COVID-19

Prediction of Patient Management in COVID-19 Using Deep Learning-Based Fully Automated Extraction of Cardiothoracic CT Metrics and Laboratory Findings.

OBJECTIVE: To extract pulmonary and cardiovascular metrics from chest CTs of patients with coronavir...

Application of machine learning methods to pathogen safety evaluation in biological manufacturing processes.

The production of recombinant therapeutic proteins from animal or human cell lines entails the risk ...

Olfactory Testing in Parkinson Disease and REM Behavior Disorder: A Machine Learning Approach.

OBJECTIVE: We sought to identify an abbreviated test of impaired olfaction amenable for use in busy ...

JCS: An Explainable COVID-19 Diagnosis System by Joint Classification and Segmentation.

Recently, the coronavirus disease 2019 (COVID-19) has caused a pandemic disease in over 200 countrie...

COVID-19 outbreak and air quality: Analyzing the influence of physical distancing and the resumption of activities in São Paulo municipality.

CADD-Splice-improving genome-wide variant effect prediction using deep learning-derived splice scores.

BACKGROUND: Splicing of genomic exons into mRNAs is a critical prerequisite for the accurate synthes...

Establishing Classifiers With Clinical Laboratory Indicators to Distinguish COVID-19 From Community-Acquired Pneumonia: Retrospective Cohort Study.

BACKGROUND: The initial symptoms of patients with COVID-19 are very much like those of patients with...

Machine learning-based cytokine microarray digital immunoassay analysis.

Serial measurement of a large panel of protein biomarkers near the bedside could provide a promising...

COVID-19 Detection from Chest X-ray Images Using Feature Fusion and Deep Learning.

Currently, COVID-19 is considered to be the most dangerous and deadly disease for the human body cau...

Correlation between lung infection severity and clinical laboratory indicators in patients with COVID-19: a cross-sectional study based on machine learning.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has caused a global pandemic that has raised worldwi...

Machining learning predicts the need for escalated care and mortality in COVID-19 patients from clinical variables.

This study aimed to develop a machine learning algorithm to identify key clinical measures to triag...

A deep learning integrated radiomics model for identification of coronavirus disease 2019 using computed tomography.

Since its first outbreak, Coronavirus Disease 2019 (COVID-19) has been rapidly spreading worldwide a...

Thyroid gland delineation in noncontrast-enhanced CTs using deep convolutional neural networks.

The purpose of this study is to develop a deep learning method for thyroid delineation with high acc...

Automation of training and testing motor and related tasks in pre-clinical behavioural and rehabilitative neuroscience.

Testing and training animals in motor and related tasks is a cornerstone of pre-clinical behavioural...

DON: Deep Learning and Optimization-Based Framework for Detection of Novel Coronavirus Disease Using X-ray Images.

In the hospital, a limited number of COVID-19 test kits are available due to the spike in cases ever...

Artificial Intelligence-Based Prediction of Covid-19 Severity on the Results of Protein Profiling.

BACKGROUND: COVID-19 progresses slowly and negatively affects many people. However, mild to moderate...

Deep diversification of an AAV capsid protein by machine learning.

Modern experimental technologies can assay large numbers of biological sequences, but engineered pro...

Fast and Accurate Detection of COVID-19 Along With 14 Other Chest Pathologies Using a Multi-Level Classification: Algorithm Development and Validation Study.

BACKGROUND: COVID-19 has spread very rapidly, and it is important to build a system that can detect ...

A Machine Learning Prediction Model of Respiratory Failure Within 48 Hours of Patient Admission for COVID-19: Model Development and Validation.

BACKGROUND: Predicting early respiratory failure due to COVID-19 can help triage patients to higher ...

Intelligent Neutrosophic Diagnostic System for Cardiotocography Data.

Cardiotocography data uncertainty is a critical task for the classification in biomedical field. Con...

Domain-Scan: Combinatorial Sero-Diagnosis of Infectious Diseases Using Machine Learning.

The presence of pathogen-specific antibodies in an individual's blood-sample is used as an indicatio...