An In-depth overview of artificial intelligence (AI) tool utilization across diverse phases of organ transplantation.

Journal: Journal of translational medicine
Published Date:

Abstract

Artificial Intelligence (AI) offers a revolutionary approach to improve decision-making in medicine through the use of advanced computational tools. Its ability to analyze large and complex datasets enables a thorough evaluation of multiple factors, leading to a deeper understanding of medical procedures. Numerous studies have demonstrated that AI has made significant advancements in areas such as organ allocation, donor-recipient matching, and immunosuppression protocols in organ transplantation. The transplantation process consists of three key stages: pre-transplant evaluation, the surgical procedure, and post-transplant management. AI can enhance all three stages by analyzing and integrating data from histopathological reports, lab results, radiological features, and patient demographics to aid in matching donors and recipients. Additionally, AI supports robotic-assisted surgery and optimizes post-transplant regimens while evaluating complications. Various researches have utilized machine learning (ML) to predict medication bioavailability immediately after transplantation and assess the risk of post-transplant complications based on factors like genetic phenotypes, age, gender, and body mass index. This review aims to gather information on AI applications across various stages of organ transplantation and elaborate the strategies and tools relevant to these processes.

Authors

  • Shiva Arjmandmazidi
    Molecular Medicine Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Hamid Reza Heidari
    Molecular Medicine Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Tohid Ghasemnejad
    UNSW BioMedical Machine Learning Lab (BML), School of Biomedical Engineering, UNSW Sydney, Sydney, NSW, 2052, Australia.
  • Zeinab Mori
    Molecular Medicine Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Leila Molavi
    Molecular Medicine Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Amir Meraji
    Molecular Medicine Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Shadi Kaghazchi
    Women's Reproductive Health Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Elnaz Mehdizadeh Aghdam
    Molecular Medicine Research Center, Tabriz University of Medical Sciences, Tabriz, Iran. mehdizadehe@tbzmed.ac.ir.
  • Soheila Montazersaheb
    Molecular Medicine Research Center, Tabriz University of Medical Sciences, Tabriz, Iran. smontazersaheb@gmail.com.