AIMC Topic: Anti-Bacterial Agents

Clear Filters Showing 361 to 370 of 710 articles

Deep Learning-Enhanced Potentiometric Aptasensing with Magneto-Controlled Sensors.

Angewandte Chemie (International ed. in English)
Bioelectronic sensors that report charge changes of a biomolecule upon target binding enable direct and sensitive analyte detection but remain a major challenge for potentiometric measurement, mainly due to Debye Length limitations and the need for m...

RMSCNN: A Random Multi-Scale Convolutional Neural Network for Marine Microbial Bacteriocins Identification.

IEEE/ACM transactions on computational biology and bioinformatics
The abuse of traditional antibiotics has led to an increase in the resistance of bacteria and viruses. Similar to the function of antibacterial peptides, bacteriocins are more common as a kind of peptides produced by bacteria that have bactericidal o...

Machine learning and molecular simulation ascertain antimicrobial peptide against Klebsiella pneumoniae from public database.

Computational biology and chemistry
Antimicrobial peptides (AMPs) are short peptides with a broad spectrum of antimicrobial activity. They play a key role in the host innate immunity of many organisms. The growing threat of microorganisms resistant to antimicrobial agents and the lack ...

Antibiotic discovery in the artificial intelligence era.

Annals of the New York Academy of Sciences
As the global burden of antibiotic resistance continues to grow, creative approaches to antibiotic discovery are needed to accelerate the development of novel medicines. A rapidly progressing computational revolution-artificial intelligence-offers an...

Analysis of Characteristic Factors of Nursing Safety Incidents in ENT Surgery by Deep Learning-Based Medical Data Association Rules Method.

Computational and mathematical methods in medicine
It is of great significance to explore the characteristic factors of postoperative nursing safety events in patients with otolaryngology surgery and to understand the characteristics of postoperative nursing safety events in otolaryngology surgery pa...

Risk Factors Analysis of Surgical Infection Using Artificial Intelligence: A Single Center Study.

International journal of environmental research and public health
Surgical site infections (SSIs) have a major role in the evolution of medical care. Despite centuries of medical progress, the management of surgical infection remains a pressing concern. Nowadays, the SSIs continue to be an important factor able to...

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

Communications biology
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 recently developed ZeroCostDL4Mic platform. We generated a database of image datasets used to train n...

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

Molecular pharmaceutics
Antibacterial drugs (AD) change the metabolic status of bacteria, contributing to bacterial death. However, antibiotic resistance and the emergence of multidrug-resistant bacteria increase interest in understanding metabolic network (MN) mutations an...

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

World journal of urology
PURPOSE: Artificial intelligence is part of our daily life and machine learning techniques offer possibilities unknown until now in medicine. This study aims to offer an evaluation of the performance of machine learning (ML) techniques, for predictin...