Prescriptions

Multimodal machine learning and deep graph neural networks for the prediction of molecular inhibitory activity and disease associations.

Effectively integrating a variety of biological and chemical data sources is essential for the acceleration of drug discovery and precision diagnostics. Nevertheless, conventional computational methods frequently experience modality isolation, which results in their inability to simultaneously capture the intricate multi-omics regulatory landscape of diseases and the detailed electronic properties...

Participatory Digital Twins for Chronic Care: From Predictive Models to Shared Sensemaking.

Health digital twins, computational models that integrate longitudinal data, simulation, and forecasting, are increasingly proposed as tools for chronic care management. However, most current implementations are expert oriented, prioritizing technical optimization and clinical prediction while offering limited support for patient understanding, engagement, or participation. This orientation is par...

Early prediction and risk assessment of adverse drug combinations using ensemble learning.

Modern day healthcare has seen an increase in polypharmacy, which is the prescription of multiple drugs as medication to treat illnesses simultaneousl...

A Two-Stage, Semi-Supervised Deep Learning Framework for the Detection and Classification of Ambient Pollen using Evanescent Wave Scattering.

Airborne pollen, an aeroallergen, impacts human health, particularly as climate change shifts pollen dynamics, requiring accurate monitoring to suppor...

Natural language processing to enhance rheumatoid arthritis care in clinical studies: a scoping review of applications, data, approaches, challenges and future directions.

Structured claims or EMR datasets have limitations, such as lacking important clinical variables, upcoding, or potential coding errors. Unstructured d...

Development of Data-Driven Models for Just-in-Time Digital Self-Management Advice to Improve Physical Functioning in Hip and Knee Osteoarthritis: Protocol for the e-cOAch Cross-Over Study.

BACKGROUND: Clinical guidelines recommend a stepped-care strategy for patients with hip and knee osteoarthritis that begins with nonoperative approach...

Integrating experimental biology, computational methods, and artificial intelligence in anticancer drug discovery: Bridging the translational gap.

Cancer remains a leading cause of mortality globally, with the incidence projected to reach 28.4 million new cases annually by 2040. Traditional drug ...

Allosteric targeting of the ACE2 dimer interface by a medium-sized compound inhibits SARS-CoV-2 entry.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), enters host cells via intera...

Interpersonal neural synchrony in joint music-making and conversation: toward an integrative Marr-level account.

Joint music-making and conversation are two fundamental forms of human interaction. A growing number of hyperscanning studies have examined interperso...

Trends in the use of adult-specific preference-weighted health-related quality of life instruments in clinical trials over the past 50 years: a protocol for a meta-research study using deep learning-based natural language processing and large language models.

BACKGROUND: Health technology assessment bodies increasingly emphasise the importance of preference-weighted health-related quality of life (HRQoL) ev...

Green finance and technological innovation interact to shape economic growth in China.

This study investigates the direct effects and the interaction between green finance and technological innovation on China's economic growth. The empi...

Bidirectional cross-modal fusion with tensor interaction for drug-target binding prediction.

Accurate prediction of drug-target binding affinity is central to computational drug discovery, yet it remains difficult because binding is governed b...

MammoDenseSegNet: A Context-Aware Deep Learning Model for Dense Tissue Segmentation in Digital Mammograms.

Breast density is a breast cancer risk factor. The accurate quantification of breast density requires reliable segmentation of dense tissue in mammogr...

Patient Trust in AI-generated Medication Information and the Role of Clinical Pharmacists in Preventing Medication-related Safety Risks: A Cross-sectional Survey.

BACKGROUND: To assess patient trust in AI-generated medication information, examine associated behavioral safety risks, and evaluate patient expectati...

Non-linear impact mechanisms of multi-modal urban traffic on air quality: An interpretable machine learning study for sustainable policy making.

Urban air pollution, specifically Nitrogen Dioxide (NO2), presents a multifaceted challenge that is intricately coupled with the stochastic, multi-mod...

A multi-modal co-attention model for accurate drug-target interaction prediction.

Accurate prediction of drug-target interactions (DTIs) plays a crucial role in modern drug discovery and repositioning. Despite recent advances in dee...

GinkgoSense-Net: A method for characterization and real-time detection of ginkgo fruits in complex field environments.

Automatic picking of ginkgo fruits is beneficial for prolonging their freshness and ensuring quality during storage. Accurate identification of ginkgo...

Towards optimal valve prescription for transcatheter aortic valve replacement (TAVR) surgery: a machine learning approach.

Transcatheter Aortic Valve Replacement (TAVR) has emerged as a prominent, minimally invasive treatment for patients with severe aortic stenosis, a lif...

MMTF-DTI: Drug-target interaction prediction via multimodal feature extraction and dynamic fusion.

Drug-target interaction (DTI) prediction is vital for computer-aided drug discovery, yet current methods struggle with cross-domain generalization and...

Phenotyping of pulmonary arterial hypertension associated with congenital heart disease using latent class analysis: insights from a national prospective registry.

BACKGROUND: Pulmonary arterial hypertension associated with congenital heart disease (PAH-CHD) is characterized by substantial prognostic and therapeu...