Prescriptions

Design and optimization of deep learning model based on multimodal data fusion for dynamic mental health assessment.

The dynamic assessment of mental health has emerged as a hotspot for study and application due to the rise in social pressure. However, onventional methods rely mostly on static scales or single-modal data, failing to fully capture multifaceted emotional and behavioral features. This study suggests a deep learning model based on multi-modal data fusion to address this problem. By combining informa...

A dual-stream deep learning architecture for business impact scoring and alert escalation.

Modern network monitoring systems generate massive volumes of telemetry data, yet most existing anomaly detection models fail to prioritize alerts according to their operational urgency and business impact. This limitation results in delayed incident responses and inefficient alert management in Network Operations Centers. To address this gap, this study proposes a Dual-Stream Predictive Alert Esc...

Disparities in severe infection risk associated with systemic lupus erythematosus: evidence from a causal forest analysis.

OBJECTIVES: Severe infections are a primary cause of morbidity and premature mortality in patients with Systemic Lupus Erythematosus (SLE). Although S...

Frailty burden and symptomatic BPH/LUTS in aging men: evidence from two nationally representative population-based studies.

BACKGROUND: The frailty index (FI) is a well-established marker of biological aging and a widely validated predictor of adverse health outcomes in old...

Prediction and mechanistic insights into drug-induced reproductive toxicity through integrated machine learning, FAERS-based signal comparison, and network toxicology analyses.

Drug-induced reproductive toxicity is a critical concern in drug safety evaluation, whereas conventional assessment methods are often constrained by h...

Additive effects of heat and volatile organic compounds co-exposure on metabolic syndrome: evidence from petrochemical workers in China.

OBJECTIVE: To investigate the independent and joint associations of heat and volatile organic compounds (VOCs) exposure with metabolic syndrome (MetS)...

Digital and AI-enabled models in pharmaceutical development and manufacturing: a regulatory-focused industry survey.

Digital and artificial intelligence (AI)-enabled tools are increasingly being applied across pharmaceutical Chemistry, Manufacturing and Controls (CMC...

Machine learning assisted spectroscopic investigation of fluorescence quenching in Hypocrellin B with magnetic nanoparticles.

The present study investigates the interaction behavior of the photosensitizer Hypocrellin B (HB) with Fe3O4 nanoparticles and Fe3O4/CdTe nanocomposit...

Machine learning driven modeling of synergistic perinatal risk profiles in early onset pediatric cerebral palsy.

AIM: To develop and evaluate machine learning (ML) models for early cerebral palsy (CP) prediction and identify synergistic perinatal risk factors in ...

Phenotyping antidepressant treatment response with deep learning in electronic health records.

Efficient, accurate phenotyping for antidepressant treatment response in electronic health records (EHRs) could facilitate precision psychiatry applic...

Week-Ahead Prediction of High-Risk Drinking Episodes Among Young Adults Using Wearable Biosignals and Psychological Vulnerabilities: Prospective Observational Machine Learning Study.

BACKGROUND: Although machine learning has increasingly been used to predict mental health symptoms and maladaptive behaviors, real-world prediction of...

Image-guided multiscale modeling of trabecular bone: lacuna-resolved stress amplification and interaction effects.

Osteocyte lacunae are ubiquitous microstructural cavities in bone that perturb local stress and strain fields, shaping the mechanical microenvironment...

Intelligent early warning model for financial risks of new energy vehicle enterprises based on deep learning.

The financial stability of new energy vehicle (NEV) firms has become a central concern amid rapid digitalization and the transition toward low-carbon ...

PregMedNet: Multifaceted maternal medication impacts on neonatal complications.

While medication use is common among pregnant women, medication safety remains insufficiently characterized because studies in pregnant women are chal...

The role of AI-assisted drug repurposing in neurological disorders: a systematic review of validation strategies, challenges and opportunities.

Neurological disorders refer to a diverse group of conditions that affect the brain, peripheral nerves, and spinal cord and impair socioemotional, cog...

Identification of FOXK1 and SEMA7A as key genes associated with m6A-related programmed cell death in diabetic retinopathy.

BACKGROUND: Diabetic retinopathy (DR), a serious microvascular complication of diabetes, has a complex pathogenic mechanism that is intricately linked...

GraphTransDTI: A novel hybrid framework combining graph transformer and CNN-BiLSTM for enhanced Drug-Protein Interaction prediction.

Drug-protein interaction (DTI) prediction is a pivotal step in the drug discovery and repurposing process, helping to minimize experimental costs and ...

Machine learning-based analysis of drug resistance mutations in Mycobacterium tuberculosis.

Tuberculosis is a deadly airborne disease caused by Mycobacterium tuberculosis. Drug-resistant tuberculosis presents significant challenges for treatm...

Automatic detection of e-cigarette screens using object detection and vision language models.

INTRODUCTION: The e-cigarette market evolves faster than regulation and enforcement. In recent years, e-cigarette manufacturers have introduced vapes ...

Therapeutic Hybrid Intelligence with Neural and Knowledge-based Expert Reasoning for SRS (THINKERS): an AI model for GBM.

BACKGROUND: Prescription dose selection for recurrent glioblastoma treated with Gamma Knife radiosurgery remains highly individualized and is largely ...