Transplantation

Technological Innovation in Outpatient Assistance for Chronic Liver Disease and Liver Transplant Patients During the Coronavirus Disease Outbreak: A Method to Minimize Transmission.

The compatibility of theoretical frameworks with machine learning analyses in psychological research.

Supervised machine learning has been increasingly used in psychology and psychiatry research. Machin...

Results of Green Indocyanine in the Use of the R1T1 Robot as Aid in the Pre-operative Process of Hepatic Organ Transplant: Experiment in Wistar Rats.

Since the beginning of the history of transplants, numerous difficulties have been faced in the effe...

CHEER: HierarCHical taxonomic classification for viral mEtagEnomic data via deep leaRning.

The fast accumulation of viral metagenomic data has contributed significantly to new RNA virus disco...

Cochlear implant telemedicine: Remote fitting based on psychoacoustic self-tests and artificial intelligence.

This study aims to assess the feasibility of autonomous cochlear implant (CI) fitting by adult CI r...

Using Machine Learning to Predict Early Onset Acute Organ Failure in Critically Ill Intensive Care Unit Patients With Sickle Cell Disease: Retrospective Study.

BACKGROUND: Sickle cell disease (SCD) is a genetic disorder of the red blood cells, resulting in mul...

Discovering the hidden messages within cell trajectories using a deep learning approach for in vitro evaluation of cancer drug treatments.

We describe a novel method to achieve a universal, massive, and fully automated analysis of cell mot...

A Novel Radial Basis Neural Network-Leveraged Fast Training Method for Identifying Organs in MR Images.

We propose a new method for fast organ classification and segmentation of abdominal magnetic resonan...

How to do it: a robotic kidney autotransplant.

We describe Australia's first reported case of robotic kidney autotransplantation for a complex rena...

SPST-CNN: Spatial pyramid based searching and tagging of liver's intraoperative live views via CNN for minimal invasive surgery.

Laparoscopic liver surgery is challenging to perform because of compromised ability of the surgeon t...

Machine Learning Classification Algorithms to Predict aGvHD following Allo-HSCT: A Systematic Review.

BACKGROUND:  The acute graft-versus-host disease (aGvHD) is the most important cause of mortality in...

Predicting severe clinical events by learning about life-saving actions and outcomes using distant supervision.

Medical error is a leading cause of patient death in the United States. Among the different types of...

Caregiver perspectives on a smart home-based socially assistive robot for individuals with Alzheimer's disease and related dementia.

: Innovative assistive technology can address aging-in-place and caregiving needs of individuals wit...

Re: Andrea Gallioli, Angelo Territo, Romain Boissier, et al. Learning Curve in Robotic-assisted Kidney Transplantation: Results from the European Robotic Urological Society Working Group. Eur Urol. In press. https://doi.org/10.1016/j.eururo.2019.12.008.

Reply to Jinna Yao, Henry C.C. Pleass, and Howard M.H. Lau's Letter to the Editor re: Andrea Gallioli, Angelo Territo, Romain Boissier, et al. Learning Curve in Robot-assisted Kidney Transplantation: Results from the European Robotic Urological Society Working Group. Eur Urol. In press. https://doi.org/10.1016/j.eururo.2019.12.008.

Abdominal multi-organ auto-segmentation using 3D-patch-based deep convolutional neural network.

Segmentation of normal organs is a critical and time-consuming process in radiotherapy. Auto-segment...

A method of rapid quantification of patient-specific organ doses for CT using deep-learning-based multi-organ segmentation and GPU-accelerated Monte Carlo dose computing.

PURPOSE: One technical barrier to patient-specific computed tomography (CT) dosimetry has been the l...

A fast conformal predictive system with regularized extreme learning machine.

A conformal predictive system(CPS) is based on the learning framework of conformal prediction, which...

Artificial intelligence and machine learning in nephropathology.

Artificial intelligence (AI) for the purpose of this review is an umbrella term for technologies emu...

Improving accuracy and robustness of deep convolutional neural network based thoracic OAR segmentation.

Deep convolutional neural network (DCNN) has shown great success in various medical image segmentati...

Extracting Structured Genotype Information from Free-Text HLA Reports Using a Rule-Based Approach.

BACKGROUND: Human leukocyte antigen (HLA) typing is important for transplant patients to prevent a s...