AIMC Topic: Drug Interactions

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Assessing GPT-4's accuracy in answering clinical pharmacological questions on pain therapy.

British journal of clinical pharmacology Mar 11, 2025
AIMS: This study aimed to evaluate the accuracy and completeness of GPT-4, a large language model, in answering clinical pharmacological questions related to pain therapy, with a focus on its potential as a tool for delivering patient-facing medical ...
Middle Aged Surveys and Questionnaires Analgesics Humans Cross-Sectional Studies Physicians Male Reproducibility of Results Adult Female Drug Interactions Pain Pain Management Pharmacists Pharmacology, Clinical
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MOLGAECL: Molecular Graph Contrastive Learning via Graph Auto-Encoder Pretraining and Fine-Tuning Based on Drug-Drug Interaction Prediction.

Journal of chemical information and modeling Mar 11, 2025
Drug-drug interactions influence drug efficacy and patient prognosis, providing substantial research value. Some existing methods struggle with the challenges posed by sparse networks or lack the capability to integrate data from multiple sources. In...
Machine Learning Drug Interactions Humans
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Knowledge Graph Neural Network With Spatial-Aware Capsule for Drug-Drug Interaction Prediction.

IEEE journal of biomedical and health informatics Mar 6, 2025
Uncovering novel drug-drug interactions (DDIs) plays a pivotal role in advancing drug development and improving clinical treatment. The outstanding effectiveness of graph neural networks (GNNs) has garnered significant interest in the field of DDI pr...
Computational Biology Drug Interactions Graph Neural Networks Neural Networks, Computer Algorithms Humans
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Characterizing Public Sentiments and Drug Interactions in the COVID-19 Pandemic Using Social Media: Natural Language Processing and Network Analysis.

Journal of medical Internet research Mar 5, 2025
BACKGROUND: While the COVID-19 pandemic has induced massive discussion of available medications on social media, traditional studies focused only on limited aspects, such as public opinions, and endured reporting biases, inefficiency, and long collec...
Drug Interactions COVID-19 Drug Treatment Adenosine Monophosphate Alanine Social Media Natural Language Processing SARS-CoV-2 Antiviral Agents Pandemics COVID-19 Humans
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Chat GPT vs. Clinical Decision Support Systems in the Analysis of Drug-Drug Interactions.

Clinical pharmacology and therapeutics Feb 11, 2025
The current standard method for the analysis of potential drug-drug interactions (pDDIs) is time-consuming and includes the use of multiple clinical decision support systems (CDSSs) and the interpretation by healthcare professionals. With the emergen...
Aged Polypharmacy Retrospective Studies Middle Aged Humans Generative Artificial Intelligence Aged, 80 and over Female Male Decision Support Systems, Clinical Artificial Intelligence Drug Interactions
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DSANIB: Drug-Target Interaction Predictions With Dual-View Synergistic Attention Network and Information Bottleneck Strategy.

IEEE journal of biomedical and health informatics Feb 10, 2025
Prediction of drug-target interactions (DTIs) is one of the crucial steps for drug repositioning. Identifying DTIs through bio-experimental manners is always expensive and time-consuming. Recently, deep learning-based approaches have shown promising ...
Humans Algorithms Drug Repositioning Drug Interactions Deep Learning Computational Biology
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A Multi-View Feature-Based Interpretable Deep Learning Framework for Drug-Drug Interaction Prediction.

Interdisciplinary sciences, computational life sciences Feb 3, 2025
Drug-drug interactions (DDIs) can result in deleterious consequences when patients take multiple medications simultaneously, emphasizing the critical need for accurate DDI prediction. Computational methods for DDI prediction have garnered recent atte...
Deep Learning Drug Interactions Humans Neural Networks, Computer
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Adaptive Multi-Kernel Graph Neural Network for Drug-Drug Interaction Prediction.

Interdisciplinary sciences, computational life sciences Jan 28, 2025
 Combination therapy, which synergistically enhances treatment efficacy and inhibits disease progression through the combined effects of multiple drugs, has emerged as a mainstream approach for treating complex diseases and alleviating symptoms. Howe...
Humans Drug Interactions Graph Neural Networks Neural Networks, Computer Algorithms
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Leveraging Network Target Theory for Efficient Prediction of Drug-Disease Interactions: A Transfer Learning Approach.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Jan 28, 2025
Efficient virtual screening methods can expedite drug discovery and facilitate the development of innovative therapeutics. This study presents a novel transfer learning model based on network target theory, integrating deep learning techniques with d...
Humans Drug Interactions Deep Learning Algorithms Drug Discovery
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Deep Learning of CYP450 Binding of Small Molecules by Quantum Information.

Journal of chemical information and modeling Jan 27, 2025
Drug-drug interaction can lead to diminished therapeutic effects or increased toxicity, posing significant risks, especially in polypharmacy, and cytochrome P450 plays an indispensable role in this interaction. Cytochrome P450, responsible for the me...
Cytochrome P-450 Enzyme System Small Molecule Libraries Cytochrome P-450 CYP1A2 Drug Interactions Quantum Theory Deep Learning Protein Binding Humans
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