Transplantation

[The first 50 robot-assisted donor nephrectomies : Lessons learned].

BACKGROUND: Minimally invasive donor nephrectomy (DN) is considered the gold standard, but the role of robot-assisted surgery is still controversial.

Dermoscopic Features of Giant Molluscum Contagiosum in a Patient with Acquired Immunodeficiency Syndrome.

Giant molluscum contagiosum (MC) is a peculiar variant of the disease with the presence of multiple or single lesions larger than 5 mm. In contrast to typical molluscum contagiosum, dermoscopic features of giant lesions have been poorly described, and none of the reports included multiple giant lesions in an immunocompromised patient. We present a patient with acquired immunodeficiency syndrome di...

Stability and compatibility of methotrexate and dexamethasone in 0.9% sodium chloride for intrathecal injection.

The stability of a mixture of methotrexate and dexamethasone sodium phosphate in 0.9% sodium chloride for intrathecal (IT) injection was assessed. To ...

Robot-Assisted Total Pancreatectomy With Autologous Islet Cell Transplantation: Perioperative Nursing Considerations.

Chronic pancreatitis (CP) is an inflammatory disease of the pancreas that causes pain and gastrointestinal problems in patients. Robot-assisted total ...

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 cause an invasive fungal infection in immunosuppressiv...

Artificial neural network and bioavailability of the immunosuppression drug.

PURPOSE OF REVIEW: The success of organ transplant is determined by number of demographic, clinical, immunological and genetic variables. Artificial i...

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

PURPOSE OF REVIEW: To highlight recent efforts in the development and implementation of machine learning in transplant oncology - a field that uses li...

Artificial intelligence and organ transplantation: challenges and expectations.

PURPOSE OF REVIEW: Classifiers based on artificial intelligence have emerged in all areas of medicine. Although very subtle, many decisions in organ t...

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 problems related to the inclusion or removal of possib...

Machine learning methods in organ transplantation.

PURPOSE OF REVIEW: Machine learning techniques play an important role in organ transplantation. Analysing the main tasks for which they are being appl...

Deep neural networks capture texture sensitivity in V2.

Deep convolutional neural networks (CNNs) trained on visual objects have shown intriguing ability to predict some response properties of visual cortic...

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 region to improve safety. For organs that do not de...

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 metastatic sites in the clinical follow-up of metastatic br...

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 pelvic organ prolapse.

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

Advanced imaging techniques for chronic pancreatitis.

MRI and MRCP play an important role in the diagnosis of chronic pancreatitis (CP) by imaging pancreatic parenchyma and ducts. MRI/MRCP is more widely ...

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 transplant candidates since 2002, and at the time bringing...

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 using data from several sites without any personal ...

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 need for reliable and noninvasive assays to validat...

Can Machine Learning Improve Screening for Targeted Delinquency Prevention Programs?

The cost-effectiveness of targeted delinquency prevention programs for children depends on the accuracy of the screening process. Screening accuracy i...