Infectious Disease

A stochastic numerical analysis based on hybrid NAR-RBFs networks nonlinear SITR model for novel COVID-19 dynamics.

BACKGROUND: Mathematical modeling of vector-borne diseases and forecasting of epidemics outbreak are global challenges and big point of concern worldwide. The outbreaks depend on different social and demographic factors based on human mobility structured with the help of mathematical models for vector-borne disease transmission. In Dec 2019, an infectious disease is known as "coronavirus" (officia...

Federated semi-supervised learning for COVID region segmentation in chest CT using multi-national data from China, Italy, Japan.

The recent outbreak of Coronavirus Disease 2019 (COVID-19) has led to urgent needs for reliable diagnosis and management of SARS-CoV-2 infection. The current guideline is using RT-PCR for testing. As a complimentary tool with diagnostic imaging, chest Computed Tomography (CT) has been shown to be able to reveal visual patterns characteristic for COVID-19, which has definite value at several stages...

Computational approach for identification, characterization, three-dimensional structure modelling and machine learning-based thermostability prediction of xylanases from the genome of Aspergillus fumigatus.

Identification of thermostable and alkaline xylanases from different fungal and bacterial species have gained an interest for the researchers because ...

Toward data-efficient learning: A benchmark for COVID-19 CT lung and infection segmentation.

PURPOSE: Accurate segmentation of lung and infection in COVID-19 computed tomography (CT) scans plays an important role in the quantitative management...

A multi-center study of COVID-19 patient prognosis using deep learning-based CT image analysis and electronic health records.

PURPOSE: As of August 30th, there were in total 25.1 million confirmed cases and 845 thousand deaths caused by coronavirus disease of 2019 (COVID-19) ...

Development and validation of a prognostic COVID-19 severity assessment (COSA) score and machine learning models for patient triage at a tertiary hospital.

BACKGROUND: Clinical risk scores and machine learning models based on routine laboratory values could assist in automated early identification of seve...

An in silico deep learning approach to multi-epitope vaccine design: a SARS-CoV-2 case study.

The rampant spread of COVID-19, an infectious disease caused by SARS-CoV-2, all over the world has led to over millions of deaths, and devastated the ...

Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients.

Patients with severe COVID-19 have overwhelmed healthcare systems worldwide. We hypothesized that machine learning (ML) models could be used to predic...

PACIFIC: a lightweight deep-learning classifier of SARS-CoV-2 and co-infecting RNA viruses.

Viral co-infections occur in COVID-19 patients, potentially impacting disease progression and severity. However, there is currently no dedicated metho...

COVID-19 CT Image Synthesis With a Conditional Generative Adversarial Network.

Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic that has spread rapidly since December 2019. Real-time reverse transcription polymer...

Machine Learning-Based Early Warning Systems for Clinical Deterioration: Systematic Scoping Review.

BACKGROUND: Timely identification of patients at a high risk of clinical deterioration is key to prioritizing care, allocating resources effectively, ...

Predicting Potential SARS-COV-2 Drugs-In Depth Drug Database Screening Using Deep Neural Network Framework SSnet, Classical Virtual Screening and Docking.

Severe Acute Respiratory Syndrome Corona Virus 2 has altered life on a global scale. A concerted effort from research labs around the world resulted i...

Six artificial intelligence paradigms for tissue characterisation and classification of non-COVID-19 pneumonia against COVID-19 pneumonia in computed tomography lungs.

BACKGROUND: COVID-19 pandemic has currently no vaccines. Thus, the only feasible solution for prevention relies on the detection of COVID-19-positive ...

Risk factors analysis of COVID-19 patients with ARDS and prediction based on machine learning.

COVID-19 is a newly emerging infectious disease, which is generally susceptible to human beings and has caused huge losses to people's health. Acute r...

Relationships among Healthcare Digitalization, Social Capital, and Supply Chain Performance in the Healthcare Manufacturing Industry.

Due to the impact of coronavirus disease 2019 (COVID-19), automation and artificial intelligence (AI) have attracted renewed interest in multiple indu...

Hybrid ensemble model for differential diagnosis between COVID-19 and common viral pneumonia by chest X-ray radiograph.

BACKGROUND: Chest X-ray radiography (CXR) has been widely considered as an accessible, feasible, and convenient method to evaluate suspected patients'...

Machine learning applied on chest x-ray can aid in the diagnosis of COVID-19: a first experience from Lombardy, Italy.

BACKGROUND: We aimed to train and test a deep learning classifier to support the diagnosis of coronavirus disease 2019 (COVID-19) using chest x-ray (C...

Machine learning techniques to detect and forecast the daily total COVID-19 infected and deaths cases under different lockdown types.

COVID-19 has impacted the world in many ways, including loss of lives, economic downturn and social isolation. COVID-19 was emerged due to the SARS-Co...

Diagnosis of COVID-19 using CT scan images and deep learning techniques.

Early diagnosis of the coronavirus disease in 2019 (COVID-19) is essential for controlling this pandemic. COVID-19 has been spreading rapidly all over...

Computational identification of ubiquitination sites in Arabidopsis thaliana using convolutional neural networks.

We developed two CNNs for predicting ubiquitination sites in Arabidopsis thaliana, demonstrated their competitive performance, analyzed amino acid phy...