Prescriptions

Prognostic value of estimated pulse wave velocity for all-cause and cardiovascular mortality in individuals with cardiovascular-kidney-metabolic (CKM) syndrome: analyses of NHANES 2007-2018.

BACKGROUND: The impact of estimated pulse wave velocity (ePWV) on the prognosis of cardiovascular-kidney-metabolic (CKM) syndrome has not been explored. This study investigated the association between ePWV and mortality and its predictive performance in individuals with CKM syndrome. METHODS: This population-based prospective study of 9,416 American participants used ordinal logistic regression to...

Cognitive glues are shared models of relative scarcities: the economics of collective intelligence.

Collective intelligence has emergent problem-solving capacities that are different than those of its subunits. The plethora of multi-scale systems within nature and society makes it imperative to understand the interaction policies necessary and sufficient for emergence of collective intelligences. The economy is a complex system consisting of autonomous elements at multiple scales and which exhib...

ProteinNetworkSight: a user-friendly platform for transforming co-expression patterns into actionable therapeutic insights through interactive network visualization.

ProteinNetworkSight (https://proteinnetworksight.jce.ac) addresses a pervasive bottleneck in modern systems biology: the inability to simultaneously a...

Immunological Drug-Drug Interactions in Immune Checkpoint Inhibitor Therapy: Mechanisms, Clinical Evidence, and Artificial Intelligence.

PURPOSE OF REVIEW: Immune checkpoint inhibitors (ICIs) have transformed cancer therapy, producing durable responses across multiple malignancies. Howe...

Unified model for prediction of the strength of soils stabilized with xanthan gum using white-box machine learning.

Biopolymer-based soil stabilization has attracted increasing attention as a sustainable approach in geotechnical engineering. However, accurate predic...

Tetrahedral framework nucleic acids as a promising vehicle for small molecule drugs of traditional Chinese medicine: application to disease prevention and treatment.

The modernization of Traditional Chinese Medicine (TCM) faces considerable challenges, primarily due to the poor water solubility, low chemical stabil...

Machine Learning for Comparative Antidepressant Selection in Major Depressive Disorder: Systematic Review.

BACKGROUND: Major depressive disorder (MDD) affects approximately 1 in 6 adults during their lifetime, yet antidepressant selection relies predominant...

A quantum graph-based differential model for drug-drug interaction prediction.

Predicting clinically significant drug-drug interactions (DDIs) continues to be an unresolved challenge in contemporary pharmacovigilance, primarily d...

Multimodal interpretable deep learning for transcriptome-informed precision oncology and drug mechanism analysis.

Precision oncology faces critical challenges in interpreting complex cellular signals and predicting drug responses across heterogeneous cancer enviro...

Teaching artificial intelligence through drug-drug interaction clustering analysis: Integrating project-based learning and large language models.

In recent years, artificial intelligence (AI) has increasingly influenced daily life and scientific research. Traditionally, AI-related courses have t...

Hybrid attention-based multi-class classification of Ethiopian legal texts using deep learning.

The exponential growth of legal documents in Ethiopia has created an urgent need for efficient and accurate automated classification systems tailored ...

Model-guided design of lymphatic drug delivery systems using osmotic pressure, viscosity and lymph node size.

Metastatic lymph nodes (LNs) represent a major barrier to effective drug delivery in cancer therapy. To address this challenge, a lymphatic drug deliv...

Experiences and Perceived Influence of the Artificial Intelligence-Based Health Education Accurately Linking System (AI-HEALS) on Health Behaviors Among Patients With Type 2 Diabetes: Qualitative Study.

BACKGROUND: The management of type 2 diabetes requires sustained self-management across diet, physical activity, medication adherence, and blood gluco...

Exploring human GABA transporter 3 binders for epilepsy through quantum reactivity analysis, molecular dynamics, machine learning prediction, and network pharmacology.

CONTEXT: Drug-resistant epilepsy (DRE) remains a major therapeutic challenge, affecting millions of patients globally who do not respond to convention...

Public Expectations for Food and Drug Administration Approval of AI-Based Clinical Decision Support Tools: Quantitative Study.

BACKGROUND: Regulation of artificial intelligence (AI) has been slow relative to the pace of its integration into health care. Several AI diagnostic t...

CT-based radiomic markers to predict late-onset seizures after traumatic brain injury.

Post-traumatic epilepsy (PTE) is a major long-term complication of traumatic brain injury (TBI), but early risk prediction remains imprecise. Radiomic...

Distribution-informed machine learning for flash flood susceptibility: integrating weibull extreme value theory with interpretable models.

Flash floods represent one of the deadliest weather-related hazards globally, yet their prediction remains fundamentally challenged by extreme class i...

An engineering-informed voting ensemble framework for rapid seismic risk screening of reinforced concrete structures.

Rapid evaluation of existing building stocks is essential for reducing earthquake-related disaster risk, particularly in seismically vulnerable cities...

Are AI chatbots ready for chikungunya public education? Evidence on validity, reliability, and readability.

BACKGROUND: Chikungunya continues to expand geographically, driving demand for trustworthy, easy-to-read public guidance. Conversational AI systems ar...

The conditional indirect effect of perceived robot threat on employees' proactive behavior: the moderating role of human-robot interaction.

In the era of artificial intelligence, an increasing number of robots are entering the workplace as active contributors to organizational tasks. While...