Transplantation

Latest AI and machine learning research in transplantation for healthcare professionals.

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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 ...

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 opti...

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 ...

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 ...

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 se...

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 remo...

Integrated Cells and Collagen Fibers Spatial Image Analysis.

Modern technologies designed for tissue structure visualization like brightfield microscopy, fluores...

EEG-based detection of emotional valence towards a reproducible measurement of emotions.

A methodological contribution to a reproducible Measurement of Emotions for an EEG-based system is p...

Artificial Intelligence in Liver Transplantation.

BACKGROUND: Advancements based on artificial intelligence have emerged in all areas of medicine. Man...

Deep learning identified pathological abnormalities predictive of graft loss in kidney transplant biopsies.

Interstitial fibrosis, tubular atrophy, and inflammation are major contributors to kidney allograft ...

Robotic endovascular surgery: current and future practice.

Minimally invasive techniques have been at the forefront of surgical progress, and the evolution of ...

Deep protein representations enable recombinant protein expression prediction.

A crucial process in the production of industrial enzymes is recombinant gene expression, which aims...

Development of calciphylaxis in kidney transplant recipients with a functioning graft.

BACKGROUND: Calciphylaxis is not uniquely observed in uraemic patients, as some cases have also been...

Deep Learning CT-based Quantitative Visualization Tool for Liver Volume Estimation: Defining Normal and Hepatomegaly.

Background Imaging assessment for hepatomegaly is not well defined and currently uses suboptimal, un...

Machine Learning Assisted Approach for Finding Novel High Activity Agonists of Human Ectopic Olfactory Receptors.

Olfactory receptors (ORs) constitute the largest superfamily of G protein-coupled receptors (GPCRs)....

AI Integration in the Clinical Workflow.

Machine learning and artificial intelligence (AI) algorithms hold significant promise for addressing...

Connecting MHC-I-binding motifs with HLA alleles via deep learning.

The selection of peptides presented by MHC molecules is crucial for antigen discovery. Previously, s...

Prospective comparative study of postoperative systemic inflammatory syndrome in robot-assisted vs. open kidney transplantation.

PURPOSE: Robot-assisted kidney transplant (RAKT) recently proved to provide functional results simil...

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