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Prescriptions

Latest AI and machine learning research in prescriptions for healthcare professionals.

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Showing 211-231 of 6,756 articles
Pisces: A multi-modal data augmentation approach for drug combination synergy prediction.

Drug combination therapy is promising for cancer treatment by reducing resistance and improving effi...

Integrative strategies in drug discovery: Harnessing genomics, deep learning, and computer-aided drug design.

The development of novel drugs increasingly relies on advanced omics technologies, including genomic...

Personalized medication recommendations for Parkinson's disease patients using gated recurrent units and SHAP interpretability.

Managing Parkinson's disease (PD) through medication can be challenging due to varying symptoms and ...

The Growing Role of Artificial Intelligence in Surgical Education: ChatGPT Undertakes the Australian Generic Surgical Sciences Examination.

BACKGROUND: Large language models have undergone vast development in recent years. The advent of lar...

DrugPipe: Generative artificial intelligence-assisted virtual screening pipeline for generalizable and efficient drug repurposing.

Drug repurposing presents a promising strategy to accelerate drug discovery by identifying new thera...

Prediction of drug-target interactions based on substructure subsequences and cross-public attention mechanism.

Drug-target interactions (DTIs) play a critical role in drug discovery and repurposing. Deep learnin...

Explainability of Protein Deep Learning Models.

Protein embeddings are the new main source of information about proteins, producing state-of-the-art...

The Innovation Paradox in Emerging Pharmaceutical Markets: Barriers and Opportunities for Sustainable Development.

Emerging pharmaceutical markets like Brazil, India, and China have seen significant growth due to ri...

Bioinformatics prediction of function of T-cell exhaustion related genes in ischemic stroke.

Ischemic stroke (IS) is a multifactorial disease caused by the interaction of a variety of environme...

Research on early warning model of coal spontaneous combustion based on interpretability.

Predicting the temperature of the coal spontaneous combustion (CSC) is essential for preventing and ...

Toward Faithful Neural Network Intrinsic Interpretation With Shapley Additive Self-Attribution.

Self-interpreting neural networks have attracted significant attention from the research community. ...

Menopausal hormone therapy and the female brain: Leveraging neuroimaging and prescription registry data from the UK Biobank cohort.

BACKGROUND: Menopausal hormone therapy (MHT) is generally thought to be neuroprotective, yet results...

Automating the Analysis of Substrate Reactivity through Environment Interaction Mapping.

Exploring the interaction configurations between substrates and atomic or molecular systems is cruci...

Drug-drug interaction prediction of traditional Chinese medicine based on graph attention networks.

Predicting drug-drug interactions (DDI) is crucial for preventing adverse reactions in patients and ...

How generative Artificial Intelligence can transform drug discovery?

Generative Artificial Intelligence (Generative AI) is transforming drug discovery by enabling advanc...

Application of high-precision solubility prediction models in the assisted design of drug-like compounds.

Machine learning (ML) techniques are rapidly being applied to drug-assisted design. In order to prov...

Evaluation of Diagnostic Recommendations Embedded in Medication Alerts: Prospective Single-Arm Interventional Study.

BACKGROUND: Potentially inappropriate prescribing in outpatient care contributes to adverse outcomes...

AI in Neurology: Everything, Everywhere, all at Once PART 2: Speech, Sentience, Scruples, and Service.

Artificial intelligence (AI) applications are finding use in real-world neurological settings. Where...

Is Interaction Between Human and Artificial Intelligence-Driven Agents (Para)Social? A Scoping Review.

Despite the growing presence of artificial intelligence (AI)-based agents in human daily life, there...

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