Flu & URI

A syntactic evidence network model for fact verification.

In natural language processing, fact verification is a very challenging task, which requires retrieving multiple evidence sentences from a reliable corpus to verify the authenticity of a claim. Although most of the current deep learning methods use the attention mechanism for fact verification, they have not considered imposing attentional constraints on important related words in the claim and ev...

Mapping African Swine Fever and Highly Pathogenic Avian Influenza Outbreaks along the Demilitarized Zone in the Korean Peninsula.

The Korean Demilitarized Zone (DMZ) is one of the world's most preserved habitats for wild animals and migratory birds. The area also plays a major role in the spread of infectious animal diseases, in particular, African swine fever (ASF) and highly pathogenic avian influenza (HPAI). These outbreaks threaten the livelihood of local livestock farms, not infrequently. In this paper, we explore these...

Respiratory Syncytial Virus Vaccine Design Using Structure-Based Machine-Learning Models.

When designing live-attenuated respiratory syncytial virus (RSV) vaccine candidates, attenuating mutations can be developed through biologic selection...

Prediction of incomplete immunization among under-five children in East Africa from recent demographic and health surveys: a machine learning approach.

The World Health Organization as part of the goal of universal vaccination coverage by 2030 for all individuals. The global under-five mortality rate ...

A complex fuzzy decision model for analysing the post-pandemic immuno-sustainability.

The post-effects of the COronaVIrus Disease (COVID-19) vary depending on socioeconomic and biological factors. Similarly, the effects of vaccination o...

Feature fusion method for pulmonary tuberculosis patient detection based on cough sound.

Since the COVID-19, cough sounds have been widely used for screening purposes. Intelligent analysis techniques have proven to be effective in detectin...

Predicting drug-Protein interaction with deep learning framework for molecular graphs and sequences: Potential candidates against SAR-CoV-2.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the COVID-19 disease, which represents a new life-threatening disaster. Regard...

Machine learning-driven optimization of mRNA-lipid nanoparticle vaccine quality with XGBoost/Bayesian method and ensemble model approaches.

To enhance the efficiency of vaccine manufacturing, this study focuses on optimizing the microfluidic conditions and lipid mix ratios of messenger RNA...

Seasonal antigenic prediction of influenza A H3N2 using machine learning.

Antigenic characterization of circulating influenza A virus (IAV) isolates is routinely assessed by using the hemagglutination inhibition (HI) assays ...

Predicting humoral responses to primary and booster SARS-CoV-2 mRNA vaccination in people living with HIV: a machine learning approach.

BACKGROUND: SARS-CoV-2 mRNA vaccines are highly immunogenic in people living with HIV (PLWH) on effective antiretroviral therapy (ART). However, wheth...

Optical biosensing of monkeypox virus using novel recombinant silica-binding proteins for site-directed antibody immobilization.

The efficient immobilization of capture antibodies is crucial for timely pathogen detection during global pandemic outbreaks. Therefore, we proposed a...

Prediction of hospital-acquired influenza using machine learning algorithms: a comparative study.

BACKGROUND: Hospital-acquired influenza (HAI) is under-recognized despite its high morbidity and poor health outcomes. The early detection of HAI is c...

Combining serum microRNAs and machine learning algorithms for diagnosing infectious fever after HSCT.

Infection post-hematopoietic stem cell transplantation (HSCT) is one of the main causes of patient mortality. Fever is the most crucial clinical sympt...

Using UAV images and deep learning in investigating potential breeding sites of Aedes albopictus.

Aedes albopictus (Diptera: Culicidae) plays a crucial role as a vector for mosquito-borne diseases like dengue and zika. Given the limited availabilit...

Ontological representation, modeling, and analysis of parasite vaccines.

BACKGROUND: Pathogenic parasites are responsible for multiple diseases, such as malaria and Chagas disease, in humans and livestock. Traditionally, pa...

Predicting clinical outcomes of SARS-CoV-2 infection during the Omicron wave using machine learning.

The Omicron SARS-CoV-2 variant continues to strain healthcare systems. Developing tools that facilitate the identification of patients at highest risk...

Leveraging AI and Machine Learning to Develop and Evaluate a Contextualized User-Friendly Cough Audio Classifier for Detecting Respiratory Diseases: Protocol for a Diagnostic Study in Rural Tanzania.

BACKGROUND: Respiratory diseases, including active tuberculosis (TB), asthma, and chronic obstructive pulmonary disease (COPD), constitute substantial...

Phylogenetic and Molecular Characteristics of Wild Bird-Origin Avian Influenza Viruses Circulating in Poland in 2018-2022: Reassortment, Multiple Introductions, and Wild Bird-Poultry Epidemiological Links.

Since 2020, a significant increase in the severity of H5N highly pathogenic avian influenza (HPAI) epidemics in poultry and wild birds has been observ...

High-Precision Viral Detection Using Electrochemical Kinetic Profiling of Aptamer-Antigen Recognition in Clinical Samples and Machine Learning.

High-precision viral detection at point of need with clinical samples plays a pivotal role in the diagnosis of infectious diseases and the control of ...

Towards classification and comprehensive analysis of AI-based COVID-19 diagnostic techniques: A survey.

The unpredictable pandemic came to light at the end of December 2019, known as the novel coronavirus, also termed COVID-19, identified by the World He...