Prescriptions

Accuracy, Usefulness, and Impact Variability of ChatGPT-4 for COPD Medication Management: A Modified Delphi Study.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) management is complex and rapidly evolving. ChatGPT is a large language model (LLM) shown to generate treatment plans for chronic conditions, yet its accuracy, usefulness, and consistency for COPD remain poorly characterized. This study evaluated the accuracy, usefulness, and impact variability of simultaneous ChatGPT-4.0 responses to COPD m...

Comparative analysis of supervised machine learning algorithms for transdermal drug delivery in brain disorders.

To improve patient compliance and provide stable and prolonged delivery of drugs to the brain, transdermal drug delivery systems (TDDS) are being explored as a viable method of treatment of various brain diseases without the invasion of any organs. Optimization of TDDS remains problematic owing to the complex nonlinear interplay between formulation elements and process factors that affect drug ent...

Prediction of Blood Transfusion Need and Dose in Patients With Upper Gastrointestinal Bleeding: Retrospective Multicenter Prediction Model Study.

BACKGROUND: Transfusion thresholds in upper gastrointestinal bleeding are debated; hemoglobin cutoffs of 70-80 g/L are widely cited yet inconsistently...

Precision pharmacology: deep learning infused ontological framework with E-GRU enhancement for tailored medicine prescriptions.

Advanced Clinical Decision Support Systems significantly influence patient care, with medicine prescriptions being a vital area of research. Ontology,...

What predicts postoperative opioid prescribing and consumption? A statewide analysis of surgical quality registry data.

OBJECTIVE: Tailoring postoperative opioid recommendations to patient needs requires nuanced understanding of factors contributing to post-discharge op...

Addressing the Global Disparities in Access to Treatment in Spinal Muscular Atrophy.

The advent of novel disease-modifying therapeutics for spinal muscular atrophy (SMA) increased life expectancy with better motor function and potentia...

Engineering strategies and translational progress in targeted nanoparticle drug delivery.

INTRODUCTION: Nanoparticle-based drug delivery has emerged as a transformative approach in modern therapeutics, offering improved targeting efficiency...

Cancer drug response and resistance: molecular mechanisms and combating strategies.

Despite remarkable advances in cancer drug treatment, including chemotherapy, targeted therapy, and immunotherapy, therapeutic resistance remains a fo...

Optimizing Cancer Drug Treatments Using Big Data Integration of Genomic and Clinical Data for Personalized Medicine.

Personalized cancer care depends on the seamless integration of genetic profiles, medical histories, and continuous patient monitoring to optimize the...

Temporal Drivers of Opioid-Related ED Visits: An Ensemble Machine Learning Study With Consensus-Based Feature Attribution.

Identification of modifiable risk factors for prescription opioid use disorder (OUD)-related emergency department (ED) visits (ICD-10 F11.xx) is a cli...

Signal Detection and Temporal Analysis of Aromatase Inhibitor-Associated Hepatotoxicity: A Pharmacovigilance Study Integrating Bayesian Belief-Propagation Network and Frequentist Metrics.

BACKGROUND: This study assessed the real-world hepatotoxicity of third-generation aromatase inhibitors (AIs) for breast cancer using pharmacovigilance...

GraESM-FuseDTA: adaptive gated multimodal fusion of graph neural networks and protein language models for robust drug-target affinity prediction.

Accurate drug-target affinity prediction is essential for virtual screening, lead compound prioritization, and drug repositioning, especially under co...

Development and Validation of an XGBoost-SHAP Model for Predicting Adverse Outcomes in Elderly Cardiovascular Patients With Polypharmacy: A Retrospective Cohort Study.

This study aims to develop and validate an interpretable machine learning model using Extreme Gradient Boosting (XGBoost) with SHapley Additive exPlan...

A Data-Driven Medication Regimen Complexity Score for Critically Ill Patients: MRC-ICU 2.0.

BACKGROUND: The 2019 medication regimen complexity-intensive care unit (MRC-ICU) score is associated with patient outcomes, ICU complications, and cri...

Using Machine Learning to Automate the Analysis of an Olfactory Habituation-Dishabituation Task in Mice.

INTRODUCTION: Improving the efficiency and accuracy of annotation and extraction of performance data from mouse behavioral tasks will improve both the...

Ethical Risks and Governance Directions of Conversational Artificial Intelligence in Nursing Triage and Patient Education: Shared Foundations and Contextual Differences.

AIM: To provide an early-stage integrative synthesis of shared and scenario-specific ethical risks of Conversational Artificial Intelligence in nursin...

Automated Multi-Label Adverse drug Reaction Extraction from Malaysia's National Pharmacovigilance Narratives.

Extracting multiple adverse drug reaction (ADR) terms from unstructured narratives remains challenging, particularly under severe label imbalance that...

Discovery and development of small-molecule inhibitors targeting cytotoxic T lymphocyte associated protein 4 to enhance cancer immunotherapy and reduce side effects.

The immune system plays crucial role to fight against cancer. Still, cancer cells have evolved mechanisms to evade immune responses, especially throug...

[AI Chatbots and Suicidality: Implications for Practice].

OBJECTIVE: OpenAI, the provider of ChatGPT, estimates that approximately 0.15% of weekly active users engage in conversations with the chatbot that co...

Fine-tuned machine learning models for the discovery of dye nanoparticles with enhanced lung delivery.

Drug delivery using self-assembling drug-excipient nanoparticles offers a scalable strategy to improve the solubility, bioavailability, and biodistrib...