Prescriptions

Artificial Intelligence for Regulatory Evidence: A Systematic Document Analysis of European Medicines Agency Regulatory Advice and Public Reports.

Artificial intelligence (AI) is receiving increasing attention across the entire lifecycle of medicines, from early development to postauthorization use. While various AI tools have been developed in commercial and academic settings, the extent of their use in regulatory contexts within the European Union remains unknown. In this study, we systematically analyzed the use of AI for regulatory evide...

Impact of a Prototype Combining Recommender Functionality With Structured Documentation on Operator Performance in Calls to Medical Communication Centers: Quasi-Experimental Feasibility Study.

BACKGROUND: Management of contacts to medical communication centers relies heavily on clinical judgment, contextual understanding, and communication skills. Decision support systems, intended to complement medical expertise, may, due to their rigidity, impede effective caller interaction and may, together with the obligatory documentation of calls, contribute to a workflow that draws attention awa...

Clinical Context Variables Collectively Rival Model Choice in Embedding-Based Retrieval: Multi-Corpus Benchmark Study.

BACKGROUND: Retrieval-augmented generation (RAG) systems increasingly support clinical decision-making by grounding large language model outputs in ve...

Health AI research capacity and equity-adjusted patient value in 27 European Union countries: an ecological panel study, 2011-2024.

BACKGROUND: Investments in health artificial intelligence (AI) are accelerating across European Union member states, yet evidence linking national AI ...

Divergent neuropsychiatric and systemic toxicity profiles of abemaciclib and palbociclib: a triangulation study integrating pharmacovigilance, genetic epidemiology, and multi-omics profiling.

Cyclin-dependent kinase 4/6 inhibitors improve outcomes in hormone receptor-positive, human epidermal growth factor receptor 2-negative advanced breas...

Towards structure-aware surrogate modeling: explicit region interaction improves knee contact stress prediction in young men.

Knee contact-stress hotspots are closely linked to meniscal/cartilage injury risk. Still, high-fidelity subject-specific FEA is too computationally ex...

Photophysics and complexation of indolic compounds: the effect of intra-annular and extra-annular substitution.

In this work, substitution-dependent modulation of ground- and excited-state properties is examined for intra-annular aza-substituted indoles (indazol...

Deciphering spatial-temporal mechanisms of PD-1 blockade resistance via biologically informed machine learning.

Immune checkpoint inhibitors (ICIs), especially PD-1/PD-L1 blockade, have transformed cancer therapy; yet objective response rates to anti-PD-(L)1 mon...

A Lightweight LSTM-Transformer Fusion Architecture for Real-Time Sepsis Mortality Prediction.

BackgroundAccurate prediction of short-term mortality in sepsis patients is critical for timely clinical decision-making. However, existing deep learn...

SelfBlending: Artificial Intelligence-driven Augmentation with Hand Interactions for Seamless Reality Blending in Virtual Environments.

Accessing real-world objects during immersive virtual reality (VR) experiences remains challenging, as current cross-reality systems often rely on pre...

Evaluating the Potential Impact of AI on Urinary Tract Infection Diagnosis in the Emergency Department Across Demographic Groups: Retrospective Cohort Study.

BACKGROUND: Urinary tract infection (UTI) is a common emergency department (ED) presentation but can be challenging to diagnose; both overdiagnosis an...

S-MEOD: A Novel Evaluation Metric for Frame-Based Medical Object Detection.

Traditional metrics such as precision, recall, mean Average Precision (mAP), and F-score are widely used to evaluate object detection models. However,...

Machine learning-based unified models for predicting drug clearance from pharmacokinetic animal and study design variables.

Clearance (CL) is a primary pharmacokinetic (PK) parameter crucial to determine how quickly a drug is eliminated from the body, which guides the appro...

Artificial intelligence in nutritional assessment and decision making.

PURPOSE OF THE REVIEW: Artificial intelligence (AI) has become an non contourable tool in clinical nutrition practice. This review proposes to discuss...

Learning Drug Synergy through Environment-Conditioned Feature Modulation.

MOTIVATION: Drug combinations are crucial for overcoming resistance in cancer therapy. Although deep learning has achieved strong performance in syner...

Learning Protein Representations with Conformational Dynamics.

MOTIVATION: Proteins change shape as they work, and these changing states control whether binding sites are exposed, signals are relayed, and catalysi...

Lump and breather interaction with different soliton solutions for the generalized doubly dispersive equation by embedded the neural networks.

In this study, we present the neural networks generalized Kudryashov (NNGK) method for the first time to explore exact solutions of the generalized do...

CADS: A Causal Inference Framework for Identifying Essential Genes to Enhance Drug Synergy Prediction.

MOTIVATION: Drug synergy is crucial for developing effective combination therapies, but traditional screening methods suffer from inefficiency and hig...

When AI Colludes: Clinical Reliability of Training and Preference Data as a Trustworthy-AI Criterion.

BACKGROUND: Research on artificial intelligence (AI) and mental health has focused largely on harms at deployment, including chatbot safety, sycophanc...

Hypergraph-Based Dual-Channel Improved Variational Autoencoder with Cross-Attention for Compound-Protein Interactions Identification.

Elucidating compound-protein interactions is crucial for early drug discovery, offering insights into molecular mechanisms and therapeutic potential. ...