Prescriptions

Causal-Inference Machine Learning for Unveiling Hydroxyl Radical Reactivity with Antibiotics in Water Purification.

Understanding hydroxyl radical (HO·) reactivity with organic pollutants is crucial for optimizing advanced oxidation processes in water purification. Machine learning (ML) models have been developed to predict HO· reactivity but often produce black-box results due to complex chemical interplay. Herein, we constructed an interpretable ML framework to unveil the intrinsic molecular factors governing...

Med-ViX-Ray: Enhancing explainable chest X-ray analysis with clinical knowledge graphs.

BACKGROUND AND OBJECTIVE: Deep learning has achieved remarkable success in chest x-ray interpretation, yet most models remain black boxes, producing accurate predictions without exposing the clinical reasoning behind them. This opacity limits trust and adoption in real-world practice. We introduce Med-ViX-Ray, a knowledge-guided and interpretable framework that integrates symbolic clinical reasoni...

The economic imperative of artificial intelligence in maternal and neonatal health: a review of evaluation benefits, frameworks, challenges, future perspectives, and limitations.

Integrating artificial intelligence (AI) into maternal and neonatal health (MNH) offers significant opportunities for enhancing patient care through a...

Study of bladder cancer detection in standard white light versus AI-supported endoscopy-01 (RAISE-01) - Development and validation of an AI-based support tool.

BACKGROUND: Diagnosis and surveillance of bladder cancer rely on white-light cystoscopy (WLC). However, this modality is operator-dependent and associ...

Relation-Centric knowledge graph generation for recommendation based on conditional diffusion model.

Recommendation actively selects information for users, yet it persistently face data sparsity and cold-start problems. The incorporation of knowledge ...

Computational Innovations in Cancer Research and How Computing is Transforming Drug Discovery and Development: A Review.

INTRODUCTION: Cancer is a major global health concern, causing millions of deaths each year due to the uncontrolled growth and spread of abnormal cell...

Epilepsy: Modern Treatment Approaches, Clinical Aspects, and Patent Status.

Epilepsy is a chronic neurological disorder causing recurrent seizures. Improved diagnosis and management, including high-resolution imaging, genetic ...

Predicting lithium-associated thyroid dysfunction through dimension reduction to establish a practical machine learning model: A retrospective multicenter study.

BACKGROUND: Thyroid dysfunction is a prevalent side effect among patients using lithium and links to refractory mood disorders. Existing predictive mo...

A machine learning framework for personalized exercise prescription based on BMI and physical fitness assessment.

Enhancing heat and mass transfer in hybrid nanofluid with gyrotactic microbes and local thermal non equlibrium effects using artificial neural network.

This study analyzes the impact of local thermal non-equilibrium on the bioconvection flow of hybrid nanofluid across a slender extending sheet contain...

Machine Learning Models for Identifying Dental Pain in Adolescents.

INTRODUCTION: This study aimed to identify dental pain using machine learning (ML) algorithms in Brazilian adolescents for public health screening pur...

InChINet: a self-supervised molecular representation learning framework leveraging SMILES and InChI.

Molecular representation, as one of the fundamental challenges in artificial intelligence-driven drug discovery, has attracted increasing attention du...

[Care for uncontrolled asthma in Germany - with focus on Magdeburg and Mannheim regions].

Description of treatment and prescription patterns among asthma patients in the regions of Magdeburg (MD) and Mannheim (MA) compared nationwide.We ana...

CFGSCDSA: Predicting circRNA-drug sensitivity associations based on collaborative feature learning and graph structure learning.

MOTIVATION: The expression of circular RNAs (circRNAs) has been shown to be strongly correlated with drug sensitivity in human cells. However, experim...

DPCNet: A dual path cross perception network for small object detection in UAV imagery.

Small object detection in unmanned aerial vehicle imagery is challenged by tiny target scales, dense layouts, and cluttered backgrounds that blur fine...

Genetic and clinical determinants of tacrolimus accumulation in early liver transplantation: evidence for a combined genotype-antibiotic effect.

BACKGROUND: Tacrolimus is a first-line immunosuppressant essential for preventing graft rejection after liver transplantation, but its narrow therapeu...

A complete blood count-based machine learning model for rapid differentiation of aplastic anemia, immune thrombocytopenia, and myelodysplastic syndromes in routine clinical practice.

BACKGROUND: Accurate differentiation of common hematologic disorders remains challenging in routine clinical practice and often requires invasive diag...

Advancing Global Drug Safety: Challenges and Future Perspectives in Pharmacovigilance.

Adverse Drug Reactions (ADRs) pose significant challenges to patient safety, healthcare systems, and public health worldwide. As the pharmaceutical la...

MSCMF-DTB: a multi-scale cross-modal fusion framework for drug-target binding prediction.

Predicting drug-target binding remains a central challenge in computational drug discovery, particularly due to the need for models that jointly captu...

Automated auditing of emergency department documentation using large language models.

INTRODUCTION: Errors in emergency department (ED) documentation can lead to patient harm and medicolegal risk, however manual document auditing is res...