Prescriptions

An explainable machine learning model for predicting high phosphorus risk in patients on maintenance hemodialysis: a multicenter retrospective study.

BACKGROUND: Hyperphosphatemia is a common complication in hemodialysis and serves as a key marker for evaluating dialysis adequacy. This study aimed to develop an interpretable machine learning (ML) model to predict the risk of hyperphosphatemia in patients undergoing maintenance hemodialysis. METHODS: Data from 718 patients receiving maintenance hemodialysis across five hemodialysis centers in Ch...

LKCAU-Net: A Large Kernel Coordinated Attention U-Net for Breast Tumors Segmentation in Ultrasound Images.

Breast cancer remains a significant health concern for women worldwide. Ultrasound imaging is widely adopted for screening due to its non-invasive and radiation-free nature. However, challenges such as low image contrast, blurred tumor boundaries, and diverse tumor morphologies severely hinder accurate segmentation. To address these issues, we propose LKCAU-Net, a novel hybrid multi-scale network ...

Two faces of drug repurposing data in machine learning-driven structure-based virtual screening supported by interaction fingerprints.

Ensemble docking is a prominent source of protein-ligand complex structures, which could be conveniently analyzed with interaction fingerprints approa...

Operationalizing AI-Assisted Polypharmacy Review in Post-Acute and Long-Term Care: A 4Ms-Based, NP-Led Workflow.

Polypharmacy in post-acute and long-term care (PA/LTC) is common and is associated with falls, delirium, hospitalization, functional decline, and mort...

Explainable detection of goldenhar syndrome using an OD-Mamba backbone for rare craniofacial disorder diagnosis.

Goldenhar Syndrome (GS) is a rare congenital craniofacial disorder characterized by asymmetrical facial deformities. It is often underdiagnosed due to...

Explainable AI for employee turnover prediction: a SHAP-based intelligent analytics approach.

Employee turnover prediction is a critical challenge in human resource management. Existing studies emphasise predictive accuracy but generally treat ...

A Unified Molecular Graph and Protein Language Model Framework for Predicting Human Drug-Hormone Receptor Interactions with Structure-Aware Validation.

Hormones regulate many essential biological processes by interacting with specific receptors that control gene expression, metabolism, growth, and imm...

Decrypting the allosteric network: multi-scale dynamics of SARS-CoV-2 main protease inhibition by Moringa oleifera flavonoids.

The SARS-CoV-2 main protease (Mpro) is a prototypical enzyme whose activity is governed by long-range allosteric communication within its dynamic stru...

Multi-scale analysis of thermal forcing of heatwaves on cyanobacterial blooms in Lake Taihu: mechanisms, spatial heterogeneity, and future projections.

Rising water temperatures and intensifying lake heatwaves (LHWs) are increasingly recognized as important drivers of cyanobacterial harmful algal bloo...

A historical journey of metabolite-protein interaction discovery: from data harmonization to AI-driven prediction.

Metabolites are life-sustaining small molecules produced by living organisms. They interact with proteins involved in metabolism, signalling, and gene...

Development of a human-artificial intelligence collaboration-based storybook series for understanding epilepsy and supporting self-management.

Epilepsy is a chronic condition that requires ongoing self-management, including medication adherence, trigger control, lifestyle regulation, and psyc...

Body composition's effect on the bone-vascular axis of osteoporosis discovered in AI-based CT analysis of COPD patients.

OBJECTIVES: This study aimed to investigate the effect of body composition on the inverse relationship between vertebral bone density (T12 BMD) and to...

Annotation-efficient weed detection using DINOv3-distilled YOLOv12.

Weed pressure causes global crop yield losses of 10-34%, while the deployment of deep learning-based weed detection systems at scale remains constrain...

Spatiotemporal self-attention network ST-GranNet for granary temperature prediction.

BACKGROUND: Food storage temperature prediction is critical for ensuring the safety of the food supply chain and reducing food waste. Traditional phys...

3DICE: Interpretable 3D Cross-Modal Learning for Drug-Target Interaction Prediction and Large-Scale Drug Discovery.

MOTIVATION: Drug-target interaction (DTI) prediction is a crucial step in modern drug discovery. Accurate and efficient predictions can substantially ...

Bioinspired Electrostatic-Field Perturbated Sensing for General Material Noncontact Perception.

Noncontact sensing is essential for smart manufacturing and safe human-machine interaction, yet existing proximity and inspection sensors are often li...

Extracting Medical Information From Unstructured Clinical Text Using Large Language Models to Enhance Health Care Interoperability: Proof-of-Concept Study.

BACKGROUND: Unstructured clinical text remains a major barrier to interoperable data reuse and large-scale secondary analysis in health care. Large la...

Informative Relational Learning for Adverse Reaction Prediction with Enhanced Generalization to Novel Drugs.

MOTIVATION: Accurate prediction of adverse drug reactions (ADRs) is essential for drug safety surveillance, and recent advances in machine learning wi...

CoAff-DTI: Fine-grained drug-target interaction prediction using pre-trained language models and affinity-guided mechanisms.

Accurate prediction of drug-target interactions (DTI) is essential for drug discovery. Despite the success of pre-trained language models (PLMs) in le...

Lipid digestion- driven drug fate as a key determinant of SNEDDS performance: Mechanistic basis of absorption and in vitro- in vivo disconnect.

Self-nanoemulsifying drug delivery systems (SNEDDS) represent a major class of lipid-based nanomedicines that are primarily utilised for the enhanceme...