Flu & URI

Complementing the power of deep learning with statistical model fusion: Probabilistic forecasting of influenza in Dallas County, Texas, USA.

Influenza is one of the main causes of death, not only in the USA but worldwide. Its significant economic and public health impacts necessitate development of accurate and efficient algorithms for forecasting of any upcoming influenza outbreaks. Most currently available methods for influenza prediction are based on parametric time series and regression models that impose restrictive and often unve...

Sentiment Analysis of Social Media on Childhood Vaccination: Development of an Ontology.

BACKGROUND: Although vaccination rates are above the threshold for herd immunity in South Korea, a growing number of parents have expressed concerns about the safety of vaccines. It is important to understand these concerns so that we can maintain high vaccination rates.

MHCSeqNet: a deep neural network model for universal MHC binding prediction.

BACKGROUND: Immunotherapy is an emerging approach in cancer treatment that activates the host immune system to destroy cancer cells expressing unique ...

Weekly ILI patient ratio change prediction using news articles with support vector machine.

BACKGROUND: Influenza continues to pose a serious threat to human health worldwide. For this reason, detecting influenza infection patterns is critica...

Streptococcus Gallolyticus endocarditis in patient with liver cirrhosis: a case report.

Streptococcus gallolyticus (S. gallolyticus) bacteremia is commonly associated with endocarditis and diseases of gastrointestinal tract, especially wi...

Regional level influenza study based on Twitter and machine learning method.

The significance of flu prediction is that the appropriate preventive and control measures can be taken by relevant departments after assessing predic...

The use of natural language processing to identify Tdap-related local reactions at five health care systems in the Vaccine Safety Datalink.

OBJECTIVE: Local reactions are the most common vaccine-related adverse event. There is no specific diagnosis code for local reaction due to vaccinatio...

Application of Deep-Learning Methods to Bird Detection Using Unmanned Aerial Vehicle Imagery.

Wild birds are monitored with the important objectives of identifying their habitats and estimating the size of their populations. Especially in the c...

Understanding the importance of key risk factors in predicting chronic bronchitic symptoms using a machine learning approach.

BACKGROUND: Chronic respiratory symptoms involving bronchitis, cough and phlegm in children are underappreciated but pose a significant public health ...

Chief complaint classification with recurrent neural networks.

Syndromic surveillance detects and monitors individual and population health indicators through sources such as emergency department records. Automate...

A novel machine-learning-based infection screening system via 2013-2017 seasonal influenza patients' vital signs as training datasets.

Tweet Classification Toward Twitter-Based Disease Surveillance: New Data, Methods, and Evaluations.

BACKGROUND: The amount of medical and clinical-related information on the Web is increasing. Among the different types of information available, socia...

The analysis of the effects of acute rheumatic fever in childhood on cardiac disease with data mining.

BACKGROUND: Acute rheumatic fever (ARF) is an important disease that is frequently seen in Turkey, it is necessary to develop solutions to cure the di...

PADI-web corpus: Labeled textual data in animal health domain.

Monitoring animal health worldwide, especially the early detection of outbreaks of emerging pathogens, is one of the means of preventing the introduct...

A Machine Hearing System for Robust Cough Detection Based on a High-Level Representation of Band-Specific Audio Features.

UNLABELLED: Cough is a protective reflex conveying information on the state of the respiratory system. Cough assessment has been limited so far to sub...

Structured illumination microscopy combined with machine learning enables the high throughput analysis and classification of virus structure.

Optical super-resolution microscopy techniques enable high molecular specificity with high spatial resolution and constitute a set of powerful tools i...

Deep-learning classification using convolutional neural network for evaluation of maxillary sinusitis on panoramic radiography.

OBJECTIVES: To apply a deep-learning system for diagnosis of maxillary sinusitis on panoramic radiography, and to clarify its diagnostic performance.

Demographic, Clinical, and Allergic Characteristics of Children with Eosinophilic Esophagitis in Isfahan, Iran.

Eosinophilic esophagitis (EoE) is a chronic immune-mediated disease isolated to the esophagus Food allergy is thought to play an important role in the...

CbpM and CbpG of Streptococcus Pneumoniae Elicit a High Protection in Mice Challenged with a Serotype 19F Pneumococcus.

Among many pneumococcal antigens, choline-binding proteins (CPBs) display a high immunogenicity in animal models. This study aims to determine the imm...

Immunogenicity of Concentrated and Purified Inactivated Avian Influenza Vaccine Formulation.

Avian influenza (AI) H9N2 is a low pathogenic virus subtype belonging to Orthomyxoviridae family. Given the prevalence of this subtype as an infectiou...