Prescriptions

Platelets as Programmable Drug Depots: Toward Predictive and Mechanistic Drug Loading.

Efficient drug delivery remains a major challenge in pharmaceutical science, with synthetic nanocarriers often facing limitations in real biological systems. While blood platelets have been explored as biomimetic carriers, their intrinsic capacity for molecular storage and stimulus-triggered release remains largely underutilized. Here, we propose that platelet granules can be viewed as programmabl...

Cost-effectiveness of artificial intelligence interventions for musculoskeletal disorders of the spine: a systematic review.

Musculoskeletal disorders (MSDs) represent a substantial global health burden, and artificial intelligence (AI)-based technologies are emerging as potential approaches for their management. However, evidence regarding the cost-effectiveness of these interventions remains limited. This systematic review synthesised the available evidence on the cost-effectiveness of AI-based technologies for managi...

Biomedical Large Language Models and Prompt Engineering for Causality Assessment of Individual Case Safety Reports in Pharmacovigilance.

BACKGROUND: Biomedical Large Language Models (LLMs) combined with prompt engineering offer domain-specific reasoning, yet their application to individ...

Integrated multi-stage screening assisted discovery and optimization of spirooxindole MDM2 inhibitors.

The rational design of novel MDM2 inhibitors with superior biochemical properties represents the most consequential outcome of contemporary computer-a...

From interface to outcome: a 4I framework for AI-linked functionality in electronic health records.

BACKGROUND: Electronic health records (EHRs) are central to clinical documentation and care coordination, yet long-standing studies report persistent ...

A Comprehensive Self-Medication Management System to Reduce Medication Errors Among People Living With Dementia: Mixed Methods Feasibility and Usability Study.

BACKGROUND: Medication adherence is a critical challenge for people living with dementia and their caregivers. Standard care relies on appropriate med...

Twelve Tips for Recognizing and Addressing the Adverse Effects of Medical Education Interventions: Tutorial.

"First, do no harm" is a fundamental principle in health care, and clinical researchers carefully monitor adverse drug reactions to ensure patient saf...

Autonomous RCM-less endoscope control: integrating force-based pivoting with deep learning visual servoing.

Robotic endoscope holders improve visual stability, yet enforcing a fixed remote center of motion (RCM) often induces lateral interaction forces due t...

Feasibility of Causality-Aware Machine Learning for Drug Safety on OMOP-CDM.

Regulators increasingly view real-world healthcare data and potential use of Artificial Intelligence (AI) approaches as vital for pharmacovigilance (P...

Machine Learning for Cardiovascular Prevention Prescriptions: Real-World vs. Synthetic Data.

Cardiovascular diseases remain the leading cause of death worldwide, primarily driven by atherosclerosis, which is targeted by lipid-lowering agents s...

Keep it Simple, Stupid! Towards PySTRIPA for Medication Reviews.

We revisit and reimagine STRIPA, the STRIP Assistant. The Systematic Tool to Reduce Inappropriate Prescribing Assistant is a medication review system ...

Generation of Training Data to Distinguish Adverse Events from Medical Conditions.

To support pharmacovigilance activities in social media, innovative methods are required to detect named entities corresponding to drugs and adverse e...

Interpretable Feature Extraction from Clinical Notes for Sepsis Prediction: Comparing Rule-Based, LLM, and Hybrid Approaches.

Embedding-based approaches integrate clinical notes into sepsis prediction models but produce uninterpretable representations, obscuring which clinica...

Cross-Institutional Data Harmonization for AI in Nursing Care Using the OMOP CDM.

Artificial Intelligence (AI) offers potential to support and empower nurses, yet its development depends on the availability of high-quality, standard...

Integrating Multi-Source Biomedical Data for Adverse Drug Reaction Analysis: A Knowledge Graph Approach.

Understanding adverse drug reaction mechanisms requires integrating information from multiple heterogeneous sources. We developed a pipeline for combi...

FGAIM: Identifying Drug-Target Activation and Inhibition Mechanisms via Inductive Graph Neural Networks Based on Fine-Grained Interaction Strategies.

Distinguishing the activation and inhibition mechanisms between drugs and targets can reveal the potential regulatory pathways of target functions, wh...

A digital twin-driven computation and analysis framework for low-altitude airspace.

This study aims to address critical challenges in low-altitude airspace management, including high dynamic complexity, substantial safety hazards, and...

Predicting intrinsic clearance using deep learning-based drug-metabolic enzyme interaction features on an IVIVE-harmonized endpoint dataset.

BACKGROUND AND OBJECTIVE: Intrinsic clearance is a key pharmacokinetic parameter in drug development because it influences systemic exposure and dose ...

Enhancing prediction of inpatient deterioration by combining clinical and nurse concern features, with or without temporal clustering.

BACKGROUND: Early warning systems (EWSs) help clinicians identify deteriorating patients using clinical data, such as vital signs. However, standard s...

Real-time interaction with artificial intelligence and its association with learning experience and academic performance among undergraduate nursing students in Peshawar: an analytical cross-sectional study.

BACKGROUND: Artificial intelligence (AI) has been widely incorporated in the education domain for offering adaptive learning, personalized feedback an...