po. Code, Tehran, 14399-55991, Iran. mariakoopaie@gmail.com.
  • Sasan Arian-Kia
    Department of Oral Medicine, School of Dentistry, Tehran University of Medical Sciences, North Kargar St, P.O.BOX:14395-433, Po. Code, Tehran, 14399-55991, Iran.
  • Soheila Manifar
    Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran.
  • Mahnaz Fatahzadeh
    Division of Oral Medicine, Department of Oral Medicine, Rutgers School of Dental Medicine, 110 Bergen Street, Newark, NJ, 07103, USA.
  • Sajad Kolahdooz
    Universal Scientific Education and Research Network (USERN), Tehran University of Medical Sciences, Tehran, Iran.
  • Mansour Davoudi
    Department of Computer Science and Engineering and IT, School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran.

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