Transplantation

Comparative Analysis for Prediction of Kidney Disease Using Intelligent Machine Learning Methods.

Chronic kidney disease (CKD) is a major burden on the healthcare system because of its increasing prevalence, high risk of progression to end-stage renal disease, and poor morbidity and mortality prognosis. It is rapidly becoming a global health crisis. Unhealthy dietary habits and insufficient water consumption are significant contributors to this disease. Without kidneys, a person can only live ...

Application of information theoretic feature selection and machine learning methods for the development of genetic risk prediction models.

In view of the growth of clinical risk prediction models using genetic data, there is an increasing need for studies that use appropriate methods to select the optimum number of features from a large number of genetic variants with a high degree of redundancy between features due to linkage disequilibrium (LD). Filter feature selection methods based on information theoretic criteria, are well suit...

Forecasting of Patient-Specific Kidney Transplant Function With a Sequence-to-Sequence Deep Learning Model.

IMPORTANCE: Like other clinical biomarkers, trajectories of estimated glomerular filtration rate (eGFR) after kidney transplant are characterized by i...

Research on the Application of Intelligent Choreography for Musical Theater Based on Mixture Density Network Algorithm.

Musical choreography is usually completed by professional choreographers, which is very professional and time-consuming. In order to realize the intel...

Extending Camera's Capabilities in Low Light Conditions Based on LIP Enhancement Coupled with CNN Denoising.

Using a sensor in variable lighting conditions, especially very low-light conditions, requires the application of image enhancement followed by denois...

Deep learning model enables the discovery of a novel immunotherapeutic agent regulating the kynurenine pathway.

Kynurenine (Kyn) is a key inducer of an immunosuppressive tumor microenvironment (TME). Although indoleamine 2,3-dioxygenase (IDO)-selective inhibitor...

Evaluating comforting messages with the sentiment analysis and social cognition engine.

The current study extended the literature on social support by examining the differences in the word content of supportive messages using a free onlin...

The concept of social dignity as a yardstick to delimit ethical use of robotic assistance in the care of older persons.

With robots being introduced into caregiving, particularly for older persons, various ethical concerns are raised. Among them is the fear of replacing...

A study of generalization and compatibility performance of 3D U-Net segmentation on multiple heterogeneous liver CT datasets.

BACKGROUND: Most existing algorithms have been focused on the segmentation from several public Liver CT datasets scanned regularly (no pneumoperitoneu...

Personalized Cell Therapy for Patients with Peripheral Arterial Diseases in the Context of Genetic Alterations: Artificial Intelligence-Based Responder and Non-Responder Prediction.

Stem/progenitor cell transplantation is a potential novel therapeutic strategy to induce angiogenesis in ischemic tissue, which can prevent major ampu...

Cuprous oxide coated silver/graphitic carbon nitride/cadmium sulfide nanocomposite heterostructure: Specific recognition of carcinoembryonic antigen through sandwich-type mechanism.

The development of the effective diagnostic method for the determination of cancer biomarkers is one of the most promising strategies for early clinic...

The Role of Machine Learning in Cardiovascular Pathology.

Machine learning has seen slow but steady uptake in diagnostic pathology over the past decade to assess digital whole-slide images. Machine learning t...

Zernike Moment Based Classification of Cosmic Ray Candidate Hits from CMOS Sensors.

Reliable tools for artefact rejection and signal classification are a must for cosmic ray detection experiments based on CMOS technology. In this pape...

Dynamics-Based Peptide-MHC Binding Optimization by a Convolutional Variational Autoencoder: A Use-Case Model for CASTELO.

An unsolved challenge in the development of antigen-specific immunotherapies is determining the optimal antigens to target. Comprehension of antigen-m...

Machine learning of genomic features in organotropic metastases stratifies progression risk of primary tumors.

Metastatic cancer is associated with poor patient prognosis but its spatiotemporal behavior remains unpredictable at early stage. Here we develop Meta...

Injectable conductive gelatin methacrylate / oxidized dextran hydrogel encapsulating umbilical cord mesenchymal stem cells for myocardial infarction treatment.

Umbilical cord mesenchymal stem cells (UCMSCs) transplantation has been proposed as a promising treatment modality for myocardial infarction (MI), but...

Deep learning-based classification of kidney transplant pathology: a retrospective, multicentre, proof-of-concept study.

BACKGROUND: Histopathological assessment of transplant biopsies is currently the standard method to diagnose allograft rejection and can help guide pa...

3D spatial priors for semi-supervised organ segmentation with deep convolutional neural networks.

PURPOSE: Fully Convolutional neural Networks (FCNs) are the most popular models for medical image segmentation. However, they do not explicitly integr...

A deep learning approach to identify and segment alpha-smooth muscle actin stress fiber positive cells.

Cardiac fibrosis is a pathological process characterized by excessive tissue deposition, matrix remodeling, and tissue stiffening, which eventually le...

Integrated Cells and Collagen Fibers Spatial Image Analysis.

Modern technologies designed for tissue structure visualization like brightfield microscopy, fluorescent microscopy, mass cytometry imaging (MCI) and ...