Bacterial Infection

Classification and Detection of COVID-19 and Other Chest-Related Diseases Using Transfer Learning.

COVID-19 has infected millions of people worldwide over the past few years. The main technique used for COVID-19 detection is reverse transcription, which is expensive, sensitive, and requires medical expertise. X-ray imaging is an alternative and more accessible technique. This study aimed to improve detection accuracy to create a computer-aided diagnostic tool. Combining other artificial intelli...

Nondestructive and multiplex differentiation of pathogenic microorganisms from spoilage microflora on seafood using paper chromogenic array and neural network.

Non-destructive detection of human foodborne pathogens is critical to ensuring food safety and public health. Here, we report a new method using a paper chromogenic array coupled with a machine learning neural network (PCA-NN) to detect viable pathogens in the presence of background microflora and spoilage microbe in seafood via volatile organic compounds sensing. Morganella morganii and Shewanell...

De novo design of anti-tuberculosis agents using a structure-based deep learning method.

Mycobacterium tuberculosis (Mtb) is a pathogen of major concern due to its ability to withstand both first- and second-line antibiotics, leading to dr...

Label-free bacteria identification for clinical applications.

We have developed a system for bacteria identification based on absorption spectroscopy in the mid-infrared spectral range. The data collected are ana...

Bacteria-inspired magnetically actuated rod-like soft robot in viscous fluids.

This paper seeks to design, develop, and explore the locomotive dynamics and morphological adaptability of a bacteria-inspired rod-like soft robot pro...

Rapid identification of salmonella serovars by using Raman spectroscopy and machine learning algorithm.

A widespread and escalating public health problem worldwide is foodborne illness, and foodborne Salmonella infection is one of the most common causes ...

MolPredictX: Online Biological Activity Predictions by Machine Learning Models.

Here we report the development of MolPredictX, an innovate and freely accessible web interface for biological activity predictions of query molecules....

Deep Learning-Enabled Raman Spectroscopic Identification of Pathogen-Derived Extracellular Vesicles and the Biogenesis Process.

Pathogenic bacterial infections, exacerbated by increasing antimicrobial resistance, pose a major threat to human health worldwide. Extracellular vesi...

Machine learning-assisted discovery of growth decision elements by relating bacterial population dynamics to environmental diversity.

Microorganisms growing in their habitat constitute a complex system. How the individual constituents of the environment contribute to microbial growth...

Machine learning approach identifies prominent codons from different degenerate groups influencing gene expression in bacteria.

Unequal usage of synonymous codons is known as codon usage bias (CUB), which is generally different between the high-expression genes (HEG) and low-ex...

Clinical and bacteriological outcomes in patients with urinary tract infections presenting to primary care in Harare, Zimbabwe: a cohort study.

: Treatment for urinary tract infections (UTIs) is usually empiric and is based on local antimicrobial resistance data. These data, however, are scarc...

Dynamic Sepsis Prediction for Intensive Care Unit Patients Using XGBoost-Based Model With Novel Time-Dependent Features.

Sepsis is a systemic inflammatory response caused by pathogens such as bacteria. Because its pathogenesis is not clear, the clinical manifestations of...

Impact of ANN in Revealing of Viral Peptides.

All organisms contain antimicrobial peptides (AMPs), which are a critical component of the innate immune system. These chemicals have the ability to s...

Machine learning-assisted prediction of pneumonia based on non-invasive measures.

BACKGROUND: Pneumonia is an infection of the lungs that is characterized by high morbidity and mortality. The use of machine learning systems to detec...

The Use of Chest Radiographs and Machine Learning Model for the Rapid Detection of Pneumonitis in Pediatric.

Pneumonia is a common lung disease that is the leading cause of death worldwide. It primarily affects children, accounting for 18% of all deaths in ch...

Deep-learning-based removal of autofluorescence and fluorescence quantification in plant-colonizing bacteria in vivo.

Fluorescence microscopy is common in bacteria-plant interaction studies. However, strong autofluorescence from plant tissues impedes in vivo studies o...

A Deep-Learning Based System for Rapid Genus Identification of Pathogens under Hyperspectral Microscopic Images.

Infectious diseases have always been a major threat to the survival of humanity. Additionally, they bring an enormous economic burden to society. The ...

Classification of COVID-19 from tuberculosis and pneumonia using deep learning techniques.

Deep learning provides the healthcare industry with the ability to analyse data at exceptional speeds without compromising on accuracy. These techniqu...

Research on soft sensing method of photosynthetic bacteria fermentation process based on ant colony algorithm and least squares support vector machine.

Photosynthetic bacteria wastewater treatment is an efficient water pollution treatment method, but photosynthetic bacteria fermentation is a multivari...

DeepBacs for multi-task bacterial image analysis using open-source deep learning approaches.

This work demonstrates and guides how to use a range of state-of-the-art artificial neural-networks to analyse bacterial microscopy images using the r...