AIMC Topic: Anti-Bacterial Agents

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Artificial intelligence-accelerated high-throughput screening of antibiotic combinations on a microfluidic combinatorial droplet system.

Lab on a chip
Microfluidic platforms have been employed as an effective tool for drug screening and exhibit the advantages of lower reagent consumption, higher throughput and a higher degree of automation. Despite the great advancement, it remains challenging to s...

Recent Advances of Biosensors for Detection of Multiple Antibiotics.

Biosensors
The abuse of antibiotics has caused a serious threat to human life and health. It is urgent to develop sensors that can detect multiple antibiotics quickly and efficiently. Biosensors are widely used in the field of antibiotic detection because of th...

Photothermal Conversion of Hydrogel-Based Biomaterial.

Chemical record (New York, N.Y.)
Traditional energy from fossil fuels like petroleum and coal is limited and contributes to global environmental pollution and climate change. Developing sustainable and eco-friendly energy is crucial for addressing significant challenges such as clim...

Identification of inhibitors for Agr quorum sensing system of Staphylococcus aureus by machine learning, pharmacophore modeling, and molecular dynamics approaches.

Journal of molecular modeling
CONTEXT: Staphylococcus aureus is a highly pathogenic organism that is the most common cause of postoperative complications as well as severe infections like bacteremia and infective endocarditis. By mediating the formation of biofilms and the expres...

[Factors influencing the implementation of AI-based decision support systems for antibiotic prescription in hospitals: a qualitative analysis from the perspective of health professionals].

Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany))
BACKGROUND: Decision support systems based on artificial intelligence might optimize antibiotic prescribing in hospitals and prevent the development of antimicrobial resistance. The aim of this study was to identify impeding and facilitating factors ...

A deep learning method for predicting the minimum inhibitory concentration of antimicrobial peptides against using Multi-Branch-CNN and Attention.

mSystems
Antimicrobial peptides (AMPs) are a promising alternative to antibiotics to combat drug resistance in pathogenic bacteria. However, the development of AMPs with high potency and specificity remains a challenge, and new tools to evaluate antimicrobial...

Pneumonia-Plus: a deep learning model for the classification of bacterial, fungal, and viral pneumonia based on CT tomography.

European radiology
OBJECTIVES: This study aims to develop a deep learning algorithm, Pneumonia-Plus, based on computed tomography (CT) images for accurate classification of bacterial, fungal, and viral pneumonia.

Robot-Guided Stereotactic Puncture and Drainage in the Treatment of Thalamic Abscess.

The Journal of craniofacial surgery
Brain abscess is rare in clinic, the reported incidence is only 0.4 to 0.90 per 100,000 population, and most of them have a history of prodromal infection. Headache and fever are the most common clinical symptoms, and only a few are accompanied by ne...

Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii.

Nature chemical biology
Acinetobacter baumannii is a nosocomial Gram-negative pathogen that often displays multidrug resistance. Discovering new antibiotics against A. baumannii has proven challenging through conventional screening approaches. Fortunately, machine learning ...

Deep Learning-Assisted Surface-Enhanced Raman Scattering for Rapid Bacterial Identification.

ACS applied materials & interfaces
Bloodstream infection (BSI) is characterized by the presence of viable microorganisms in the bloodstream and may induce systemic immune responses. Early and appropriate antibiotic usage is crucial to effectively treating BSI. However, conventional cu...