COVID-19

A deep learning-based application for COVID-19 diagnosis on CT: The Imaging COVID-19 AI initiative.

BACKGROUND: Recently, artificial intelligence (AI)-based applications for chest imaging have emerged as potential tools to assist clinicians in the diagnosis and management of patients with coronavirus disease 2019 (COVID-19).

Prediction of atmospheric pollutants in urban environment based on coupled deep learning model and sensitivity analysis.

Accurate and efficient predictions of pollutants in the atmosphere provide a reliable basis for the scientific management of atmospheric pollution. This study develops a model that combines an attention mechanism, convolutional neural network (CNN), and long short-term memory (LSTM) unit to predict the O and PM levels in the atmosphere, as well as an air quality index (AQI). The prediction results...

HER2-low breast cancer: insights on pathological testing.

Human epidermal growth factor receptor 2 (HER2) is an important biomarker for predicting prognosis and effectiveness of HER2-targeted therapy in breas...

Accelerating therapeutic protein design with computational approaches toward the clinical stage.

Therapeutic protein, represented by antibodies, is of increasing interest in human medicine. However, clinical translation of therapeutic protein is s...

Application of an AI image analysis and classification approach to characterise dissolution and precipitation events in the flow through apparatus.

Imaging and artificial intelligence (AI) approaches have been used with increasing frequency in pharmaceutical industry in recent years. Characterisat...

Targeting Protein-Protein Interfaces with Peptides: The Contribution of Chemical Combinatorial Peptide Library Approaches.

Protein-protein interfaces play fundamental roles in the molecular mechanisms underlying pathophysiological pathways and are important targets for the...

Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies.

Antibodies have the capacity to bind a diverse set of antigens, and they have become critical therapeutics and diagnostic molecules. The binding of an...

Sample-to-answer platform for the clinical evaluation of COVID-19 using a deep learning-assisted smartphone-based assay.

Since many lateral flow assays (LFA) are tested daily, the improvement in accuracy can greatly impact individual patient care and public health. Howev...

DeepBCE: Evaluation of deep learning models for identification of immunogenic B-cell epitopes.

B-Cell epitopes (BCEs) can identify and bind with receptor proteins (antigens) to initiate an immune response against pathogens. Understanding antigen...

Data-driven prediction models for forecasting multistep ahead profiles of mammalian cell culture toward bioprocess digital twins.

Recently, the advancement in process analytical technology and artificial intelligence (AI) has enabled the generation of enormous culture data sets f...

Rethinking Saliency Map: A Context-Aware Perturbation Method to Explain EEG-Based Deep Learning Model.

Deep learning is widely used to decode the electroencephalogram (EEG) signal. However, there are few attempts to specifically study how to explain EEG...

Validation of genetic variants from NGS data using deep convolutional neural networks.

Accurate somatic variant calling from next-generation sequencing data is one most important tasks in personalised cancer therapy. The sophistication o...

[Laboratory testing for anemia in primary care: reflex testing, reflecting and algorithms?].

This commentary discusses the prevalence and causes of anemia in primary care in the Netherlands and the role of laboratory diagnostics in determining...

An investigation into epidemiological situations of COVID-19 with fuzzy K-means and K-prototype clustering methods.

The ten countries with the highest population during the pandemic were analyzed for clustering based on the quantitative numbers of COVID-19 and polic...

A multicenter evaluation of a deep learning software (LungQuant) for lung parenchyma characterization in COVID-19 pneumonia.

BACKGROUND: The role of computed tomography (CT) in the diagnosis and characterization of coronavirus disease 2019 (COVID-19) pneumonia has been widel...

The second-order problem of other minds.

The target article proposes that people perceive social robots as depictions rather than as genuine social agents. We suggest that people might instea...

Hybrid optimized feature selection and deep learning based COVID-19 disease prediction.

The COVID-19 virus has affected many people around the globe with several issues. Moreover, it causes a worldwide pandemic, and it makes more than one...

Myopia prediction for children and adolescents via time-aware deep learning.

This is a retrospective analysis. Quantitative prediction of the children's and adolescents' spherical equivalent based on their variable-length histo...

How Deepbics Quantifies Intensities of Transcription Factor-DNA Binding and Facilitates Prediction of Single Nucleotide Variant Pathogenicity With a Deep Learning Model Trained On ChIP-Seq Data Sets.

The binding of DNA sequences to cell type-specific transcription factors is essential for regulating gene expression in all organisms. Many variants o...

Synthetic biology, genetic circuits and machine learning: a new age of cancer therapy.

Synthetic biology has made it possible to rewire natural cellular responses to treat disease, notably demonstrated by chimeric antigen receptor (CAR) ...