Transplantation

A fatal invasive pulmonary infection in an adult patient with malignant lung adenocarcinoma.

BACKGROUND AND PURPOSE: complex as a ubiquitous environmental mold is increasingly reported to caus...

Artificial neural network and bioavailability of the immunosuppression drug.

PURPOSE OF REVIEW: The success of organ transplant is determined by number of demographic, clinical,...

Artificial intelligence in transplantation (machine-learning classifiers and transplant oncology).

PURPOSE OF REVIEW: To highlight recent efforts in the development and implementation of machine lear...

Artificial intelligence and organ transplantation: challenges and expectations.

PURPOSE OF REVIEW: Classifiers based on artificial intelligence have emerged in all areas of medicin...

Machine-learning algorithms for predicting results in liver transplantation: the problem of donor-recipient matching.

PURPOSE OF REVIEW: Classifiers based on artificial intelligence can be useful to solve decision prob...

Machine learning methods in organ transplantation.

PURPOSE OF REVIEW: Machine learning techniques play an important role in organ transplantation. Anal...

Deep neural networks capture texture sensitivity in V2.

Deep convolutional neural networks (CNNs) trained on visual objects have shown intriguing ability to...

Deep Learning Based Lung Region Segmentation with Data Preprocessing by Generative Adversarial Nets.

In endoscopic surgery, it is necessary to understand the three-dimensional structure of the target r...

Combining Superpixels and Deep Learning Approaches to Segment Active Organs in Metastatic Breast Cancer PET Images.

Semi-automatic measurements are performed on FDG PET-CT images to monitor the evolution of metastati...

Therapeutic effect of robot-assisted laparoscopic sacrocolpopexy in the treatment of pelvic organ prolapse.

OBJECTIVES: To assess short-term functional outcomes achieved by robot-assisted sacrocolpopexy for p...

Seeing the Forest for the Trees: Random Forest Models for Predicting Survival in Kidney Transplant Recipients.

The rise and fall of the model for end-stage liver disease score and the need for an optimized machine learning approach for liver allocation.

PURPOSE OF REVIEW: The Model for End-Stage Liver Disease (MELD) has been used to rank liver transpla...

Using federated data sources and Varian Learning Portal framework to train a neural network model for automatic organ segmentation.

PURPOSE: In this study we trained a deep neural network model for female pelvis organ segmentation u...

Deep learning predicts function of live retinal pigment epithelium from quantitative microscopy.

Increases in the number of cell therapies in the preclinical and clinical phases have prompted the n...

Can Machine Learning Improve Screening for Targeted Delinquency Prevention Programs?

The cost-effectiveness of targeted delinquency prevention programs for children depends on the accur...

Predicting Acute Graft-Versus-Host Disease Using Machine Learning and Longitudinal Vital Sign Data From Electronic Health Records.

PURPOSE: Acute graft-versus-host disease (aGVHD) remains a significant complication of allogeneic he...

Comparison of semi-automatic and deep learning-based automatic methods for liver segmentation in living liver transplant donors.

PURPOSE: To compare the accuracy and repeatability of emerging machine learning based (i.e. deep) au...

Automatic Segmentation of Multiple Organs on 3D CT Images by Using Deep Learning Approaches.

This chapter focuses on modern deep learning techniques that are proposed for automatically recogniz...

[Volume Measurements of Post-transplanted Liver of Pediatric Recipients Using Workstations and Deep Learning].

PURPOSE: The purpose of this study was to propose a method for segmentation and volume measurement o...

Iatrogenic Cushing's syndrome as a consequence of nasal use of Betamethasone spray during pregnancy.

INTRODUCTION: Glucocorticoids (GC) are largely used for their anti-inflammatory and immunosuppressiv...

Using a machine learning algorithm to predict acute graft-versus-host disease following allogeneic transplantation.

Acute graft-versus-host disease (aGVHD) is 1 of the critical complications that often occurs followi...