Prescriptions

Research on interpretable machine learning modeling and spatial prediction of cross-landform landslide disaster mechanism: A case study of Shaanxi Province.

The differential understanding of the landslidetriggering mechanisms across various geomorphic units is vital for enhancing regional disaster prevention. This study investigates the Loess Plateau area in northern Shaanxi and the Qinba Mountain Area in southern Shaanxi as the study areas, and constructs a 15dimensional evaluation factor system covering topography, geology, vegetation, and human act...

DeepDRP: Dose-response predictions of drug pairs using deep learning based on data-driven feature representation and dose-response curve characteristics.

Combination therapies have become a cornerstone of modern medicine, offering improved treatment outcomes and reduced side effects compared to monotherapies. However, the efficacy and safety of drug combinations depend heavily on the specific doses of each component, making the optimization of dosing regimens a crucial yet challenging task. Despite the importance of dose optimization, few computati...

Validation of a machine learning model for predicting early deterioration in the emergency department.

Early recognition of patients at risk for deterioration in the emergency department (ED) is critical for patient safety. Traditional early warning sco...

IHM-DDI: Integrating High-order Interaction Topology and Morgan Fingerprint Features for Drug-Drug Interaction Prediction.

Drug-drug Interaction (DDI) prediction is crucial in pharmacology and clinical applications. Conventional methods remain constrained by single-view pa...

From Mood Episodes to Digital Signatures: Passive and Active Phenotyping of Bipolar Disorder Over Time.

BACKGROUND: Digital phenotyping has emerged as a promising approach to capture real-time behavioral and physiological data in individuals with bipolar...

Artificial Intelligence for Regulatory Evidence: A Systematic Document Analysis of European Medicines Agency Regulatory Advice and Public Reports.

Artificial intelligence (AI) is receiving increasing attention across the entire lifecycle of medicines, from early development to postauthorization u...

Clinical Context Variables Collectively Rival Model Choice in Embedding-Based Retrieval: Multi-Corpus Benchmark Study.

BACKGROUND: Retrieval-augmented generation (RAG) systems increasingly support clinical decision-making by grounding large language model outputs in ve...

Health AI research capacity and equity-adjusted patient value in 27 European Union countries: an ecological panel study, 2011-2024.

BACKGROUND: Investments in health artificial intelligence (AI) are accelerating across European Union member states, yet evidence linking national AI ...

Divergent neuropsychiatric and systemic toxicity profiles of abemaciclib and palbociclib: a triangulation study integrating pharmacovigilance, genetic epidemiology, and multi-omics profiling.

Cyclin-dependent kinase 4/6 inhibitors improve outcomes in hormone receptor-positive, human epidermal growth factor receptor 2-negative advanced breas...

Towards structure-aware surrogate modeling: explicit region interaction improves knee contact stress prediction in young men.

Knee contact-stress hotspots are closely linked to meniscal/cartilage injury risk. Still, high-fidelity subject-specific FEA is too computationally ex...

Photophysics and complexation of indolic compounds: the effect of intra-annular and extra-annular substitution.

In this work, substitution-dependent modulation of ground- and excited-state properties is examined for intra-annular aza-substituted indoles (indazol...

Deciphering spatial-temporal mechanisms of PD-1 blockade resistance via biologically informed machine learning.

Immune checkpoint inhibitors (ICIs), especially PD-1/PD-L1 blockade, have transformed cancer therapy; yet objective response rates to anti-PD-(L)1 mon...

A Lightweight LSTM-Transformer Fusion Architecture for Real-Time Sepsis Mortality Prediction.

BackgroundAccurate prediction of short-term mortality in sepsis patients is critical for timely clinical decision-making. However, existing deep learn...

SelfBlending: Artificial Intelligence-driven Augmentation with Hand Interactions for Seamless Reality Blending in Virtual Environments.

Accessing real-world objects during immersive virtual reality (VR) experiences remains challenging, as current cross-reality systems often rely on pre...

Evaluating the Potential Impact of AI on Urinary Tract Infection Diagnosis in the Emergency Department Across Demographic Groups: Retrospective Cohort Study.

BACKGROUND: Urinary tract infection (UTI) is a common emergency department (ED) presentation but can be challenging to diagnose; both overdiagnosis an...

S-MEOD: A Novel Evaluation Metric for Frame-Based Medical Object Detection.

Traditional metrics such as precision, recall, mean Average Precision (mAP), and F-score are widely used to evaluate object detection models. However,...

Machine learning-based unified models for predicting drug clearance from pharmacokinetic animal and study design variables.

Clearance (CL) is a primary pharmacokinetic (PK) parameter crucial to determine how quickly a drug is eliminated from the body, which guides the appro...

Artificial intelligence in nutritional assessment and decision making.

PURPOSE OF THE REVIEW: Artificial intelligence (AI) has become an non contourable tool in clinical nutrition practice. This review proposes to discuss...

Learning Drug Synergy through Environment-Conditioned Feature Modulation.

MOTIVATION: Drug combinations are crucial for overcoming resistance in cancer therapy. Although deep learning has achieved strong performance in syner...

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...