Transplantation

FCN Based Label Correction for Multi-Atlas Guided Organ Segmentation.

Segmentation of medical images using multiple atlases has recently gained immense attention due to t...

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...

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...

Can Machine Learning Improve Screening for Targeted Delinquency Prevention Programs?

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

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...

[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...

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...

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...

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...

Relevant Features in Nonalcoholic Steatohepatitis Determined Using Machine Learning for Feature Selection.

We investigated the prevalence and the most relevant features of nonalcoholic steatohepatitis (NASH...

Graft Rejection Prediction Following Kidney Transplantation Using Machine Learning Techniques: A Systematic Review and Meta-Analysis.

Kidney transplantation is recommended for patients with End-Stage Renal Disease (ESRD). However, com...

Deep learning detects impending organ injury in the clinic.

DeepDSSR: Deep Learning Structure for Human Donor Splice Sites Recognition.

Human genes often, through alternative splicing of pre-messenger RNAs, produce multiple mRNAs and pr...

A sustainable HL7 FHIR based ontology for PHR data.

One of the most widely acknowledged standards in health informatics is HL7 (Health Level 7 Internati...

A Robotic Platform for 3D Forelimb Rehabilitation with Rats.

In an attempt to promote greater functional recovery after spinal cord injury, researchers have begu...

Re: Minimally Invasive, Robot-Assisted Procedure for Kidney Transplantation among Morbidly Obese: Positive Outcomes at 5 Years Post-Transplant.

SuperCT: a supervised-learning framework for enhanced characterization of single-cell transcriptomic profiles.

Characterization of individual cell types is fundamental to the study of multicellular samples. Sing...

Liver and Lung Transplant Advances.

Ovarian tissue cryopreservation and transplantation: what advances are necessary for this fertility preservation modality to no longer be considered experimental?

Heart rate variability based machine learning models for risk prediction of suspected sepsis patients in the emergency department.

Early identification of high-risk septic patients in the emergency department (ED) may guide appropr...

Using Deep Learning in Automated Detection of Graft Detachment in Descemet Membrane Endothelial Keratoplasty: A Pilot Study.

PURPOSE: To evaluate a deep learning-based method to automatically detect graft detachment (GD) afte...