AIMC Topic: Tissue Donors
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Crossroads in Liver Transplantation: Is Artificial Intelligence the Key to Donor-Recipient Matching?
Medicina (Kaunas, Lithuania)
Nov 28, 2022
Liver transplantation outcomes have improved in recent years. However, with the emergence of expanded donor criteria, tools to better assist donor-recipient matching have become necessary. Most of the currently proposed scores based on conventional b...
Artificial Intelligence in Liver Transplantation.
Transplantation proceedings
Nov 2, 2021
BACKGROUND: Advancements based on artificial intelligence have emerged in all areas of medicine. Many decisions in organ transplantation can now potentially be addressed in a more precise manner with the aid of artificial intelligence.
Statistical methods versus machine learning techniques for donor-recipient matching in liver transplantation.
PloS one
May 21, 2021
Donor-Recipient (D-R) matching is one of the main challenges to be fulfilled nowadays. Due to the increasing number of recipients and the small amount of donors in liver transplantation, the allocation method is crucial. In this paper, to establish a...
Validating machine learning approaches for prediction of donor related complication in microsurgical breast reconstruction: a retrospective cohort study.
Scientific reports
Mar 10, 2021
Autologous reconstruction using abdominal flaps remains the most popular method for breast reconstruction worldwide. We aimed to evaluate a prediction model using machine-learning methods and to determine which factors increase abdominal flap donor s...
Image-Based Machine Learning Algorithms for Disease Characterization in the Human Type 1 Diabetes Pancreas.
The American journal of pathology
Dec 8, 2020
Emerging data suggest that type 1 diabetes affects not only the β-cell-containing islets of Langerhans, but also the surrounding exocrine compartment. Using digital pathology, machine learning algorithms were applied to high-resolution, whole-slide i...
Parameter estimation of the homodyned K distribution based on an artificial neural network for ultrasound tissue characterization.
Ultrasonics
Dec 1, 2020
The homodyned K (HK) distribution allows a general description of ultrasound backscatter envelope statistics with specific physical meanings. In this study, we proposed a new artificial neural network (ANN) based parameter estimation method of the HK...
Personalized prediction of delayed graft function for recipients of deceased donor kidney transplants with machine learning.
Scientific reports
Oct 27, 2020
Machine learning (ML) has shown its potential to improve patient care over the last decade. In organ transplantation, delayed graft function (DGF) remains a major concern in deceased donor kidney transplantation (DDKT). To this end, we harnessed ML t...
Identifying scenarios of benefit or harm from kidney transplantation during the COVID-19 pandemic: A stochastic simulation and machine learning study.
American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
Jul 15, 2020
Clinical decision-making in kidney transplant (KT) during the coronavirus disease 2019 (COVID-19) pandemic is understandably a conundrum: both candidates and recipients may face increased acquisition risks and case fatality rates (CFRs). Given our po...
[Renal graft survival in patients transplanted from organs of deceased donors].
Revista medica del Instituto Mexicano del Seguro Social
Jul 1, 2019
BACKGROUND: In Mexico, out of the total number of transplants it was reported, in 2014, a frequency of 29% of deceased donor renal transplantation (DDRT). The use of kidneys from deceased elderly donors is increasing over the years. Currently, some a...
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