Prescriptions

Reproducibility of cardiac volumetric parameters derived from fully automatically prescribed image planes: a direct comparison to manual planning at 1.5-T and 3-T MRI.

OBJECTIVES: The prescription of cardiac MRI (CMR) image planes is essential for comparable volumetric assessment, but manual planning is time-consuming and error-prone. This prospective single-center study evaluated automated planning and its impact on the reproducibility of volumetric parameters derived from CMR. MATERIALS AND METHODS: Fifty-two healthy volunteers (26 males, median age 44.5 years...

Risk Modeling and Association Pathways Integrating Psychosocial Factors for Drug Misuse in Adolescents and Young Adults: A Machine Learning Approach.

INTRODUCTION: Early identification for preventing drug misuse among adolescents and young adults (AYAs) is more cost-effective than drug treatment. However, there is a lack of scientific and comprehensive risk models for early identification. This study aimed to construct risk models and association pathways that integrate psychosocial factors influencing drug misuse in AYAs using a machine learni...

The Trial Bank initiative to promote trustworthy living evidence for medication safety (PROMISE) of children: design and pilot validation.

BACKGROUND: While medications are essential for preventing and treating disease, they can also cause harm. Evidence synthesis has been widely adopted ...

CL-MHAD: Contrastive Learning-based Multi-Hypergraph Aggregation and Diffusion model for prescription recommendation.

Multiple syndrome-based prescription recommendations are significant for personalized diagnosis and treatment in Traditional Chinese Medicine (TCM). H...

Artificial Intelligence Impact on Radiologist Performance in Breast Cancer Screening with Digital Breast Tomosynthesis.

PURPOSE: Assess impact of artificial intelligence (AI) on radiologists' detection of cancer on digital breast tomosynthesis (DBT) exams based on densi...

Interpretable Ensemble Machine Learning Prediction of Nonadherence and the Risk of Nonpersistence of Targeted Disease-Modifying Antirheumatic Agents in Older Adults With Rheumatoid Arthritis.

PURPOSE: Ensemble machine learning (ML) demonstrated potential for improving predictions based on big health care data. We developed and validated int...

Deep learning-based H&E-derived risk scores in colorectal cancer: associations with tumour morphology, biology, and predicted drug response.

Over recent years, several deep learning (DL) models have been presented to predict colorectal cancer (CRC) patient survival directly from haematoxyli...

Expanding access to cerebrovascular imaging with routine MRI for pre-surgical assessment of intracranial tumor patients: an AI model development and multi-center validation study.

BACKGROUND: Angiography is the gold standard for assessing the relationship between cerebral arteries and intracranial tumors, but its use is limited ...

[Drug repositioning prediction based on dynamic feature learning on heterogeneous graphs].

OBJECTIVES: To address the challenges faced by existing artificial intelligence methods in modeling complex heterogeneous biological networks, particu...

Electroencephalography-Based Machine Learning Models for Predicting Ketogenic Diet Outcomes in Pediatric Drug-Resistant Epilepsy.

BACKGROUND: Ketogenic diet therapy (KDT) is an established treatment for drug-resistant epilepsy (DRE); however, methods for predicting its effectiven...

Privacy-preserving multimodal fusion for Alzheimer's staging: A federated vision transformer framework with explainable AI.

Accurate, early-stage staging of Alzheimer's disease (AD) is critical for therapeutic intervention but is hampered by data privacy regulations, multim...

RCLG-PPIS: Structure-Aware Protein-Protein Interaction Site Prediction with Cascaded Local and Global Information.

Accurately obtaining Protein-protein Interaction Sites (PPIS) information is crucial for understanding cell functions and drug development. In recent ...

Generative AI in preanesthetic consultations: Effects on efficiency, documentation workload, quality, and physician-patient interaction: A simulation trial.

BACKGROUND: Clinicians spend over 30% of their workday on electronic health records, reducing patient interaction and contributing to burnout. Preanes...

Development of an artificial intelligence platform to improve compliance in periodontal maintenance patients: A proof-of-concept study.

BACKGROUND: The purpose of this study is to report on the development of an artificial intelligence (AI) model designed to improve compliance in perio...

YOLO-based real-time floating debris counting in urban rivers for flood monitoring and water resource management.

Urban flooding is increasingly exacerbated by the accumulation of floating debris in rivers, which obstructs water flow, degrades water quality, and p...

PAIRNet: Predicting PIWI cleavage specificity via position-aware RNA interaction modeling.

PIWI proteins maintain genome integrity by piRNA-guided cleavage of complementary RNA targets. While Cleave-N'-Seq (CNS-seq) has advanced our understa...

Filtering Trust: Disclosing the Role of Artificial Intelligence Decreases Trust in Technology, but Does Not Prevent Harm to Body Image After Viewing AI-Generated Content.

OBJECTIVES: Despite the rapid growth of generative artificial intelligence (AI), virtually no research exists examining the psychological impacts of v...

Prediction of bacterial protein-compound interactions with only positive samples.

MOTIVATION: Prediction of Compound-Protein Interactions (CPI) in bacteria is crucial to advance various pharmaceutical and chemical engineering fields...

A framework for enhancing pharmaceutical integrity and patient safety: novel mobile health solution integrating smart packaging and computer vision.

Counterfeit and substandard pharmaceuticals represent a critical global health crisis, with the World Health Organisation (WHO) reporting that falsifi...

Anomaly detection of cybersecurity behavior using cross-sequence aligned transformer-A dynamic recognition approach for high-frequency interaction patterns.

In high-frequency interaction network environments, network traffic features and user behavior sequences often exhibit pronounced temporal asynchrony ...