Prescriptions

Development of prediction models for perioperative opioid needs in laparoscopic cholecystectomy patients: A machine-learning approach.

BACKGROUND: Changes in opioid prescribing practices have evolved, including perioperative settings. However, computerized clinical decision support systems to guide opioid prescribing remain limited. This study aimed to develop and validate prediction models for perioperative opioid needs among patients undergoing laparoscopic cholecystectomy (LC) and to create a risk-scoring tool. METHODS: This w...

Deep learning in stroke therapeutics: drug repurposing and beyond.

INTRODUCTION: Deep learning is reshaping stroke research by accelerating drug repurposing amid heterogeneous pathology, narrow therapeutic windows, and poor translation. This review highlights current therapeutic challenges and emerging DL applications from preclinical modeling to clinical decision support. AREA COVERED: This narrative review focuses on the application of DL in preclinical and cli...

Attenuation-based ultra-low-dose lung computed tomography at 0.1 mSv to 0.3 mSv effective dose in children.

BACKGROUND: Radiation dose reduction is essential in paediatric lung computed tomography (CT). Advances in energy-integrating detector CT and deep-lea...

Quantifying customer sentiment for automobile brand perception analysis using machine learning on Twitter.

Social networking sites provide a platform for individuals to express their opinions publicly. Brand managers actively use these platforms to gain ins...

Fuzzy classification of sepsis subtypes and implications for trajectory and treatment.

BACKGROUND: Sepsis is common and deadly, and subtypes are proposed to guide precision treatment. However, little is known about the uncertainty in sub...

Exploring Primary and Interaction Effects of Minor Physical Anomalies: Development and Validation of Prediction Models Using Explainable Machine Learning Algorithms for Early-Onset Schizophrenia.

BACKGROUND AND HYPOTHESIS: Minor physical abnormalities (MPAs) are neurodevelopmental markers that can be traced to prenatal events and may be signifi...

Multiomics Profiling of T-cell Leukemia and Lymphoma Enables Targeted Therapeutic Discovery.

UNLABELLED: T-cell leukemias and lymphomas (TCL) form a heterogeneous group of rare and often aggressive malignancies. Because of the rarity and heter...

PANTHER Score: Protein-Affinity for Nucleic Target-binding, Hybridization, and Energy Regression.

Although protein-RNA interactions are crucial for many biological processes, predicting their binding free energies (ΔG) is a challenging task due to ...

Order-Aware Deep Learning for Drug Combination Benefit Prediction in Cancer Cell Lines.

Drug combination therapy has exhibited favorable effects in treating cancer patients, with less toxicity and adverse reactions compared to monotherapy...

Treatment Recommendations for Clinical Deterioration on the Wards: Development and Validation of Machine Learning Models.

BACKGROUND: Clinical deterioration in general ward patients is associated with increased morbidity and mortality. Early and appropriate treatments can...

Development and external validation of machine learning approaches for risk prediction of cardiovascular disease in individuals with schizophrenia: a nationwide Swedish and Danish study.

BACKGROUND: Currently available cardiovascular disease (CVD) risk prediction tools may underestimate the risk in individuals with schizophrenia. OBJEC...

A graph-based spatio-temporal framework for predicting safety-critical pedestrian-vehicle interactions at unsignalized crosswalks.

Pedestrian safety remains a critical global concern, especially in countries like India, where unsignalized crossings with limited traffic control con...

MAGED: Multimodal attentive graph learning with gene expression dynamics on knowledge graphs for TCM target prediction.

ETHNOPHARMACOLOGICAL RELEVANCE: Plants used in traditional medicine have long provided valuable clues for drug discovery, yet systematically connectin...

Properties of AgNPs stabilized with polyvinylpyrrolidone relevant to antidiabetic agents.

Type 2 diabetes mellitus (DM2) is a chronic metabolic disease. Silver nanoparticles (AgNPs) show promise in their treatment. This study assessed the p...

Segmentation and calculation of lung fibrosis in IPF mice by 2.5D UNet.

BACKGROUND: Idiopathic pulmonary fibrosis significantly threatens patient survival and remains a condition with limited effective treatment options. T...

EnsDTI: Predicting Drug-Target Interaction with Mixture-of-Experts and Confidence Assessment.

Accurately identifying drug-target interactions (DTIs) is a critical step in drug discovery. While structure-based drug design methods demonstrate imp...

Peak strain dispersion as a nonlinear mediator in HFpEF: Unraveling subtype-specific pathways via SHAP-augmented ensemble modeling.

BACKGROUND: Heart failure with preserved ejection fraction (HFpEF) represents a heterogeneous syndrome with diverse pathophysiological mechanisms and ...

A Case-Based Explainable Graph Neural Network Framework for Mechanistic Drug Repositioning.

Drug repositioning offers a cost-effective alternative to traditional drug development by identifying new uses for existing drugs. Recent advances lev...

Comparative study of 11 machine learning algorithms for predicting recurrence risk after atrial fibrillation catheter ablation based on a real-world cohort: a retrospective study.

BACKGROUND: Atrial fibrillation (AF) is the most common arrhythmia worldwide, with catheter ablation being an effective yet recurrence-prone treatment...

CADS: A Causal Inference Framework for Identifying Essential Genes to Enhance Drug Synergy Prediction.

MOTIVATION: Drug synergy is crucial for developing effective combination therapies, but traditional screening methods suffer from inefficiency and hig...