AIMC Topic: Drug Combinations
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Artificial intelligence-clinical decision support system for enhanced infectious disease management: Accelerating ceftazidime-avibactam resistance detection in Klebsiella pneumoniae.
Journal of infection and public health
Sep 10, 2024
BACKGROUND: Effective and rapid diagnostic strategies are required to manage antibiotic resistance in Klebsiella pneumonia (KP). This study aimed to design an artificial intelligence-clinical decision support system (AI-CDSS) using matrix-assisted la...
Microbial Sensitivity Tests
Drug Resistance, Multiple, Bacterial
Decision Support Systems, Clinical
Artificial Intelligence
Machine Learning
Anti-Bacterial Agents
Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
Azabicyclo Compounds
Ceftazidime
Klebsiella pneumoniae
Klebsiella Infections
Drug Combinations
Humans
Predicting drug resistance using artificial intelligence and clinical MALDI-TOF mass spectra.
mSystems
Aug 16, 2024
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....
DrugSK: A Stacked Ensemble Learning Framework for Predicting Drug Combinations of Multiple Diseases.
Journal of chemical information and modeling
Jun 20, 2024
Combination therapy is an important direction of continuous exploration in the field of medicine, with the core goals of improving treatment efficacy, reducing adverse reactions, and optimizing clinical outcomes. Machine learning technology holds gre...
Accurate prediction of drug combination risk levels based on relational graph convolutional network and multi-head attention.
Journal of translational medicine
Jun 16, 2024
BACKGROUND: Accurately identifying the risk level of drug combinations is of great significance in investigating the mechanisms of combination medication and adverse reactions. Most existing methods can only predict whether there is an interaction be...
An Artificial Neural Network Predicts Gender Differences of Motor and Non-Motor Symptoms of Patients with Advanced Parkinson's Disease under Levodopa-Carbidopa Intestinal Gel.
Medicina (Kaunas, Lithuania)
May 26, 2024
: Currently, no tool exists to predict clinical outcomes in patients with advanced Parkinson's disease (PD) under levodopa-carbidopa intestinal gel (LCIG) treatment. The aim of this study was to develop a novel deep neural network model to predict th...
MMSyn: A New Multimodal Deep Learning Framework for Enhanced Prediction of Synergistic Drug Combinations.
Journal of chemical information and modeling
Apr 27, 2024
Combination therapy is a promising strategy for the successful treatment of cancer. The large number of possible combinations, however, mean that it is laborious and expensive to screen for synergistic drug combinations in vitro. Nevertheless, becaus...
Augmented drug combination dataset to improve the performance of machine learning models predicting synergistic anticancer effects.
Scientific reports
Jan 18, 2024
Combination therapy has gained popularity in cancer treatment as it enhances the treatment efficacy and overcomes drug resistance. Although machine learning (ML) techniques have become an indispensable tool for discovering new drug combinations, the ...
Antimalarial Drug Combination Predictions Using the Machine Learning Synergy Predictor (MLSyPred©) tool.
Acta parasitologica
Jan 2, 2024
PURPOSE: Antimalarial drug resistance is a global public health problem that leads to treatment failure. Synergistic drug combinations can improve treatment outcomes and delay the development of drug resistance. Here, we describe the implementation o...
What are the most relevant publications in Clinical Microbiology in the last two years?
Revista espanola de quimioterapia : publicacion oficial de la Sociedad Espanola de Quimioterapia
Nov 24, 2023
This minireview describes some of the articles published in the last two years related to innovative technologies including CRISPR-Cas, surface-enhanced Raman spectroscopy, microfluidics, flow cytometry, Fourier transform infrared spectroscopy, and a...
Drug synergy model for malignant diseases using deep learning.
Journal of bioinformatics and computational biology
Jun 22, 2023
Drug synergy has emerged as a viable treatment option for malignancy. Drug synergy reduces toxicity, improves therapeutic efficacy, and overcomes drug resistance when compared to single-drug doses. Thus, it has attained significant interest from acad...
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