AIMC Topic: Anti-Bacterial Agents

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Scalable de novo classification of antibiotic resistance of Mycobacterium tuberculosis.

Bioinformatics (Oxford, England)
MOTIVATION: World Health Organization estimates that there were over 10 million cases of tuberculosis (TB) worldwide in 2019, resulting in over 1.4 million deaths, with a worrisome increasing trend yearly. The disease is caused by Mycobacterium tuber...

Machine Learning for Clinical Decision Support of Acute Streptococcal Pharyngitis: A Pilot Study.

The Israel Medical Association journal : IMAJ
BACKGROUND: Group A Streptococcus (GAS) is the predominant bacterial pathogen of pharyngitis in children. However, distinguishing GAS from viral pharyngitis is sometimes difficult. Unnecessary antibiotic use contributes to unwanted side effects, such...

Eravacycline, an antibacterial drug, repurposed for pancreatic cancer therapy: insights from a molecular-based deep learning model.

Briefings in bioinformatics
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) remains a serious threat to health, with limited effective therapeutic options, especially due to advanced stage at diagnosis and its inherent resistance to chemotherapy, making it one of the leadin...

[Effect of enzybiotics on the healing of Staphylococcus aureus-infected skin wounds in a pig model].

Klinicka mikrobiologie a infekcni lekarstvi
INTRODUCTION: Staphylococcus aureus is a gram-positive, facultatively anaerobic coccus capable of causing infectious diseases in animals and humans. Especially dangerous are multidrug-resistant forms with poor or even no response to available treatme...

Enhancing Antibiotic Stewardship: A Machine Learning Approach to Predicting Antibiotic Resistance in Inpatient Care.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Antibiotics have been crucial in advancing medical treatments, but the growing threat of antibiotic resistance challenges these achievements and emphasizes the need for innovative stewardship strategies. In this study, we developed machine learning m...

Prediction of Vancomycin-Associated Nephrotoxicity Based on the Area under the Concentration-Time Curve of Vancomycin: A Machine Learning Analysis.

Biological & pharmaceutical bulletin
Several machine learning models have been proposed to predict vancomycin (VCM)-associated nephrotoxicity; however, they have notable limitations. Specifically, they do not use the area under the concentration-time curve (AUC) as recommended in the la...

Machine learning-based antibiotic resistance prediction models: An updated systematic review and meta-analysis.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: The widespread use of antibiotics has led to a gradual adaptation of bacteria to these drugs, diminishing the effectiveness of treatments.

Heterocyclic-Based Analogues against Sarcine-Ricin Loop RNA from : Molecular Docking Study and Machine Learning Classifiers.

Medicinal chemistry (Shariqah (United Arab Emirates))
BACKGROUND: Heterocyclic-based drugs have strong bioactivities, are active pharmacophores, and are used to design several antibacterial drugs. Due to the diverse biodynamic properties of well-known heterocyclic cores, such as quinoline, indole, and i...

Therapeutic effects of orally administration of viable and inactivated probiotic strains against murine urinary tract infection.

Journal of food and drug analysis
Urinary tract infections (UTIs) are highly prevalent bacterial infections that pose significant health risks. Specific probiotic strains have been recommended for UTI control and management of antibiotic resistance. Otherwise, para-probiotics, define...