Prescriptions

A Gravity-Informed Spatiotemporal Transformer for Human Activity Intensity Prediction.

Human activity intensity prediction is crucial to many location-based services. Despite tremendous progress in modeling dynamics of human activity, most existing methods overlook physical constraints of spatial interaction, leading to uninterpretable spatial correlations and over-smoothing phenomenon. To address these limitations, this work proposes a physics-informed deep learning framework, name...

Adverse reactions of PD-1/PD-L1 inhibitors in cancer: FAERS database analysis and protocols to mitigate immune-related events in elderly patients and when using pembrolizumab and atezolizumab.

OBJECTIVE: This study aimed to characterize adverse drug reactions (ADRs) associated with programmed death-1/programmed death-ligand 1 (PD-1/PD-L1) inhibitors in cancer immunotherapy, identifying demographic, pharmacological, and clinical determinants of toxicity severity using real-world pharmacovigilance data. MATERIALS AND METHODS: We analyzed 93,925 ADR reports from the FDA Adverse Event Repor...

Foot Progression Angle Modulates Three-Dimensional Lower-Limb Biomechanics in Flexible Flatfoot: Kinematic-Kinetic Patterns and Clinical Implications.

INTRODUCTION: Foot progression angle affects gait and lowerlimb alignment. Altered angles may increase knee and ankle loading and produce tissue loadi...

Retrieval Augmented Generation (RAG) for Evaluating Regulatory Compliance of Drug Information and Clinical Trial Protocols.

The purpose was to evaluate retrieval-augmented generative (RAG) artificial intelligence (AI) methods for assessing the regulatory compliance of drug ...

Failure Event Mining With Fine-Tuned Large Language Model: Case Study of Analyzing United States Nuclear Power Plant Failure Event Reports.

Failure event narratives contain detailed and valuable information describing how failures initiate and propagate. Event causality analysis can help i...

Maternal and Pediatric Precision in Therapeutic Knowledge Portal (MPRINT-KP): Landscape Analysis of Pharmacology Research in Maternal and Pediatric Patient Populations.

Pregnant women and children have been underrepresented in clinical studies due to ethical concerns and perceived vulnerabilities. This resulted in a s...

Predicting early discontinuation of adalimumab in patients with rheumatoid arthritis using machine learning: A specialty pharmacy-based approach.

BACKGROUND: Patients with rheumatoid arthritis (RA) prescribed adalimumab often discontinue treatment within 6 months because of a perceived lack of b...

Modeling Polymeric Drug Release: The Emerging Role of Machine Learning.

Polymeric drug formulations have significantly improved the safety, efficacy, and clinical impact of many therapies. A persistent challenge for formul...

Small target detection of floating objects in river channels based on improved YOLOv7.

Computer vision-aided small target detection in moving streams, such as rivers/ roads, requires a fast-converging outcome as the frame requirements ar...

AI-driven forecasting of Vibrio vulnificus in the Southern Baltic Sea using high-resolution data.

Vibrio vulnificus poses a growing public health risk in the brackish Baltic Sea, where rising summer sea temperatures can create optimal conditions fo...

Methodological considerations for a deep learning-based prescription framework for traditional Chinese medicine.

Artificial intelligence revolution in toxicology: Clinical precision, global equity, and the 2030 roadmap.

Artificial intelligence (AI) is transforming toxicology by enabling faster, more accurate, and more equitable approaches to diagnosis, treatment, rese...

Prediction of the joint toxicity of microplastics and organic pollutants on algae based on machine learning.

Complex joint toxicity driven by microplastic (MP)-organic pollutant mixtures in aquatic ecosystems remains poorly captured by conventional models. He...

Machine Learning-Informed Nano Co-Assembly Inhibits Fibroblast Activation Protein and Improves Drug Delivery in Fibrotic Tissue.

Nanoparticle-based drug delivery faces persistent challenges, including complex fabrication processes and limited lesional accumulation. Here we intro...

NLP in Support of Pharmacovigilance: QUality Adverse Drug Reaction AcTIve Control (QUADRATIC).

Adverse drug reactions (ADRs) are a major cause of morbidity, hospital admissions, and in-hospital mortality, yet remain incompletely captured by post...

MDDTA: A Drug Target Binding Affinity Prediction Method Based on Molecular Dynamics Simulation Data Enhancement.

Deep learning-based methods for drug target binding affinity (DTA) prediction are improving the efficien cy of drug screening, but some limitations pe...

Outcomes with revascularization vs. medical therapy according to plaque burden from coronary computed tomography angiography.

AIMS: We aimed to investigate whether plaque burden from coronary computed tomography angiography (CCTA) could be used to identify patients potentiall...

Machine learning models to detect opioid misuse in emergency department patients at triage.

OBJECTIVE: Emergency department (ED) encounters represent valuable opportunities to initiate evidence-based treatments for patients with opioid misuse...

Integrating Clinical Modeling and Machine Learning for Risk Assessment of Paracetamol and Other Nonsteroidal Anti-Inflammatory Drug Hypersensitivity in Children.

BACKGROUND: Nonsteroidal anti-inflammatory drug (NSAID) hypersensitivity is a common cause of drug-related reactions in children. Pre-test risk strati...

Predicting the Course of High-Impact Chronic Pain Using Machine Learning Algorithms.

High-impact chronic pain (HICP) affects over 17 million U.S. adults and follows highly variable courses. To date, the relative importance of biopsycho...