Prescriptions

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 information and adherence to best practices in clinical trial protocols. Integrated systems containing RAG and large language model (LLM) components were employed to evaluate drug information and clinical trial protocols. The drug information for ada...

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 improve the understanding of failure physics and facilitate the use of non-failure data (e.g., near-misses and degradations) to complement the limited data pool of failures, which is common in high-reliability industries such as the nuclear power indu...

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...

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...

Multi-Objective Spray Drying Process Optimization via BBD-ANN-AGWO Framework: Case of Andrographolide Amorphous Solid Dispersions.

This study aims to establish a multi-objective spray drying process optimization framework, with andrographolide (ADG) amorphous solid dispersion serv...

Impact of GPT-4-Generated Discharge Letters on Patients' Medical Comprehension: Prospective Crossover Study.

BACKGROUND: Patients often struggle to understand standard hospital discharge letters, increasing the risk of medication errors and misunderstandings....

CPGPrompt: translating clinical guidelines into large language model-executable decision support.

OBJECTIVE: Clinical practice guidelines (CPGs) provide evidence-based recommendations for patient care; however, integrating them into artificial inte...

Retrieval-Augmented Generation for Medical Question Answering on a Heart Failure Dataset: Performance Analysis.

BACKGROUND: The integration of retrieval-augmented generation (RAG) systems into the domain of medical question-answering (QA) presents a significant ...