Transplantation

Utilization of machine-learning models to accurately predict the risk for critical COVID-19.

Among patients with Coronavirus disease (COVID-19), the ability to identify patients at risk for deterioration during their hospital stay is essential for effective patient allocation and management. To predict patient risk for critical COVID-19 based on status at admission using machine-learning models. Retrospective study based on a database of tertiary medical center with designated departments...

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography.

Brain metastases are the most lethal cancer lesions; 10-30% of all cancers metastasize to the brain, with a median survival of only ~5-20 months, depending on the cancer type. To reduce the brain metastatic tumor burden, gaps in basic and translational knowledge need to be addressed. Major challenges include a paucity of reproducible preclinical models and associated tools. Three-dimensional model...

Deep learning and level set approach for liver and tumor segmentation from CT scans.

PURPOSE: Segmentation of liver organ and tumors from computed tomography (CT) scans is an important task for hepatic surgical planning. Manual segment...

DE-CNN: An Improved Identity Recognition Algorithm Based on the Emotional Electroencephalography.

In the past few decades, identification recognition based on electroencephalography (EEG) has received extensive attention to resolve the security pro...

Anatomical classification of upper gastrointestinal organs under various image capture conditions using AlexNet.

BACKGROUND: Machine learning has led to several endoscopic studies about the automated localization of digestive lesions and prediction of cancer inva...

Machine learning for predicting long-term kidney allograft survival: a scoping review.

Supervised machine learning (ML) is a class of algorithms that "learn" from existing input-output pairs, which is gaining popularity in pattern recogn...

Assessment of the Effect of Infliximab on Immunomodulation Properties of Mesenchymal Stem Cells .

Mesenchymal stem cells (MSCs) have immunomodulatory traits making them a promising choice in the treatment of inflammatory diseases such as graft-ver...

Robot-assisted double screw fixation of minimally displaced scaphoid waist fracture nonunions or delayed unions without bone graft.

We retrospectively reviewed 12 minimally displaced fractures of the scaphoid waist in 12 patients who developed delayed or nonunions with or without c...

Unbiased Characterization of Peptide-HLA Class II Interactions Based on Large-Scale Peptide Microarrays; Assessment of the Impact on HLA Class II Ligand and Epitope Prediction.

Human Leukocyte Antigen class II (HLA-II) molecules present peptides to T lymphocytes and play an important role in adaptive immune responses. Charact...

Integrated artificial neural network analysis and functional cell based affinity mass spectrometry for screening a bifunctional activator of Ca and βAR in aconite.

Arrhythmia, a common heart disease, is an abnormal frequency or rhythm of heartbeat caused by the origin or conduction obstacle of the heart. Aconite ...

Prospective Nonrandomized Comparison Between Open and Robot-Assisted Kidney Transplantation: Analysis of Midterm Functional Outcomes.

To compare short- and midterm outcomes of the first 55 patients undergoing robot-assisted kidney transplant (RAKT) with patients undergoing open kidn...

Patterns of 1,748 Unique Human Alloimmune Responses Seen by Simple Machine Learning Algorithms.

Allele specific antibody response against the polymorphic system of HLA is the allogeneic response marker determining the immunological risk for graft...

EDeepSSP: Explainable deep neural networks for exact splice sites prediction.

Splice site prediction is crucial for understanding underlying gene regulation, gene function for better genome annotation. Many computational methods...

Identifying scenarios of benefit or harm from kidney transplantation during the COVID-19 pandemic: A stochastic simulation and machine learning study.

Clinical decision-making in kidney transplant (KT) during the coronavirus disease 2019 (COVID-19) pandemic is understandably a conundrum: both candida...

Deep-learning-based accurate hepatic steatosis quantification for histological assessment of liver biopsies.

Hepatic steatosis droplet quantification with histology biopsies has high clinical significance for risk stratification and management of patients wit...

Predicting the chemical reactivity of organic materials using a machine-learning approach.

Stability and compatibility between chemical components are essential parameters that need to be considered in the selection of functional materials i...

Evaluation of marker selection methods and statistical models for chronological age prediction based on DNA methylation.

In forensic investigation, retrieving biological information from DNA evidence is a promising field of interest. One of the applications is on the est...

Improved Active Disturbance Rejection Control for Trajectory Tracking Control of Lower Limb Robotic Rehabilitation Exoskeleton.

Neurological disorders such as cerebral paralysis, spinal cord injuries, and strokes, result in the impairment of motor control and induce functional ...

Deep learning approach to describe and classify fungi microscopic images.

Preliminary diagnosis of fungal infections can rely on microscopic examination. However, in many cases, it does not allow unambiguous identification o...

Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation.

Although having achieved great success in medical image segmentation, deep learning-based approaches usually require large amounts of well-annotated d...