Infectious Disease

Spatial Prediction of COVID-19 in China Based on Machine Learning Algorithms and Geographically Weighted Regression.

COVID-19 has swept through the world since December 2019 and caused a large number of patients and deaths. Spatial prediction on the spread of the epidemic is greatly important for disease control and management. In this study, we predicted the cumulative confirmed cases () from Jan 17 to Mar 1, 2020, in mainland China at the city level, using machine learning algorithms, geographically weighted r...

AIoT Used for COVID-19 Pandemic Prevention and Control.

The pandemic of COVID-19 is continuing to wreak havoc in 2021, with at least 170 million victims around the world. Healthcare systems are overwhelmed by the large-scale virus infection. Luckily, Internet of Things (IoT) is one of the most effective paradigms in the intelligent world, in which the technology of artificial intelligence (AI), like cloud computing and big data analysis, is playing a v...

Computational investigation of drug bank compounds against 3C-like protease (3CL) of SARS-CoV-2 using deep learning and molecular dynamics simulation.

Blocking the main replicating enzyme, 3 Chymotrypsin-like protease (3CL) is the most promising drug development strategy against the SARS-CoV-2 virus,...

Content-based Image Retrieval by Using Deep Learning for Interstitial Lung Disease Diagnosis with Chest CT.

Background Evaluation of interstitial lung disease (ILD) at CT is a challenging task that requires experience and is subject to substantial interreade...

COVID-19 Diagnosis from CT Images with Convolutional Neural Network Optimized by Marine Predator Optimization Algorithm.

In recent years, almost every country in the world has struggled against the spread of Coronavirus Disease 2019. If governments and public health syst...

Early Prediction of Sepsis Based on Machine Learning Algorithm.

Sepsis is an organ failure disease caused by an infection resulting in extremely high mortality. Machine learning algorithms XGBoost and LightGBM are ...

A large margin piecewise linear classifier with fusion of deep features in the diagnosis of COVID-19.

The world has experienced epidemics of coronavirus infections several times over the last two decades. Recent studies have shown that using medical im...

Navigating Chemical Space by Interfacing Generative Artificial Intelligence and Molecular Docking.

Here, we report the implementation and application of a simple, structure-aware framework to generate target-specific screening libraries. Our approac...

Machine learning-enabled predictive modeling to precisely identify the antimicrobial peptides.

The ubiquitous antimicrobial peptides (AMPs), with a broad range of antimicrobial activities, represent a great promise for combating the multi-drug r...

Predicting bloodstream infection outcome using machine learning.

Bloodstream infections (BSI) are a main cause of infectious disease morbidity and mortality worldwide. Early prediction of BSI patients at high risk o...

Yeast cell segmentation in microstructured environments with deep learning.

Cell segmentation is a major bottleneck in extracting quantitative single-cell information from microscopy data. The challenge is exasperated in the s...

Development of monoclonal antibodies for quantification of bovine tumor necrosis factor-α.

The expression of the proinflammatory cytokine tumor necrosis factor-α (TNF-α) is associated with production losses in dairy cows and is a hallmark of...

Simultaneous degradation of glucocorticoids and sterilization using bubbling corona discharge plasma based systems: A promising terminal water treatment facility for hospital wastewater.

Glucocorticoids (GCs) have drawn great concern due to their widespread contamination in the environment and application in treating patients with COVI...

Prediction for understanding the effectiveness of antiviral peptides.

The low efficacy of current antivirals in conjunction with the resistance of viruses against existing antiviral drugs has resulted in the demand for t...

StackHCV: a web-based integrative machine-learning framework for large-scale identification of hepatitis C virus NS5B inhibitors.

Fast and accurate identification of inhibitors with potency against HCV NS5B polymerase is currently a challenging task. As conventional experimental ...

Simulation and Prediction of Fungal Community Evolution Based on RBF Neural Network.

Simulation and prediction of the scale change of fungal community. First, using the experimental data of a variety of fungal decomposition activities,...

SenSARS: A Low-Cost Portable Electrochemical System for Ultra-Sensitive, Near Real-Time, Diagnostics of SARS-CoV-2 Infections.

A critical path to solving the SARS-CoV-2 pandemic, without further socioeconomic impact, is to stop its spread. For this to happen, pre- or asymptoma...

A bioinspired neural architecture search based convolutional neural network for breast cancer detection using histopathology images.

The design of neural architecture to address the challenge of detecting abnormalities in histopathology images can leverage the gains made in the fiel...

A novel random forest approach to revealing interactions and controls on chlorophyll concentration and bacterial communities during coastal phytoplankton blooms.

Increasing occurrence of harmful algal blooms across the land-water interface poses significant risks to coastal ecosystem structure and human health....

A Deep Learning-Based Method for Identification of Bacteriophage-Host Interaction.

Multi-drug resistance (MDR) has become one of the greatest threats to human health worldwide, and novel treatment methods of infections caused by MDR ...