COVID-19

Anam-Net: Anamorphic Depth Embedding-Based Lightweight CNN for Segmentation of Anomalies in COVID-19 Chest CT Images.

Chest computed tomography (CT) imaging has become indispensable for staging and managing coronavirus disease 2019 (COVID-19), and current evaluation of anomalies/abnormalities associated with COVID-19 has been performed majorly by the visual score. The development of automated methods for quantifying COVID-19 abnormalities in these CT images is invaluable to clinicians. The hallmark of COVID-19 in...

Metaheuristic-based Deep COVID-19 Screening Model from Chest X-Ray Images.

COVID-19 has affected the whole world drastically. A huge number of people have lost their lives due to this pandemic. Early detection of COVID-19 infection is helpful for treatment and quarantine. Therefore, many researchers have designed a deep learning model for the early diagnosis of COVID-19-infected patients. However, deep learning models suffer from overfitting and hyperparameter-tuning iss...

Accurately Discriminating COVID-19 from Viral and Bacterial Pneumonia According to CT Images Via Deep Learning.

Computed tomography (CT) is one of the most efficient diagnostic methods for rapid diagnosis of the widespread COVID-19. However, reading CT films bri...

Parallel Binary Image Cryptosystem Via Spiking Neural Networks Variants.

Due to the inefficiency of multiple binary images encryption, a parallel binary image encryption framework based on the typical variants of spiking ne...

Generating functional protein variants with variational autoencoders.

The vast expansion of protein sequence databases provides an opportunity for new protein design approaches which seek to learn the sequence-function r...

Artificial neural network and logistic regression modelling to characterize COVID-19 infected patients in local areas of Iran.

BACKGROUND: COVID-19 is an infectious disease that started spreading globally at the end of 2019. Due to differences in patient characteristics and sy...

Auxiliary Diagnosis for COVID-19 with Deep Transfer Learning.

To assist physicians identify COVID-19 and its manifestations through the automatic COVID-19 recognition and classification in chest CT images with de...

COVID-19 in Iran: Forecasting Pandemic Using Deep Learning.

COVID-19 has led to a pandemic, affecting almost all countries in a few months. In this work, we applied selected deep learning models including multi...

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 coronavirus disease 2019 (COVID-19) using a fully automated...

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 of endogenous viral contamination from cell substr...

Ultrasound-based deep learning radiomics in the assessment of pathological complete response to neoadjuvant chemotherapy in locally advanced breast cancer.

PURPOSE: The aim of the study was to develop and validate a deep learning radiomic nomogram (DLRN) for preoperatively assessing breast cancer patholog...

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 countries, influencing billions of humans. To control the ...

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 community-acquired pneumonia (CAP); it is difficu...

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 synthesis of human proteins. Genetic variants impacting s...

Machine learning-based cytokine microarray digital immunoassay analysis.

Serial measurement of a large panel of protein biomarkers near the bedside could provide a promising pathway to transform the critical care of acutely...

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 caused by the novel coronavirus. In December 2019, th...

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 worldwide concern. This study aims to investigate the cor...

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 triage patients more effectively to general admission v...

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 accuracy, efficiency, and robustness in noncontrast-e...

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 and caused a global pandemic. Rapid and early detec...