Analysis of the most influential factors affecting outcomes of lung transplant recipients: a multivariate prediction model based on UNOS Data.

Journal: BMJ open
PMID: 40379311

Abstract

OBJECTIVES: In lung transplantation (LTx), a priority is assigned to each candidate on the waiting list. Our primary objective was to identify the key factors that influence the allocation of priorities in LTx using machine learning (ML) techniques to enhance the process of prioritising patients.

Authors

  • Marsa Gholamzadeh
    Health Information Management Department, School of Allied Medical Sciences, Tehran University of Medical Sciences, No #17, 5th Floor, Farredanesh Alley, Ghods St, Enghelab Ave, Tehran, Iran. Electronic address: m-gholamzadeh@razi.tums.ac.ir.
  • Reza Safdari
    Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran. Electronic address: rsafdari@tums.ac.ir.
  • Mehrnaz Asadi Gharabaghi
    Department of Pulmonary Medicine, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran (the Islamic Republic of).
  • Hamidreza Abtahi
    Pulmonary and Critical Care Medicine Department, Thoracic Research Center, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran.

Keywords

External Resources

Popular Topics
Recent Journals