Prescriptions

Shaping the future: A pilot study on how AI-powered chatbots shape patient perceptions of pharmacist roles.

OBJECTIVE: To investigate how AI-powered chatbots influence patient perceptions of pharmacist roles compared to traditional educational methods and evaluate whether such technology can address knowledge gaps in pharmacy services. METHODS: A randomized controlled trial using a between-subject design was conducted through a crowdsourcing platform with 280 participants: baseline control (n = 82), edu...

Hypoglycemia problem-solving ability as a key predictor of severe hypoglycemia: a machine learning approach in adults with type 1 diabetes.

AIMS/INTRODUCTION: Severe hypoglycemia (SH) is a major complication in adults with type 1 diabetes mellitus (T1DM). The multifactorial etiology of T1DM highlights the need for predictive tools that integrate clinical, behavioral, and technological factors. This study aimed to develop and evaluate machine learning (ML) models for predicting SH by incorporating hypoglycemia problem-solving ability, ...

Predicting mycophenolic acid exposure in pediatric lupus nephritis: a real-world study across three clinical scenarios.

OBJECTIVES: Childhood-onset systemic lupus erythematosus (cSLE) with lupus nephritis (LN) presents therapeutic challenges due to complex mycophenolic ...

An online machine learning model for predicting medication adherence in hypertensive patients: data from the China health and retirement longitudinal study (CHARLS).

INTRODUCTION: Hypertension, a leading global cause of death with high prevalence and poor control, faces a critical issue of poor medication adherence...

Exploratory identification of COL1A1 as a potential gene linking endocrine-disrupting chemicals and lung adenocarcinoma: a bioinformatics and machine learning analysis.

BACKGROUND: Endocrine-disrupting chemicals (EDCs) are common environmental pollutants that affect human health. These chemicals have been linked to th...

How to undertake oral medicine dosage calculations.

RATIONALE AND KEY POINTS: Safe and effective medicine administration and dosage calculation are fundamental nursing proficiencies. Medicine dosage cal...

Computational Drug Repurposing for Alzheimer's Disease via Sheaf Theoretic Population-Scale Analysis of snRNA-Seq Data.

Single-cell and single-nucleus RNA sequencing are used to reveal heterogeneity in cells, showing a growing potential for precision and personalized me...

Risk Prediction of Chronic Kidney Disease Progression in Type 2 Diabetes Mellitus Across Diverse Populations.

Chronic kidney disease (CKD) is a common complication of type 2 diabetes mellitus (T2DM), with limited predictive tools for individualized prognosis, ...

Towards an objective classification of pachychoroid disease and its risk of progression.

PURPOSE: To identify clinical phenotypes in pachychoroid disease (PD), characterise long-term progression patterns, and evaluate the effect of photody...

Temporal and regional associations between fentanyl concentrations in the unregulated drug supply and drug-related mortality in British Columbia, Canada.

BACKGROUND: British Columbia (BC), Canada, continues to experience persistently high rates of unregulated drug toxicity. While the presence of fentany...

Deep learning-based object detection of dental implant systems in panoramic and periapical radiographs.

STATEMENT OF PROBLEM: The manual identification of dental implant systems on radiographs is time-consuming, operator-dependent, and prone to diagnosti...

Global spatiotemporal analysis of interactions between urban heat islands and extreme heat waves.

Extreme heat waves (HWs), defined here as periods when daily maximum temperature exceeds the 98th percentile for three or more consecutive days, pose ...

AI accelerate the identification of druggable targets by 3D structures of proteins and compounds.

Artificial intelligence (AI) is being used in oncological drug development to address the high costs, low success rates, and long timelines that chara...

A hierarchical interaction message net for accurate molecular property prediction.

Discovering molecules with desirable molecular properties, including ADMET profiles, is of great importance in drug discovery. Existing approaches typ...

Predicting disease-specific histone modifications and functional effects of non-coding variants by leveraging DNA language models.

BACKGROUND: Epigenetic modifications play a vital role in the pathogenesis of human diseases, particularly neurodegenerative disorders such as Alzheim...

Automated prescription of therapeutic exercise for shoulder impingement syndrome using literature-driven rule generation architecture.

BACKGROUND: Shoulder impingement syndrome (SIS) is a common musculoskeletal disorder that requires individualized therapeutic exercise prescription. H...

Trust - IoV: An open benchmark dataset for trust management in the internet of vehicles.

Whilst advancements in information and communication technologies and artificial intelligence have considerably enhanced the capabilities of the Inter...

Unlocking Multiscale Allosteric Mechanisms: Advanced Computational Strategies for Drug Discovery.

Multiscale allosteric mechanisms refer to regulatory processes in proteins that involve coordinated conformational changes and signal transmission occ...

TropMol: a cloud-based web tool for virtual screening and early-stage prediction of acetylcholinesterase inhibitors using machine learning.

Alzheimer's disease (AD) is the most common type of dementia, accounting for at least two-thirds of dementia cases in people aged 65 and older. Numero...

ContraIndicator: A Natural Language Processing-Based Approach to Potential Drug-Drug Interaction Detection in Pediatric Intensive Care.

BACKGROUND AND OBJECTIVES: The intricate nature of pediatric patients' physiology and the frequent administration of multiple medications in pediatric...