Infectious Disease

Application of Whole-Genome Sequences and Machine Learning in Source Attribution of Salmonella Typhimurium.

Prevention of the emergence and spread of foodborne diseases is an important prerequisite for the improvement of public health. Source attribution models link sporadic human cases of a specific illness to food sources and animal reservoirs. With the next generation sequencing technology, it is possible to develop novel source attribution models. We investigated the potential of machine learning to...

Predicting geographic location from genetic variation with deep neural networks.

Most organisms are more closely related to nearby than distant members of their species, creating spatial autocorrelations in genetic data. This allows us to predict the location of origin of a genetic sample by comparing it to a set of samples of known geographic origin. Here, we describe a deep learning method, which we call Locator, to accomplish this task faster and more accurately than existi...

COVID-19 Epidemic: Possibility of Artificial Intelligence in Infection Control and Prevention.

Efficient GAN-based Chest Radiographs (CXR) augmentation to diagnose coronavirus disease pneumonia.

: As 2019 ends coronavirus disease start expanding all over the world. It is highly transmissible disease that can affect respiratory tract and can le...

CoroNet: A deep neural network for detection and diagnosis of COVID-19 from chest x-ray images.

BACKGROUND AND OBJECTIVE: The novel Coronavirus also called COVID-19 originated in Wuhan, China in December 2019 and has now spread across the world. ...

Risk of a second wave of Covid-19 infections: using artificial intelligence to investigate stringency of physical distancing policies in North America.

PURPOSE: Accurately forecasting the occurrence of future covid-19-related cases across relaxed (Sweden) and stringent (USA and Canada) policy contexts...

COVID-19: The role of artificial intelligence in empowering the healthcare sector and enhancing social distancing measures during a pandemic.

Indiscriminatory in its spread, COVID-19 has engulfed communities from all social backgrounds throughout the world. While healthcare professionals wor...

Deep Learning Based Drug Screening for Novel Coronavirus 2019-nCov.

A novel coronavirus, called 2019-nCoV, was recently found in Wuhan, Hubei Province of China, and now is spreading across China and other parts of the ...

An Intelligent Fuzzy Rule-Based Personalized News Recommendation Using Social Media Mining.

Recommendation of a relevant and suitable news article is an essential but a challenging task due to changes in the user interest categories over time...

Modeling the Spread of COVID-19 Infection Using a Multilayer Perceptron.

Coronavirus (COVID-19) is a highly infectious disease that has captured the attention of the worldwide public. Modeling of such diseases can be extrem...

Robotics Utilization for Healthcare Digitization in Global COVID-19 Management.

This paper describes the evolving role of robotics in healthcare and allied areas with special concerns relating to the management and control of the ...

Deep learning COVID-19 detection bias: accuracy through artificial intelligence.

BACKGROUND: Detection of COVID-19 cases' accuracy is posing a conundrum for scientists, physicians, and policy-makers. As of April 23, 2020, 2.7 milli...

Its2vec: Fungal Species Identification Using Sequence Embedding and Random Forest Classification.

Fungi play essential roles in many ecological processes, and taxonomic classification is fundamental for microbial community characterization and vita...

Forecasting tuberculosis using diabetes-related google trends data.

Online activity-based data can be used to aid infectious disease forecasting. Our aim was to exploit the converging nature of the tuberculosis (TB) an...

Detection of Intestinal Protozoa in Trichrome-Stained Stool Specimens by Use of a Deep Convolutional Neural Network.

Intestinal protozoa are responsible for relatively few infections in the developed world, but the testing volume is disproportionately high. Manual li...

Predicting host taxonomic information from viral genomes: A comparison of feature representations.

The rise in metagenomics has led to an exponential growth in virus discovery. However, the majority of these new virus sequences have no assigned host...

Role of biological Data Mining and Machine Learning Techniques in Detecting and Diagnosing the Novel Coronavirus (COVID-19): A Systematic Review.

Coronaviruses (CoVs) are a large family of viruses that are common in many animal species, including camels, cattle, cats and bats. Animal CoVs, such ...

Prioritizing and Analyzing the Role of Climate and Urban Parameters in the Confirmed Cases of COVID-19 Based on Artificial Intelligence Applications.

Nowadays, an infectious disease outbreak is considered one of the most destructive effects in the sustainable development process. The outbreak of new...

Experimental Data Based Machine Learning Classification Models with Predictive Ability to Select in Vitro Active Antiviral and Non-Toxic Essential Oils.

In the last decade essential oils have attracted scientists with a constant increase rate of more than 7% as witnessed by almost 5000 articles. Among ...

CHEER: HierarCHical taxonomic classification for viral mEtagEnomic data via deep leaRning.

The fast accumulation of viral metagenomic data has contributed significantly to new RNA virus discovery. However, the short read size, complex compos...