Transplantation

A Fully Automated System Using A Convolutional Neural Network to Predict Renal Allograft Rejection: Extra-validation with Giga-pixel Immunostained Slides.

Pathologic diagnoses mainly depend on visual scoring by pathologists, a process that can be time-consuming, laborious, and susceptible to inter- and/or intra-observer variations. This study proposes a novel method to enhance pathologic scoring of renal allograft rejection. A fully automated system using a convolutional neural network (CNN) was developed to identify regions of interest (ROIs) and t...

CT male pelvic organ segmentation using fully convolutional networks with boundary sensitive representation.

Accurate segmentation of the prostate and organs at risk (e.g., bladder and rectum) in CT images is a crucial step for radiation therapy in the treatment of prostate cancer. However, it is a very challenging task due to unclear boundaries, large intra- and inter-patient shape variability, and uncertain existence of bowel gases and fiducial markers. In this paper, we propose a novel automatic segme...

3D radiotherapy dose prediction on head and neck cancer patients with a hierarchically densely connected U-net deep learning architecture.

The treatment planning process for patients with head and neck (H&N) cancer is regarded as one of the most complicated due to large target volume, mul...

Metabolomics Analysis in Acute Paraquat Poisoning Patients Based on UPLC-Q-TOF-MS and Machine Learning Approach.

Most paraquat (PQ) poisoned patients died from acute multiple organ failure (MOF) such as lung, kidney, and heart. However, the exact mechanism of int...

Simultaneous spatiotemporal tracking and oxygen sensing of transient implants in vivo using hot-spot MRI and machine learning.

A varying oxygen environment is known to affect cellular function in disease as well as activity of various therapeutics. For transient structures, wh...

ELM-MHC: An Improved MHC Identification Method with Extreme Learning Machine Algorithm.

The major histocompatibility complex (MHC) is a term for all gene groups of a major histocompatibility antigen. It binds to peptide chains derived fro...

OBELISK-Net: Fewer layers to solve 3D multi-organ segmentation with sparse deformable convolutions.

Deep networks have set the state-of-the-art in most image analysis tasks by replacing handcrafted features with learned convolution filters within end...

An integrated molecular diagnostic report for heart transplant biopsies using an ensemble of diagnostic algorithms.

BACKGROUND: We previously reported a microarray-based diagnostic system for heart transplant endomyocardial biopsies (EMBs), using either 3-archetype ...

Prediction of mortality following pediatric heart transplant using machine learning algorithms.

BACKGROUND: Optimizing transplant candidates' priority for donor organs depends on the accurate assessment of post-transplant outcomes. Due to the com...

Disturbance and uncertainty rejection performance for fractional-order complex dynamical networks.

This paper investigates the synchronization issue for a family of time-delayed fractional-order complex dynamical networks (FCDNs) with time delay, un...

Cellular cartography of the organ of Corti based on optical tissue clearing and machine learning.

The highly organized spatial arrangement of sensory hair cells in the organ of Corti is essential for inner ear function. Here, we report a new analyt...

Development and Evaluation of a Machine Learning Model for the Early Identification of Patients at Risk for Sepsis.

STUDY OBJECTIVE: The Third International Consensus Definitions (Sepsis-3) Task Force recommended the use of the quick Sequential [Sepsis-related] Orga...

Spinal cord detection in planning CT for radiotherapy through adaptive template matching, IMSLIC and convolutional neural networks.

BACKGROUND AND OBJECTIVE: The spinal cord is a very important organ that must be protected in treatments of radiotherapy (RT), considered an organ at ...

Knowledge-Aided Convolutional Neural Network for Small Organ Segmentation.

Accurate and automatic organ segmentation is critical for computer-aided analysis towards clinical decision support and treatment planning. State-of-t...

Using machine learning and an ensemble of methods to predict kidney transplant survival.

We used an ensemble of statistical methods to build a model that predicts kidney transplant survival and identifies important predictive variables. Th...

Real-time crash prediction models: State-of-the-art, design pathways and ubiquitous requirements.

Proactive traffic safety management systems can monitor traffic conditions in real-time, identify the formation of unsafe traffic dynamics, and implem...

The Protective Effects of Ciji-Hua'ai-Baosheng II Formula on Chemotherapy-Treated H Hepatocellular Carcinoma Mouse Model by Promoting Tumor Apoptosis.

Ciji-Hua'ai-Baosheng II Formula (CHB-II-F) is a traditional Chinese medical formula that has been shown in clinical practice to relieve side effects o...

Robot-assisted laparoscopic vs laparoscopic donor nephrectomy in renal transplantation: A meta-analysis.

BACKGROUND: Currently, the robot-assisted laparoscopic donor nephrectomy (RDN) technique is used for live donor nephrectomy. Does it provide sufficien...

Renal Function Impairment in Kidney Transplantation: Importance of Early BK Virus Detection.

BACKGROUND: BK virus allograft nephropathy is a major complication of kidney transplantation that markedly reduces graft survival (50% graft failure 2...

Treatment With Grazoprevir/Elbasvir for Renal Transplant Recipients With Chronic Hepatitis C Virus Infection and Impaired Allograft Function.

BACKGROUND: Direct-acing antiviral agents are highly efficient treatment options for chronic hepatitis C virus (HCV) infection after renal allograft t...