Bacterial Infection

On-chip bacterial foraging training in silicon photonic circuits for projection-enabled nonlinear classification.

On-chip training remains a challenging issue for photonic devices to implement machine learning algorithms. Most demonstrations only implement inference in photonics for offline-trained neural network models. On the other hand, artificial neural networks are one of the most deployed algorithms, while other machine learning algorithms such as supporting vector machine (SVM) remain unexplored in pho...

Development and Application of Two Inducible Expression Systems for Streptococcus suis.

Streptococcus suis is an important zoonotic bacterial pathogen posing a threat to the pig industry as well as public health, for which the mechanisms of growth and cell division remain largely unknown. Developing convenient genetic tools that can achieve strictly controlled gene expression is of great value for investigating these fundamental physiological processes of S. suis. In this study, we f...

Aglow: A Fluorescence Assay and Machine Learning Model to Identify Inhibitors of Intracellular Infection.

is a genus of Gram-negative bacteria that has for centuries caused large-scale morbidity and mortality. In recent years, the resurgence of rickettsia...

Multi-branch fusion auxiliary learning for the detection of pneumonia from chest X-ray images.

Lung infections caused by bacteria and viruses are infectious and require timely screening and isolation, and different types of pneumonia require dif...

Machine Learning Guided Batched Design of a Bacterial Ribosome Binding Site.

Optimization of gene expression levels is an essential part of the organism design process. Fine control of this process can be achieved by engineerin...

Machine Learning Study of Metabolic Networks ChEMBL Data of Antibacterial Compounds.

Antibacterial drugs (AD) change the metabolic status of bacteria, contributing to bacterial death. However, antibiotic resistance and the emergence of...

Anti-CRISPR prediction using deep learning reveals an inhibitor of Cas13b nucleases.

As part of the ongoing bacterial-phage arms race, CRISPR-Cas systems in bacteria clear invading phages whereas anti-CRISPR proteins (Acrs) in phages i...

Using machine learning techniques to predict antimicrobial resistance in stone disease patients.

PURPOSE: Artificial intelligence is part of our daily life and machine learning techniques offer possibilities unknown until now in medicine. This stu...

Automatic microscopic diagnosis of diseases using an improved UNet++ architecture.

Anthrax is a severe infectious disease caused by the Bacillus anthracis bacterium. This paper aims to design and implement a fast and reliable system ...

Deep Learning to Predict the Biosynthetic Gene Clusters in Bacterial Genomes.

Biosynthetic gene clusters (BGCs) in bacterial genomes code for important small molecules and secondary metabolites. Based on the validated BGCs and t...

Study on transfer learning capabilities for pneumonia classification in chest-x-rays images.

BACKGROUND: over the last year, the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and its variants have highlighted the importance of s...

Antilogic, a new supervised machine learning software for the automatic interpretation of antibiotic susceptibility testing in clinical microbiology: proof-of-concept on three frequently isolated bacterial species.

OBJECTIVE: Antibiotic susceptibility testing (AST) is necessary in order to adjust empirical antibiotic treatment, but the interpretation of results r...

Collaborative Robot Precision Task in Medical Microbiology Laboratory.

This study focuses on the feasibility of collaborative robot implementation in a medical microbiology laboratory by demonstrating fine tasks using kin...

Evaluation of the Effect of Comprehensive Nursing Interventions on Plaque Control in Patients with Periodontal Disease in the Context of Artificial Intelligence.

Plaque is a bacterial biofilm that adheres to each other and exists on the tooth surface, and new plaque can continuously reform after removing it fro...

Identification of antimicrobial peptides from the human gut microbiome using deep learning.

The human gut microbiome encodes a large variety of antimicrobial peptides (AMPs), but the short lengths of AMPs pose a challenge for computational pr...

Rapid Bacterial Detection in Urine Using Laser Scattering and Deep Learning Analysis.

Images of laser scattering patterns generated by bacteria in urine are promising resources for deep learning. However, floating bacteria in urine prod...

Rapid and accurate identification of pathogenic bacteria at the single-cell level using laser tweezers Raman spectroscopy and deep learning.

We report a new method for the rapid identification of pathogenic bacterial species at the single-cell level that combines laser tweezers Raman spectr...

A machine learning approach-based array sensor for rapidly predicting the mechanisms of action of antibacterial compounds.

Rapid and accurate identification of the mechanisms of action (MoAs) of antibacterial compounds remains a challenge for the development of antibacteri...

Effects of Irbesartan and Amlodipine Besylate Tablets on the Intestinal Microflora of Rats With Hypertensive Renal Damage.

The present study aimed to investigate the effects of irbesartan and amlodipine besylate tablets on the intestinal microflora of rats with hypertensi...

Accurate and rapid prediction of tuberculosis drug resistance from genome sequence data using traditional machine learning algorithms and CNN.

Effective and timely antibiotic treatment depends on accurate and rapid in silico antimicrobial-resistant (AMR) predictions. Existing statistical rule...