AIMC Topic: Anti-Bacterial Agents

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Machine learning and matrix-assisted laser desorption/ionization time-of-flight mass spectra for antimicrobial resistance prediction: A systematic review of recent advancements and future development.

Journal of chromatography. A
BACKGROUND: The use of matrix-assisted laser desorption/ionization time-of-flight mass spectra (MALDI-TOF MS) combined with machine learning techniques has recently emerged as a method to address the public health crisis of antimicrobial resistance. ...

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...

Artificial intelligence and prescription of antibiotic therapy: present and future.

Expert review of anti-infective therapy
INTRODUCTION: In the past few years, the use of artificial intelligence in healthcare has grown exponentially. Prescription of antibiotics is not exempt from its rapid diffusion, and various machine learning (ML) techniques, from logistic regression ...

Surface enhanced Raman spectroscopy and machine learning for identification of beta-lactam antibiotics resistance gene fragment in bacterial plasmid.

Analytica chimica acta
BACKGROUND: Antibiotic resistance stands as a critical medical concern, notably evident in commonly prescribed beta-lactam antibiotics. The imperative need for expeditious and precise early detection methods underscores their role in facilitating tim...

Predicting drug resistance using artificial intelligence and clinical MALDI-TOF mass spectra.

mSystems
Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) is widely used in clinical microbiology laboratories for bacterial identification but its use for detection of antimicrobial resistance (AMR) remains limited....

Unraveling the impact of therapeutic drug monitoring via machine learning for patients with sepsis.

Cell reports. Medicine
Clinical studies investigating the benefits of beta-lactam therapeutic drug monitoring (TDM) among critically ill patients are hindered by small patient groups, variability between studies, patient heterogeneity, and inadequate use of TDM. Accordingl...

Machine Learning Assisted MALDI Mass Spectrometry for Rapid Antimicrobial Resistance Prediction in Clinicals.

Analytical chemistry
Antimicrobial susceptibility testing (AST) plays a critical role in assessing the resistance of individual microbial isolates and determining appropriate antimicrobial therapeutics in a timely manner. However, conventional AST normally takes up to 72...

From Data to Decisions: Leveraging Artificial Intelligence and Machine Learning in Combating Antimicrobial Resistance - a Comprehensive Review.

Journal of medical systems
The emergence of drug-resistant bacteria poses a significant challenge to modern medicine. In response, Artificial Intelligence (AI) and Machine Learning (ML) algorithms have emerged as powerful tools for combating antimicrobial resistance (AMR). Thi...

A MOF-on-MOF heterostructure ratiometric/colorimetric dual-mode fluorescence sensor based on support vector machine for detecting tetracyclines in animal-derived foods.

Food chemistry
The misuse of tetracyclines in livestock production poses significant health risks. Thus, establishing convenient detection methods to replace complex laboratory tests for food safety is crucial. In this study, a heterostructure Zn-BTC/IRMOF-3 (denot...