Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 101 to 110 of 234,208 articles

Assessing the Potential Cumulative Effects of Longitudinal Interventions for Depression and Deviant Peer Association on Academic Achievement: a Causal Inference Approach.

Prevention science : the official journal of the Society for Prevention Research
In various studies, depressive symptoms, deviant peer association, and academic achievement appear to be reciprocally and cumulatively related across the transition from childhood to adolescence. This study asks a hypothetical question: how much woul... read more 

Immediate Hemodynamic Effects of Pulmonary Artery Flow Restrictors in Univentricular Circulation: Hypothesis-Generating Insights from High-Fidelity Physiologic Streaming Data Using Machine-Learning.

Pediatric cardiology
Hypoplastic left heart syndrome has been historically palliated with the surgical Norwood or hybrid procedures. Transcatheter placement of pulmonary flow restrictors (PFR) with prostaglandin to maintain an unobstructed ductus arteriosus has emerged a... read more 

A multi-stage multimodal learning model for functional outcomes prediction in acute ischemic stroke.

Neuroradiology
Predicting functional outcomes in acute ischemic stroke (AIS) patients after endovascular thrombectomy (EVT) remains challenging due to the complex and dynamic nature of disease progression. Existing methods typically rely on single-stage imaging or ... read more 

Microalgae-based removal and biodegradation of antibiotics: mechanisms, synergistic consortia, and engineering prospects.

Biodegradation
Antibiotic pollution in aquatic environments drives the spread of resistance genes and threatens ecosystem health. Microalgae offer a dual-function platform that both senses antibiotic stress and actively removes these contaminants. This review synth... read more 

UC-DiffuMambaNet: dual-scale state propagation and window attention for ordinal Mayo endoscopic grading.

Medical & biological engineering & computing
Automated four-grade Mayo Endoscopic Score (MES) classification is challenging because inflammatory severity depends not only on subtle local mucosal changes, but also on the collective spatial pattern of abnormalities that may be separated across th... read more 

Tissue-specific antibacterial and anti-biofilm activities of Penthorum chinense Pursh: integration of metabolomics and Random Forest machine learning.

Natural product research
Penthorum chinense Pursh is a traditional medicinal and edible plant rich in flavonoids and complex polyphenols. Evaluating its aqueous extracts against foodborne pathogens via biomass assay, microplate spread tests and scanning electron microscopy r... read more 

Relationship extraction for adverse drug events in clinical notes using large language models: a retrospective cross-sectional study.

EBioMedicine
BACKGROUND: Adverse drug events (ADEs) are a critical indicator of patient safety but are often documented only in free-text clinical notes. The potential of recent advances in natural language processing (NLP), particularly generative large language... read more 

Accuracy of soft tissue profile predictions using WebCeph and Dolphin software in non-growing skeletal Class II cases treated with upper premolar extractions: A retrospective comparative study.

International orthodontics
INTRODUCTION: Aesthetic outcomes are a primary concern for adult orthodontic patients. Clinicians often rely on soft tissue simulation software, such as Dolphin Imaging (D-Tech) and WebCeph (D-Tech), to manage patient expectations. This study aimed t... read more 

Optimized Deep Knowledge Distillation Framework for Large-Scale Virus-Host Protein Interaction Prediction.

Protein and peptide letters
BACKGROUND: In a rapidly evolving viral landscape, understanding virus-host protein interactions (VHPIs) is essential to elucidate viral infection mechanisms and support the development of effective therapeutic strategies. Accurate computational Pred... read more 

A Mechanistic Learning Framework for Breast Cancer Relapse Prediction.

Mathematical biosciences
Breast cancer recurrence is thought to arise, at least in part, from disseminated tumour cells (DTCs) that may seed distant organs prior to or during surgery, persist in a dormant state for years to decades, and eventually resume proliferation to for... read more