Infectious Disease

Single-cell segmentation in bacterial biofilms with an optimized deep learning method enables tracking of cell lineages and measurements of growth rates.

Bacteria often grow into matrix-encased three-dimensional (3D) biofilm communities, which can be imaged at cellular resolution using confocal microscopy. From these 3D images, measurements of single-cell properties with high spatiotemporal resolution are required to investigate cellular heterogeneity and dynamical processes inside biofilms. However, the required measurements rely on the automated ...

An investigation into epidemiological situations of COVID-19 with fuzzy K-means and K-prototype clustering methods.

The ten countries with the highest population during the pandemic were analyzed for clustering based on the quantitative numbers of COVID-19 and policy plans. The Fuzzy K-Means (FKM) and K-prototype algorithms were used for clustering, and various performance indices such as Partition Coefficient (PC), Partition Entropy (PE), Xie-Beni (XB), and Silhouette Fuzzy (SIL.F) were used for evaluating the...

Bifunctional robots inducing targeted protein degradation.

The gaining importance of Targeted Protein Degradation (TPD) and PROTACs (PROteolysis-TArgeting Chimeras) have drawn the scientific community's attent...

Neural network based integration of assays to assess pathogenic potential.

Limited data significantly hinders our capability of biothreat assessment of novel bacterial strains. Integration of data from additional sources that...

Collaborative training of medical artificial intelligence models with non-uniform labels.

Due to the rapid advancements in recent years, medical image analysis is largely dominated by deep learning (DL). However, building powerful and robus...

A historical, economic, and technical-scientific approach to the current crisis in the development of antibacterial drugs: Promising role of antibacterial peptides in this scenario.

The emergence of antibiotic resistance (AMR) is a global public health problem. According to estimates, drug-resistant bacteria infect 2 million patie...

A multicenter evaluation of a deep learning software (LungQuant) for lung parenchyma characterization in COVID-19 pneumonia.

BACKGROUND: The role of computed tomography (CT) in the diagnosis and characterization of coronavirus disease 2019 (COVID-19) pneumonia has been widel...

Deep learning-based network pharmacology for exploring the mechanism of licorice for the treatment of COVID-19.

Licorice, a traditional Chinese medicine, has been widely used for the treatment of COVID-19, but all active compounds and corresponding targets are s...

Comparison of deep learning models with simple method to assess the problem of antimicrobial peptides prediction.

Antibiotic-resistant strains are an emerging threat to public health. The usage of antimicrobial peptides (AMPs) is one of the promising approaches to...

Addressing antibiotic resistance: computational answers to a biological problem?

The increasing prevalence of infections caused by antibiotic-resistant bacteria is a global healthcare crisis. Understanding the spread of resistance ...

Lexicon-based sentiment analysis to detect opinions and attitude towards COVID-19 vaccines on Twitter in Italy.

The paper proposes a methodology based on Natural Language Processing (NLP) and Sentiment Analysis (SA) to get insights into sentiments and opinions t...

Engineering growth phenotypes of Aspergillus oryzae for L-malate production.

Improving the growth status of Aspergillus oryzae is an efficient way to enhance L-malate production. However, the growth mechanism of filamentous fun...

Hybrid optimized feature selection and deep learning based COVID-19 disease prediction.

The COVID-19 virus has affected many people around the globe with several issues. Moreover, it causes a worldwide pandemic, and it makes more than one...

A systematic review and repeatability study on the use of deep learning for classifying and detecting tuberculosis bacilli in microscopic images.

Tuberculosis (TB) is among the leading causes of death worldwide from a single infectious agent. This disease usually affects the lungs (pulmonary TB)...

Self-Attention Based Neural Network for Predicting RNA-Protein Binding Sites.

Proteins binding to Ribonucleic Acid (RNA) inside cells are called RNA-binding proteins (RBP), which play a crucial role in gene regulation. The ident...

Associations Between Older Adults' Loneliness and Acceptance of Socially Assistive Robots: A Cross-Sectional Study.

The use of socially assistive robots (SARs) to enable older adults (aged ≥65 years) to live independently for as long as possible has been researched ...

Clinically explainable machine learning models for early identification of patients at risk of hospital-acquired urinary tract infection.

BACKGROUND: Machine learning (ML) models for early identification of patients at risk of hospital-acquired urinary tract infection (HA-UTI) may enable...

Leptin levels in childhood tuberculosis and its correlation with body mass index, IFN-γ, and TNF-α in an Indonesian population.

BACKGROUND: Leptin plays a key role in the regulation of energy and inflammation in tuberculosis (TB). However, its correlation in children with TB re...

Neural-Like P Systems With Plasmids and Multiple Channels.

Neural-like P systems with plasmids (NP P systems, in short) are a kind of distributed and parallel computing systems inspired by the activity that ba...

Benchmark methodological approach for the application of artificial intelligence to lung ultrasound data from COVID-19 patients: From frame to prognostic-level.

Automated ultrasound imaging assessment of the effect of CoronaVirus disease 2019 (COVID-19) on lungs has been investigated in various studies using a...