Infectious Disease

Segmentation of COVID-19 pneumonia lesions: A deep learning approach.

Lung CT scan has a pivotal role in diagnosis and monitoring of COVID-19 patients, and with growing number of affected individuals, the need for artificial intelligence (AI)-based systems for interpretation of CT images is emerging. In current investigation we introduce a new deep learning-based automatic segmentation model for localization of COVID-19 pulmonary lesions. A total of 2469 CT scan s...

Clinical Assessment and Validation of a Rapid and Sensitive SARS-CoV-2 Test Using Reverse Transcription Loop-Mediated Isothermal Amplification Without the Need for RNA Extraction.

BACKGROUND: Amid the enduring pandemic, there is an urgent need for expanded access to rapid, sensitive, and inexpensive coronavirus disease 2019 (COVID-19) testing worldwide without specialized equipment. We developed a simple test that uses colorimetric reverse transcription loop-mediated isothermal amplification (RT-LAMP) to detect severe acute resrpiratory syndrome coronavirus 2 (SARS-CoV-2) i...

How artificial intelligence may help the Covid-19 pandemic: Pitfalls and lessons for the future.

The clinical severity, rapid transmission and human losses due to coronavirus disease 2019 (Covid-19) have led the World Health Organization to declar...

Active contour regularized semi-supervised learning for COVID-19 CT infection segmentation with limited annotations.

Infection segmentation on chest CT plays an important role in the quantitative analysis of COVID-19. Developing automatic segmentation tools in a shor...

Denoising Autoencoder, A Deep Learning Algorithm, Aids the Identification of A Novel Molecular Signature of Lung Adenocarcinoma.

Precise biomarker development is a key step in disease management. However, most of the published biomarkers were derived from a relatively small numb...

Analysis of Stroke Detection during the COVID-19 Pandemic Using Natural Language Processing of Radiology Reports.

BACKGROUND AND PURPOSE: The coronavirus disease 2019 (COVID-19) pandemic has led to decreases in neuroimaging volume. Our aim was to quantify the chan...

Necrotic enteritis challenge regulates peroxisome proliferator-1 activated receptors signaling and β-oxidation pathways in broiler chickens.

Necrotic enteritis (NE) is an important enteric disease in poultry and has become a major concern in poultry production in the post-antibiotic era. Th...

Subjective Well-Being of Chinese Sina Weibo Users in Residential Lockdown During the COVID-19 Pandemic: Machine Learning Analysis.

BACKGROUND: During the COVID-19 pandemic, residential lockdowns were implemented in numerous cities in China to contain the rapid spread of the diseas...

Automated Classification of Online Sources for Infectious Disease Occurrences Using Machine-Learning-Based Natural Language Processing Approaches.

Collecting valid information from electronic sources to detect the potential outbreak of infectious disease is time-consuming and labor-intensive. The...

Delimiting cryptic morphological variation among human malaria vector species using convolutional neural networks.

Deep learning is a powerful approach for distinguishing classes of images, and there is a growing interest in applying these methods to delimit specie...

Real-time neural network based predictor for cov19 virus spread.

Since the epidemic outbreak in early months of 2020 the spread of COVID-19 has grown rapidly in most countries and regions across the World. Because o...

Vulnerability of deep neural networks for detecting COVID-19 cases from chest X-ray images to universal adversarial attacks.

Owing the epidemic of the novel coronavirus disease 2019 (COVID-19), chest X-ray computed tomography imaging is being used for effectively screening C...

Evidence of Gender Differences in the Diagnosis and Management of Coronavirus Disease 2019 Patients: An Analysis of Electronic Health Records Using Natural Language Processing and Machine Learning.

The impact of sex and gender in the incidence and severity of coronavirus disease 2019 (COVID-19) remains controversial. Here, we aim to describe the...

Computing SARS-CoV-2 Infection Risk From Symptoms, Imaging, and Test Data: Diagnostic Model Development.

BACKGROUND: Assigning meaningful probabilities of SARS-CoV-2 infection risk presents a diagnostic challenge across the continuum of care.

Prediction of disease progression in patients with COVID-19 by artificial intelligence assisted lesion quantification.

To investigate the value of artificial intelligence (AI) assisted quantification on initial chest CT for prediction of disease progression and clinica...

Exploring optimal control of epidemic spread using reinforcement learning.

Pandemic defines the global outbreak of a disease having a high transmission rate. The impact of a pandemic situation can be lessened by restricting t...

Label-Free Detection of Based on Bacteria-Imprinted Polymer and Turn-on Fluorescence Probes.

The effective identification and quantitative determination of is a major public health concern. Here, an innovative strategy that combines a bacteri...

Artificial Intelligence in the Fight Against COVID-19: Scoping Review.

BACKGROUND: In December 2019, COVID-19 broke out in Wuhan, China, leading to national and international disruptions in health care, business, educatio...

Optimised genetic algorithm-extreme learning machine approach for automatic COVID-19 detection.

The coronavirus disease (COVID-19), is an ongoing global pandemic caused by severe acute respiratory syndrome. Chest Computed Tomography (CT) is an ef...

Study on the optimal antagonistic effect of a bacterial complex against in peach.

Peach brown rot caused by is one of the most economically destructive diseases of peach ( L.) in some orchards of China. Biocontrol is a significant ...