Prescriptions

FCM vectorization for Twitter sentimental analysis using multi stacked BiLSTM.

Twitter data analysis gives valuable insights into various aspects of society, such as consumer opinions, political sentiments, brand reputation, and more. This information can help businesses and organizations make informed decisions, track the success of marketing campaigns, and identify emerging trends. Additionally, Twitter data analysis can also aid in research fields such as social sciences ...

Machine learning model for multi-factor risk prediction in airport construction under non-stop operations.

Airport construction under non-stop operations presents unique safety challenges due to complex multi-factor interactions that traditional qualitative methods cannot adequately address. To address this, a study was conducted on 412 construction events (comprising 103 risk incidents and 309 routine events) at a major international hub airport between 2019 and 2024. First, a risk factor system encom...

An artificial intelligence model for accurate drug-target affinity prediction in medicinal chemistry.

Predicting Drug-Target Affinity (DTA) with high fidelity is critical for accelerating hit-to-lead optimization and understanding mechanism of action. ...

Implementing drug data exclusivity in China: A comparative analysis with global practices.

This article provides a comprehensive overview and comparative analysis of China's forthcoming drug data exclusivity system, contextualizing it within...

Medication adherence among older adults: Current practices and prospects for AI integration.

Poor medication adherence is one of the leading causes for health problems among older adults in the United States. This paper examines older adults' ...

The Motion is the Message: Evaluating Motion Tracking Quality for VR Avatars.

Motion tracking to project users into embodied virtual reality (VR) as avatars is an essential application of real-time computer graphics. Most curren...

Machine learning in the prediction of liver iron concentration and iron chelation therapy adjustment.

OBJECTIVES: Iron chelation therapy titration is managed by hematologists who monitor iron levels and adjust medication dosages to achieve patient outc...

RxPairEvid and GraphFusion: Multimodal pharmacovigilance and mechanistic knowledge-graph evidence for drug-drug interaction prediction.

Drug-drug interactions (DDIs) are a major cause of preventable adverse drug reactions, yet experimental screening cannot keep pace with the growing nu...

Using natural language processing to assess MDD psychotherapy patterns among Veterans Affairs patients with suicide risk.

Major depressive disorder (MDD) is a leading risk factor for suicide. Within the US Department of Veterans Affairs (VA), psychotherapy is widely used ...

Temporal Knowledge Discovery in Drug-Resistant Tuberculosis: A Decade-Long Machine Learning Analysis From Egyptian Clinical Data.

BACKGROUND: Advanced predictive tools are required due to the worldwide persistence of tuberculosis (TB) and the growing threat of multidrug-resistant...

Focused Ultrasound-activated Extracellular Vesicles-nanoparticle Hybrids for Targeted Brain Drug Delivery: Engineering Strategies and Translational Outlook.

A revolutionary method for targeted neurotherapeutics is focused ultrasound (FUS)-mediated blood-brain barrier (BBB) regulation. In order to enable co...

Clinical and immunological significance of FOXO1 as a biomarker of improved response to immune checkpoint plus tyrosine kinase inhibitor therapy in metastatic renal cell carcinoma.

BACKGROUND: Predicting response to immune checkpoint inhibitor plus tyrosine kinase inhibitor (IO+TKI) therapy in metastatic renal cell carcinoma (mRC...

Deciphering risk factors for severe postherpetic neuralgia in patients with herpes zoster: an interpretable machine learning approach.

INTRODUCTION: Postherpetic neuralgia (PHN) is a common complication of herpes zoster (HZ). This study aimed to use a large real-world electronic medic...

Machine learning-driven multidimensional tea profiling from a single SERS spectrum: toward practical application.

Multidimensional tea profiling is crucial for consumer experience, brand reputation, and market integrity. Here, we introduce a rapid and systematic s...

An Intelligent Interactive Management Platform for Rheumatoid Arthritis Care: Real-World Observational Study.

BACKGROUND: Effective postdischarge management is essential for maintaining disease control and improving long-term outcomes in rheumatoid arthritis (...

Machine-Learned Extrapolation of Quantum Mechanical Energies in Implicit Solvent from Short to Long Oligopeptides.

Is it possible to obtain a sufficiently accurate quantum mechanical (QM) energy of an arbitrary oligopeptide structure in an implicit solvent within a...

Polymer Drug Conjugate: A Revolution in Drug Delivery.

Polymer-drug conjugates (PDCs) represent a remarkable advancement in modern medicine, leveraging the physicochemical properties of polymers to enhance...

GATv2-TransDTI: A graph and sequence hybrid model for fine-grained drug-target interaction prediction.

Accurately predicting drug-target interaction (DTI) is critical for drug discovery and development. Existing methods typically rely on the atomic stru...

Interpretable deep learning with pharmacogenomics predicts myocardial infarction in angiotensin receptor blocker treated hypertension.

OBJECTIVE: A significant residual risk of myocardial infarction (MI) persists in hypertensive patients treated with angiotensin receptor blockers (ARB...

Isotropic and Strain-Insensitive Cellulosic Triboelectric Materials Enabled by the Hofmeister Effect.

Achieving high-fidelity tactile sensing under dynamic deformation is a key bottleneck for the practical application of flexible electronics. However, ...