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Drug Resistance, Microbial

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Deciphering complex antibiotic resistance patterns in through whole genome sequencing and machine learning.

Frontiers in cellular and infection microbiology
INTRODUCTION: Helicobacter pylori (H.pylori, Hp) affects billions of people worldwide. However, the emerging resistance of Hp to antibiotics challenges the effectiveness of current treatments. Investigating the genotype-phenotype connection for Hp us...

Pregnancy-associated asymptomatic bacteriuria and antibiotic resistance in the Maternity and Children's Hospital, Arar, Saudi Arabia.

Journal of infection in developing countries
INTRODUCTION: The Ministry of Health in Saudi Arabia provides comprehensive antenatal care for all pregnant women with all required investigations. However, it does not include urine culture for diagnosis of asymptomatic bacteriuria (ASB). This is th...

Characterising global antimicrobial resistance research explains why One Health solutions are slow in development: An application of AI-based gap analysis.

Environment international
The global health crisis posed by increasing antimicrobial resistance (AMR) implicitly requires solutions based a One Health approach, yet multisectoral, multidisciplinary research on AMR is rare and huge knowledge gaps exist to guide integrated acti...

Deciphering and predicting changes in antibiotic resistance genes during pig manure aerobic composting via machine learning model.

Environmental science and pollution research international
Livestock manure is one of the most important pools of antibiotic resistance genes (ARGs) in the environment. Aerobic composting can effectively reduce the spread of antibiotic resistance risk in livestock manure. Understanding the effect of aerobic ...

Highly accurate classification and discovery of microbial protein-coding gene functions using FunGeneTyper: an extensible deep learning framework.

Briefings in bioinformatics
High-throughput DNA sequencing technologies decode tremendous amounts of microbial protein-coding gene sequences. However, accurately assigning protein functions to novel gene sequences remain a challenge. To this end, we developed FunGeneTyper, an e...

ARGNet: using deep neural networks for robust identification and classification of antibiotic resistance genes from sequences.

Microbiome
BACKGROUND: Emergence of antibiotic resistance in bacteria is an important threat to global health. Antibiotic resistance genes (ARGs) are some of the key components to define bacterial resistance and their spread in different environments. Identific...

Application of machine learning for antibiotic resistance in water and wastewater: A systematic review.

Chemosphere
Antibiotic resistance (AR) is considered one of the greatest global threats in the current century, which can only be overcome if all interconnected areas of humans, animals and the environment are taken into account as part of the One Health concept...

Occurrence and Distribution of Antibacterial Quaternary Ammonium Compounds in Chinese Estuaries Revealed by Machine Learning-Assisted Mass Spectrometric Analysis.

Environmental science & technology
Antimicrobial resistance (AMR) undermines the United Nations Sustainable Development Goals of good health and well-being. Antibiotics are known to exacerbate AMR, but nonantibiotic antimicrobials, such as quaternary ammonium compounds (QACs), are now...

Applying Machine Learning for Antibiotic Development and Prediction of Microbial Resistance.

Chemistry, an Asian journal
Antimicrobial resistance (AMR) poses a serious threat to human health worldwide. It is now more challenging than ever to introduce a potent antibiotic to the market considering rapid emergence of antimicrobial resistance, surpassing the rate of antib...

Applications of Machine Learning on Electronic Health Record Data to Combat Antibiotic Resistance.

The Journal of infectious diseases
There is growing excitement about the clinical use of artificial intelligence and machine learning (ML) technologies. Advancements in computing and the accessibility of ML frameworks enable researchers to easily train predictive models using electron...