Bacterial Infection

One-step-immunoassay of procalcitonin enables rapid and accurate diagnosis of bacterial infection.

Procalcitonin (PCT) ( a precursor of calcitonin) attracts much attention as a reliable biomarker of bacterial infections because its concentration increases rapidly in the blood when bacterial infections occur in the body. Sepsis may occur due to indiscriminate and vigorous proliferation of infectious bacteria, and accordingly early diagnosis and treatment of bacterial infection are of crucial imp...

Application of the random forest algorithm to Streptococcus pyogenes response regulator allele variation: from machine learning to evolutionary models.

Group A Streptococcus (GAS) is a globally significant bacterial pathogen. The GAS genotyping gold standard characterises the nucleotide variation of emm, which encodes a surface-exposed protein that is recombinogenic and under immune-based selection pressure. Within a supervised learning methodology, we tested three random forest (RF) algorithms (Guided, Ordinary, and Regularized) and 53 GAS respo...

Decreased neutrophil-mediated bacterial killing in COVID-19 patients.

The coronavirus disease COVID-19 was first described in December 2019. The peripheral blood of COVID-19 patients have increased numbers of neutrophils...

An Overview of Deep Learning Techniques on Chest X-Ray and CT Scan Identification of COVID-19.

Pneumonia is an infamous life-threatening lung bacterial or viral infection. The latest viral infection endangering the lives of many people worldwide...

Identifying genomic islands with deep neural networks.

BACKGROUND: Horizontal gene transfer is the main source of adaptability for bacteria, through which genes are obtained from different sources includin...

Immunomodulatory and antimicrobial non-mulberry silk fibroin accelerates fibroblast repair and regeneration by protecting oxidative stress.

The antimicrobial nature of silk-fibroin (SF) is reported but antioxidant potential and the immunomodulatory role towards the fibroblast cell repair ...

COVID-19 diagnosis by routine blood tests using machine learning.

Physicians taking care of patients with COVID-19 have described different changes in routine blood parameters. However, these changes hinder them from...

Prediction of population behavior of Listeria monocytogenes in food using machine learning and a microbial growth and survival database.

In predictive microbiology, statistical models are employed to predict bacterial population behavior in food using environmental factors such as tempe...

Rational structural modification of the isatin scaffold to develop new and potent antimicrobial agents targeting bacterial peptidoglycan glycosyltransferase.

A series of isatin derivatives bearing three different substituent groups at the N-1, C-3 and C-5 positions of the isatin scaffold were systematically...

Combining genetic algorithm with machine learning strategies for designing potent antimicrobial peptides.

BACKGROUND: Current methods in machine learning provide approaches for solving challenging, multiple constraint design problems. While deep learning a...

A Zwitterionic-Aromatic Motif-Based ionic skin for highly biocompatible and Glucose-Responsive sensor.

Electronic skins that can sense external stimuli have been of great significance in artificial intelligence and smart wearable devices in recent years...

Aiding clinical assessment of neonatal sepsis using hematological analyzer data with machine learning techniques.

INTRODUCTION: Early diagnosis and antibiotic administration are essential for reducing sepsis morbidity and mortality; however, diagnosis remains diff...

Convolutional Sparse Support Estimator-Based COVID-19 Recognition From X-Ray Images.

Coronavirus disease (COVID-19) has been the main agenda of the whole world ever since it came into sight. X-ray imaging is a common and easily accessi...

FBSED based automatic diagnosis of COVID-19 using X-ray and CT images.

This work introduces the Fourier-Bessel series expansion-based decomposition (FBSED) method, which is an implementation of the wavelet packet decompos...

Classification of COVID-19 chest X-Ray and CT images using a type of dynamic CNN modification method.

Understanding and classifying Chest X-Ray (CXR) and computerised tomography (CT) images are of great significance for COVID-19 diagnosis. The existing...

Predicting the performance of anaerobic digestion using machine learning algorithms and genomic data.

Modeling of anaerobic digestion (AD) is crucial to better understand the process dynamics and to improve the digester performance. This is an essentia...

CT-Based COVID-19 triage: Deep multitask learning improves joint identification and severity quantification.

The current COVID-19 pandemic overloads healthcare systems, including radiology departments. Though several deep learning approaches were developed to...

Development and Validation of a Machine Learning Model to Estimate Bacterial Sepsis Among Immunocompromised Recipients of Stem Cell Transplant.

IMPORTANCE: Sepsis disproportionately affects recipients of allogeneic hematopoietic cell transplant (allo-HCT), and timely detection is crucial. Howe...

Nonlinear machine learning pattern recognition and bacteria-metabolite multilayer network analysis of perturbed gastric microbiome.

The stomach is inhabited by diverse microbial communities, co-existing in a dynamic balance. Long-term use of drugs such as proton pump inhibitors (PP...

Deep Learning for Novel Antimicrobial Peptide Design.

Antimicrobial resistance is an increasing issue in healthcare as the overuse of antibacterial agents rises during the COVID-19 pandemic. The need for ...