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Predicting the COVID-19 Patients Status Using Chest CT Scan Findings: A Risk Assessment Model Based on Decision Tree Analysis

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Application of Omic Techniques to Identify New Biomarkers and Drug Targets for COVID-19

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Acknowledgments

An early version of this manuscript was submitted as a preprint and is available at https://www.researchsquare.com/article/rs-56387/v3. The present version contains updated information.

Author information

Authors and Affiliations

  1. Colorectal Research Center, Iran University of Medical Sciences, Tehran, Iran

    Atefeh Talebi

  2. Urology and Nephrology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Nasrin Borumandnia

  3. Department of Radiology, Health Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran

    Ramezan Jafari

  4. Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Mohamad Amin Pourhoseingholi

  5. Health Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran

    Nematollah Jonaidi Jafari

  6. Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Sara Ashtari

  7. Department of Radiology, Health Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran

    Saeid Roozpeykar

  8. Anesthesia and Critical Care Department, Hamadan University of Medical Sciences, Hamadan, Iran

    Farshid RahimiBashar

  9. Behavioral Sciences Research Center, LifeStyle Institute, Nursing Faculty, Baqiyatallah University of Medical Sciences, Tehran, Iran

    Leila Karimi

  10. Department of Psychiatry, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany

    Paul C. Guest

  11. Laboratory of Translational Psychiatry, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany

    Paul C. Guest

  12. Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil

    Paul C. Guest

  13. Surgical Oncology Research Center, Mashhad University of Medical Sciences, Mashhad, Iran

    Tannaz Jamialahmadi

  14. Applied Biomedical Research Center, Mashhad University of Medical Sciences, Vakilabad blvd., Mashhad, Iran

    Tannaz Jamialahmadi

  15. Trauma Research Center, Nursing Faculty, Baqiyatallah University of Medical Sciences, Tehran, Iran

    Amir Vahedian-Azimi

  16. Medical ICU and Pulmonary unit, Shariati hospital, Tehran University of Medical Sciences, Tehran, Iran

    Keivan Gohari-moghadam

  17. Applied Biomedical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran

    Amirhossein Sahebkar

  18. Biotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran

    Amirhossein Sahebkar

  19. Department of Biotechnology, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran

    Amirhossein Sahebkar

Authors
  1. Atefeh Talebi
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  2. Nasrin Borumandnia
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  3. Ramezan Jafari
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  4. Mohamad Amin Pourhoseingholi
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  5. Nematollah Jonaidi Jafari
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  6. Sara Ashtari
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  7. Saeid Roozpeykar
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  8. Farshid RahimiBashar
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  9. Leila Karimi
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  10. Paul C. Guest
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  11. Tannaz Jamialahmadi
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  12. Amir Vahedian-Azimi
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  13. Keivan Gohari-moghadam
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  14. Amirhossein Sahebkar
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Corresponding author

Correspondence to Keivan Gohari-moghadam .

Editor information

Editors and Affiliations

  1. University of Campinas, Campinas, São Paulo, Brazil

    Paul C. Guest

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Talebi, A. et al. (2023). Predicting the COVID-19 Patients Status Using Chest CT Scan Findings: A Risk Assessment Model Based on Decision Tree Analysis. In: Guest , P.C. (eds) Application of Omic Techniques to Identify New Biomarkers and Drug Targets for COVID-19. Advances in Experimental Medicine and Biology(), vol 1412. Springer, Cham. https://doi.org/10.1007/978-3-031-28012-2_13

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