Prescriptions

Precise Staging of Diabetic Retinopathy Through Machine Learning Analysis of Leakage Source Characteristics: A Radiomics-Driven Approach Integrating OCT-A and FFA.

INTRODUCTION: Evaluating retinal fundus image for diabetic retinopathy (DR) assessment is used to reduce the risk of blindness among diabetic patients. To do this, DR staging is one of the challenging tasks in screening DR that includes the assessment of disease severity or progression. We introduce a novel Radiomics and machine learning algorithm (MLA) framework that analyzes localized vascular l...

Mitigating Algorithmic Bias in AI-Powered Toxicology: Frameworks for Explainable and Equitable Predictions in Human Health and Environmental Safety.

The rapid integration of artificial intelligence (AI) and machine learning into predictive toxicology has transformed chemical hazard identification, toxicity endpoint forecasting, and risk assessment for pharmaceuticals, environmental pollutants, and consumer products. While these tools promise faster, more ethical alternatives to traditional testing, they introduce significant risks of algorithm...

Differential cerebral white matter tract alterations in generalized anxiety disorder revealed by ultra-high-field 7 T diffusion-weighted imaging.

Generalized anxiety disorder (GAD) is characterized by chronic worry and emotional dysregulation, yet its underlying white matter (WM) microstructural...

Screening for Periodontitis Using Blood Biomarkers and Demographic Data: A Machine Learning Study.

PURPOSE: Periodontitis is a common chronic disease associated with systemic conditions such as diabetes and cardiovascular disease. Diagnosis typicall...

Fingertip-scale six-axis tactile interface with high-precision force sensing and position localization for dexterous human-machine interactions.

Developing microsystem-based tactile sensors that can simultaneously decode multidirectional forces and precise contact locations remains a formidable...

Single-cell approach dissecting agr quorum sensing dynamics in Staphylococcus aureus.

Quorum sensing (QS) enables bacteria to coordinate collective behaviors by secreting and sensing diffusible signals. Understanding QS at single-cell r...

AI-driven insights into the impact of tourism on local cultures: a machine learning approach.

Tourism is increasingly recognized as a powerful driver of economic growth, spatial restructuring, and cultural change, yet empirical evidence on how ...

Multi-scale buffer analysis and explainable machine learning identify urban form factors and thresholds for waterlogging in Shenzhen urban villages during 9·7 rainstorm.

Under the combined pressures of extreme rainfall and rapid urbanization, urban waterlogging has become increasingly severe. As high-density and low-in...

Visual design and digital transformation of imaging under artificial intelligence technology.

This study proposes a conditional hierarchical generative adversarial network (GAN) model for intelligent visual design, aiming to explore new modes o...

SDP-ChroNet: A shared dilated pooling network for chromatin interaction prediction.

A deep understanding of chromatin interactions is crucial for elucidating the mechanisms of gene expression regulation. Although various computational...

Comprehensive Review of Contrastive and Generative Self-Supervised Learning for Small Molecular Representation.

Drug discovery is a complex and resource-intensive process, where developing effective computational tools to analyze vast and heterogeneous molecular...

Extracting Social Determinants of Health From Electronic Health Records: Development and Comparison of Rule-Based and Large Language Model Methods.

BACKGROUND: Social determinants of health (SDoH) are critical drivers of health outcomes but are often underdocumented in structured electronic health...

Illuminating the black box of reservoir computing.

Reservoir computers, using recurrent neural networks with fixed random connections, are known to perform a wide range of information-processing tasks....

Heterogeneous biological graph convolutional network for drug-target interaction prediction.

Drug-target interaction prediction plays a critical role in drug discovery by identifying potential therapeutic targets and elucidating underlying mol...

Revisiting ADMET prediction reliability under real-world challenges in the foundation model era.

As AI-driven drug discovery fully enters the era of foundation models, druggability prediction is undergoing a profound transformation from being expe...

Machine Learning-Based Soft Voting Ensemble Model for the Prediction of Oral Drug-Likeness of Chemical Structures.

Drug discovery is a costly process with low success rates. Early prioritization of compounds based on drug-likeness estimation can help reduce attriti...

Machine Learning-Based Study on Xin-Pi Simultaneous Treatment Formula via Drug Nanodelivery Systems Regulating Macrophage Polarization and TEAD2/PKM2 Synergistic Repair Strategy in Myocarditis.

BACKGROUND: Myocarditis, as an important cardiovascular disease, involves complex pathogenic mechanisms including immune dysregulation and metabolic d...

Customer churn prediction in privacy-preserving HashCode-based security abstractions.

This research presents a HashCode-based security abstraction that implements privacy-by-design in customer churn statistics, safeguarding identity whi...

Strengthening Holistic Nursing Competence Among Emergency Nurses in the Digital Era: The Roles of Clinical Governance, Digital Empathy, and Artificial Intelligence Attitude.

INTRODUCTION: Digital technologies and artificial intelligence are rapidly transforming emergency nursing, raising concerns about how nurses can susta...

Accuracy and hallucination behaviors of artificial intelligence-based large language models for dental implant identification on radiographs.

OBJECTIVES: This study aimed to evaluate the accuracy and error patterns of four artificial intelligence-based large language models (LLMs) in identif...