Prescriptions

Analytic Misjudgment of Drug Safety Evidence and Causality: From the Prosecutor's Fallacy and Simpson's Paradox to Artificial Intelligence.

Drug safety assessment, particularly in the post-marketing setting, is especially vulnerable to analytic misjudgment because it relies on heterogeneous evidence streams, incomplete data, infrequent events, and decisions made under substantial uncertainty. Recurring sources of error include misinterpretation of conditional probabilities, conflation of association with causation, inappropriate denom...

Machine learning prediction of childhood nephrotic syndrome outcomes.

BACKGROUND: Children with steroid-resistant, frequently relapsing, and steroid-dependent nephrotic syndrome experience high disease and treatment-related morbidity. There are few prediction models for childhood nephrotic syndrome outcomes. Our aim was to develop and internally validate outcome prediction models, using machine learning methods. METHODS: We analyzed data from Insight into Nephrotic ...

Metapath-guided transfer learning with clinical validation for identifying herb-drug interactions.

BACKGROUND: Drug co-administration can alter metabolism and cause clinically important pharmacokinetic interactions. Herb-drug interactions (HDIs) are...

Transcending Structural Dependencies: A Tunable Mass Spectrometry-Driven Machine Learning Framework for Genotoxicity Prediction.

The escalating global challenge of genotoxic compounds (GCs) in environmental, pharmaceutical, and food contexts necessitates analytical approaches th...

Patient Cognitive Bias in Large Language Model-Supported Health Consultations: Simulation-Based Comparative Study.

BACKGROUND: Large language models (LLMs) are increasingly used by patients for health information and preliminary medical advice. In patient-facing co...

Oral and Maxillofacial Surgery research hotspots and emerging trends in 2025: A targeted bibliometric analysis.

OBJECTIVES: To perform a targeted bibliometric analysis of the Oral and Maxillofacial Surgery (OMFS) literature from 2025 to map its current intellect...

Development and prospective evaluation of a real-time deep learning model for inpatient hypoglycemia prediction.

Inpatient hypoglycemia is associated with increased morbidity, mortality, length of stay, and healthcare costs, yet current management remains reactiv...

Transforming hemodialysis care: a tripartite collaboration model among medical staff, AI agents, and robots.

Hemodialysis demand is rising as populations age and the chronic kidney disease burden increases, yet dialysis units face persistent workforce constra...

Peripheral and central immune features in insomnia: Integrative bulk and single-cell transcriptomic analyses reveal core hub genes and candidate compounds.

Insomnia is closely associated with immune dysregulation, yet the overall pattern of peripheral-central immune disequilibrium and its underlying molec...

Identifying the relationship between exosome genes and breast cancer risk using bioinformatics and machine learning methods.

BACKGROUND: Breast cancer (BC) is the most prevalent cancer among women globally, with a high mortality rate. The treatment and prevention of this dis...

Performance evaluation of deep learning based YOLOv5 and YOLOv8 models for real time breast cancer detection in mammographic images.

Breast cancer detection remains a significant challenge in medical diagnostics. Traditional diagnostic methods are time-consuming, unable to detect co...

Enhancing Cross-scale Feature Mutual Information via Heterogeneous Graph Contrastive Learning for Drug-Target Binding Affinity Prediction.

Predicting drug-target binding affinity is a crucial step in drug discovery, with the aim of estimating the strength of interactions between unknown d...

Computer-Interpretable Domain Knowledge for Drug-Induced Acute Kidney Injury: a Knowledge Graph Approach.

In this study, a Knowledge Graph (KG) for Drug-Induced Acute Kidney Injury (DAKI) was developed to provide structured and standardized knowledge about...

Machine Learning-Guided Predictive Modeling and Optimization of Polyamide-Based Thin-Film Nanocomposite Reverse Osmosis Membranes.

The growing scarcity of global freshwater resources, coupled with steady advancements in seawater desalination technology, has made the development of...

Transforming mRNA drug design with AI: From UTR and codon optimization to coordinated design.

BACKGROUND: The design of mRNA drugs involves a complex and high-dimensional optimization of sequence elements to balance stability, translation effic...

Comparing supervised machine learning and large language models in title-abstract screening.

BACKGROUND: Systematic reviews require reviewers to decide on the eligibility of large numbers of articles derived from database searches. To accelera...

Individual identification of dairy cows with occluded camera views using open-set contrastive learning model.

This study aims to perform individual identification of dairy cows in freestall barns using computer vision techniques under challenging visual condit...

Generalizing Drug-Drug Interaction Risk Prediction to Chemically Novel Compounds with Bilinear Interaction Learning and Calibrated Hybrid Inference.

Reliable drug-drug interaction (DDI) prediction is essential for polypharmacy safety and for prioritizing risky combinations during early-stage drug d...

Code-free automated machine learning for OCT-based classification of vitreoretinal interface diseases.

BACKGROUND: Differentiation of vitreoretinal interface disorders on optical coherence tomography (OCT) relies on expert interpretation and can be chal...

Using Computational Intelligence to Connect Data and Drug Design in Medicinal Chemistry: A Review.

The landscape of drug discovery is being rapidly transformed by the integration of computational intelligence (CI) techniques with big data resources ...