Prescriptions

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 attrition rates. Here we present HADES (Holistic AI-based Drug-likeness Estimation Score), a soft voting ensemble of five machine learning models that integrates ADMET and physicochemical properties to provide a unified prediction of drug-likeness. Across d...

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 disorders. The Traditional Chinese Medicine (TCM) theory of "simultaneous treatment of heart and spleen" has accumulated substantial clinical experience in treating myocarditis, yet its underlying mechanisms remain insufficiently elucidated. The devel...

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...

Real-time spectral interferometry analysis of multi-soliton dynamics based on an unsupervised physical information embedding neural network.

The real-time characterization of soliton interaction parameters is of great significance for improving the performance of passively mode-locked fiber...

Exposure to ambient PM2.5 constituents and semen quality in a retrospective cohort study: Windows of susceptibility and modification by greenness.

BACKGROUND: Access to abundant greenness and avoiding exposure to ambient fine particulate matter (PM2.5) are known to be associated with favorable he...

Influence of scintillation light confinement on depth-of-interaction measurement performance in a single-Ended readout PET detector.

Continuous depth-of-interaction (cDOI) detectors enable single-ended readout in positron emission tomography (PET) by encoding the interaction depth i...

Applying explainable artificial intelligence to interpret supervised ensemble learning models for robust credit card fraud detection.

As the usage of digital financial transactions continue to swell, it becomes all the more crucial to employ classifiers with machine learning techniqu...

Prognostic value of estimated pulse wave velocity for all-cause and cardiovascular mortality in individuals with cardiovascular-kidney-metabolic (CKM) syndrome: analyses of NHANES 2007-2018.

BACKGROUND: The impact of estimated pulse wave velocity (ePWV) on the prognosis of cardiovascular-kidney-metabolic (CKM) syndrome has not been explore...

Cognitive glues are shared models of relative scarcities: the economics of collective intelligence.

Collective intelligence has emergent problem-solving capacities that are different than those of its subunits. The plethora of multi-scale systems wit...

ProteinNetworkSight: a user-friendly platform for transforming co-expression patterns into actionable therapeutic insights through interactive network visualization.

ProteinNetworkSight (https://proteinnetworksight.jce.ac) addresses a pervasive bottleneck in modern systems biology: the inability to simultaneously a...

Immunological Drug-Drug Interactions in Immune Checkpoint Inhibitor Therapy: Mechanisms, Clinical Evidence, and Artificial Intelligence.

PURPOSE OF REVIEW: Immune checkpoint inhibitors (ICIs) have transformed cancer therapy, producing durable responses across multiple malignancies. Howe...

Unified model for prediction of the strength of soils stabilized with xanthan gum using white-box machine learning.

Biopolymer-based soil stabilization has attracted increasing attention as a sustainable approach in geotechnical engineering. However, accurate predic...

Tetrahedral framework nucleic acids as a promising vehicle for small molecule drugs of traditional Chinese medicine: application to disease prevention and treatment.

The modernization of Traditional Chinese Medicine (TCM) faces considerable challenges, primarily due to the poor water solubility, low chemical stabil...

Machine Learning for Comparative Antidepressant Selection in Major Depressive Disorder: Systematic Review.

BACKGROUND: Major depressive disorder (MDD) affects approximately 1 in 6 adults during their lifetime, yet antidepressant selection relies predominant...

A quantum graph-based differential model for drug-drug interaction prediction.

Predicting clinically significant drug-drug interactions (DDIs) continues to be an unresolved challenge in contemporary pharmacovigilance, primarily d...

Multimodal interpretable deep learning for transcriptome-informed precision oncology and drug mechanism analysis.

Precision oncology faces critical challenges in interpreting complex cellular signals and predicting drug responses across heterogeneous cancer enviro...

Teaching artificial intelligence through drug-drug interaction clustering analysis: Integrating project-based learning and large language models.

In recent years, artificial intelligence (AI) has increasingly influenced daily life and scientific research. Traditionally, AI-related courses have t...

Hybrid attention-based multi-class classification of Ethiopian legal texts using deep learning.

The exponential growth of legal documents in Ethiopia has created an urgent need for efficient and accurate automated classification systems tailored ...