Prescriptions

Chemical genomics language model toward reliable and explainable compound-protein interaction exploration.

Accurate prediction of compound-protein interactions (CPIs) is crucial for chemical biology and drug discovery. Despite recent advancements, existing deep learning (DL)-based CPI models often struggle to simultaneously achieve high generalization performance, quantify prediction confidence, and ensure explainability. Here, we propose ChemGLaM, a chemical genomics language model designed to address...

The impact of artificial intelligence (AI) on the quality of life for individuals with intellectual disabilities in Saudi Arabia: A PRISMA-compliant systematic review and meta-analysis.

BACKGROUND: Artificial intelligence (AI) is increasingly being integrated into health, education, and social systems, offering new opportunities to enhance the quality of life (QoL) for individuals with intellectual disabilities (ID). Saudi Arabia has yet to fully realize the potential of these technologies in addressing the specific needs of people with ID. This study aims to systematically revie...

μPharma: A microfluidic, AI-driven pharmacotyping platform for single-cell drug sensitivity prediction in leukemia.

BACKGROUND: Pharmacotyping, the ex vivo measurement of tumor cell responses to drugs, is particularly important for cancers lacking actionable genomic...

Graph former-CL: A novel graph transformer with contrastive learning framework for enhanced drug-drug interaction prediction.

Drug-drug interactions (DDI) represent a significant clinical challenge in modern healthcare, contributing to over 125,000 deaths annually in the Unit...

An interpretable machine learning framework for adverse drug reaction prediction from drug-target interactions.

BACKGROUND: Adverse drug reactions (ADRs) present challenges to patient safety and healthcare systems. Current pharmacovigilance methods, such as the ...

Evaluation of six large language models for study identification in an obstetric systematic review.

BACKGROUND: Identifying eligible studies is a foundational component of systematic reviews, requiring careful interpretation of complex inclusion and ...

A multilayered integrated analysis of insomnia-related genes ATG7 and JAK2 in the autophagy-inflammation mechanism and clinical implications in major depressive disorder.

OBJECTIVE: Insomnia is widely recognized as a key risk factor for major depressive disorder (MDD). However, the potential molecular mechanisms and the...

From virtual screening to bench: A dual-validation framework for drug repurposing against PI3K.

Virtual screening has emerged as one of the most impactful in silico approaches for the identification of novel drug candidates, substantially reducin...

Generic fitting models learn edge representations from prenatal retinal waves.

Orientation selectivity-the representation of oriented edges-is a hallmark of biological vision, shared across mammals, birds, and reptiles. However, ...

Anti-Inflammatory Properties of Dendrobium: A Systematic Review of Pharmacological Mechanisms.

ETHNOPHARMACOLOGICAL RELEVANCE: In Traditional Chinese Medicine (TCM), Dendrobium species have long been utilized to alleviate various inflammatory sy...

Detection of Antithrombotic-Related Bleeding in Older Inpatients: Multicenter Retrospective Study Using Structured and Unstructured Electronic Health Record Data.

BACKGROUND: Bleeding complications are a major contributor to adverse drug events among older inpatients, particularly in those treated with antithrom...

Predicting postoperative delirium after lung cancer resection: the utility of synthetic data and LIME algorithm for model interpretation.

To construct an efficient predictive model for post-lung cancer resection delirium (POD) using artificial intelligence, with a focus on leveraging syn...

Machine learning models for drug-drug interaction prediction from computational discovery to clinical application.

Drug-drug interaction (DDI) poses a major challenge in clinical pharmacology, often compromising therapeutic efficacy or causing serious adverse event...

Synergies between data science methods and innovative drug delivery technologies.

Most areas of science and technology and beyond are undergoing an almost unprecedented rate of change, driven largely by the rapid growth in automatio...

PBPK Modeling Addresses Oral Absorption-Mediated Drug Interactions.

Absorption is the first and imperative step to understanding the pharmacokinetics (PK) and ADME (absorption, distribution, metabolism, and excretion) ...

Distinguishing a drug use disorder from drug use in a high-risk sample of youth: A random forest classification and explanatory analysis.

Although many adolescents and young adults experiment with drugs, a subset may develop a drug use disorder (DUD). Few studies have used machine learni...

Attention-Guided Multiview Deep Learning Framework Uncovers miRNA-Drug Associations for Therapeutic Discovery.

MicroRNAs (miRNAs) play critical roles in regulating various biological processes and offer significant potential for treating human diseases. Aberran...

Cross specialty evaluation of large language model responses on intentional replantation.

BACKGROUND: The expanding use of LLMs (Large Language Models) for rapid, practical information access has accelerated their integration into medicine ...

Mechanistic insights into heart failure progression and therapeutic target discovery through plasma microRNA profiling: Findings from HOMAGE.

BACKGROUND: Identifying early pathobiological mechanisms associated with the onset and progression of heart failure (HF) could guide development of pr...

Human-AI interaction and collaboration in radiology: from conceptual frameworks to responsible implementation.

Artificial intelligence (AI) is entering routine radiology practice, but most studies evaluate algorithms in isolation rather than their interaction w...