COVID-19

Computer-aided diagnosis of chest X-ray for COVID-19 diagnosis in external validation study by radiologists with and without deep learning system.

To evaluate the diagnostic performance of our deep learning (DL) model of COVID-19 and investigate w...

Application of deep learning technology for temporal analysis of videofluoroscopic swallowing studies.

Temporal parameters during swallowing are analyzed for objective and quantitative evaluation of vide...

Aggregate Formation and Antibody Stability in Infusion Bags: The Impact of Manual and Robotic Compounding of Monoclonal Antibodies.

Monoclonal antibodies (mAbs) can be damaged during the aseptic compounding process, with aggregation...

Polygenic modelling and machine learning approaches in pharmacogenomics: Importance in downstream analysis of genome-wide association study data.

Genome-wide association studies (GWAS) have identified genetic variations associated with adverse dr...

Bacterial metabolism-triggered-chemiluminescence-based point-of-care testing platform for sensitive detection and photothermal inactivation of Staphylococcus aureus.

Post-operative pathogenic infections in liver transplantation seriously threaten human health. It is...

PointDE: Protein Docking Evaluation Using 3D Point Cloud Neural Network.

Protein-protein interactions (PPIs) play essential roles in many vital movements and the determinati...

RefinePocket: An Attention-Enhanced and Mask-Guided Deep Learning Approach for Protein Binding Site Prediction.

Protein binding site prediction is an important prerequisite task of drug discovery and design. Whil...

Automatic Quantification of COVID-19 Pulmonary Edema by Self-supervised Contrastive Learning.

We proposed a self-supervised machine learning method to automatically rate the severity of pulmonar...

Early monitoring-to-warning Internet of Things system for emerging infectious diseases via networking of light-triggered point-of-care testing devices.

Early monitoring and warning arrangements are effective ways to distinguish infectious agents and co...

Crack control optimization of basement concrete structures using the Mask-RCNN and temperature effect analysis.

In order to enhance the mitigation of crack occurrence and propagation within basement concrete stru...

Putative Pathogenic Variants of and of Sitosterolemia in Patients With Hyper-Low-Density Lipoprotein Cholesterolemia.

OBJECTIVE: Sitosterolemia is a rare autosomal recessive disease caused by the deleterious variants o...

The Effect of Using a Rehabilitation Robot for Patients with Post-Coronavirus Disease (COVID-19) Fatigue Syndrome.

The aim of this study was to compare the effectiveness of traditional neurological rehabilitation an...

Behind the mask: a critical perspective on the ethical, moral, and legal implications of AI in ophthalmology.

PURPOSE: This narrative review aims to provide an overview of the dangers, controversial aspects, an...

Beam mask and sliding window-facilitated deep learning-based accurate and efficient dose prediction for pencil beam scanning proton therapy.

BACKGROUND: Accurate and efficient dose calculation is essential for on-line adaptive planning in pr...

Learning smooth dendrite morphological neurons by stochastic gradient descent for pattern classification.

This article presents a learning algorithm for dendrite morphological neurons (DMN) based on stochas...

Artificial intelligence based system for predicting permanent stoma after sphincter saving operations.

Although the goal of rectal cancer treatment is to restore gastrointestinal continuity, some patient...

Hyper-parameter tuned deep learning approach for effective human monkeypox disease detection.

Human monkeypox is a very unusual virus that can devastate society. Early identification and diagnos...

Ready for testing artificial intelligence in radiology clinical practice: We would do well to be in the front line leveraging their strengths but also highlighting today weaknesses.

Predicting pathogenic protein variants.

Machine-learning algorithm uses structure prediction to spot disease-causing mutations.

Training of epitope-TCR prediction models with healthy donor-derived cancer-specific T cells.

Discovery of epitope-specific T-cell receptors (TCRs) for cancer therapies is a time consuming and e...

Gray-to-color image conversion in the classification of breast lesions on ultrasound using pre-trained deep neural networks.

Breast ultrasound (BUS) image classification in benign and malignant classes is often based on pre-t...