AIMC Topic: Adult

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Advancing training effectiveness prediction in mass sport through longitudinal data: A mathematical model approach based on the Fitness-Fatigue Model.

PloS one
Despite the critical need for scientific training load assessment in mass sports, the Fitness-Fatigue Model (FFM) requires further mathematical optimization and practical output indicators. The aim of this study was to optimize the mathematical relat...

Development and application of an artificial intelligence-assisted endoscopic system for automatic and accurate diagnosis of colorectal ulcers.

International journal of colorectal disease
OBJECTIVES: Crohn's disease (CD), ulcerative colitis (UC), intestinal Behçet's disease (BD), intestinal tuberculosis (ITB), and primary intestinal lymphoma (PIL) are major intestinal disorders that frequently present with mucosal ulceration. Accurate...

Large-scale characterisation of the nasal microbiome redefines Staphylococcus aureus colonisation status.

Nature communications
Staphylococcus aureus colonises the nose in humans, with individuals defined as persistent, intermittent or non-carriers. Unlike the gut microbiome, the nasal microbiome has not been studied in large numbers of people. Here, we define the nasal micro...

Exploring Age-Related Patterns in Smartphone Keystroke Dynamics Considering Temporal Variability: Cross-Sectional Study With AI-Based Analysis.

JMIR mHealth and uHealth
BACKGROUND: Keystroke dynamics on smartphones have emerged as a promising form of passive digital biomarker. While previous studies have explored their utility in several diseases and disorders, relatively few have examined how these dynamics change ...

Radiomics-based MRI models for predicting breast cancer axillary lymph node involvement in comparison with Node-RADS: a proof-of-concept study.

European radiology experimental
BACKGROUND: Detection of axillary lymph node (LN) involvement is essential for staging breast cancer and optimizing treatment. This proof-of-concept two-center study explored the feasibility of magnetic resonance imaging (MRI) radiomics-based machine...

Deep-learning prediction of breast cancer hormone receptor status from CEM: a preliminary study.

European radiology experimental
BACKGROUND: Hormone receptor (HR) status guides breast cancer therapy. Deep learning (DL) applied to contrast-enhanced mammography (CEM) might offer a noninvasive means for HR status prediction, but class imbalance challenges model development and as...

Novel artificial intelligence model predicts the need for reduction of distal radius fractures.

European journal of orthopaedic surgery & traumatology : orthopedie traumatologie
PURPOSE: Distal radius fractures are among the most common upper extremity injuries. While convolutional neural networks (CNNs) have shown promise in fracture detection, no models have specifically addressed the need for reduction, which is a critica...

Factors influencing immediate post-angiographic occlusion outcomes in intracranial aneurysms treated with the woven endobridge device: a multi-center analysis and predictive model from the WorldWideWEB consortium.

Neurosurgical review
The Woven EndoBridge (WEB) device treats wide-necked bifurcation aneurysms, but occlusion rates vary. This study aims to identify factors associated with immediate WEB device occlusion. Data from patients treated with WEB devices across 36 sites were...

Medical students' perceptions of AI-based feedback and feedforward on communication skills in doctor-patient consultation - an acceptance study in a video-based simulation.

Medical education online
Feedback and feedforward are highly relevant in promoting students' learning. With advances in artificial intelligence (AI), new opportunities to support feedback and feedforward are emerging. However, few studies have explored how medical students p...

Development of explainable machine learning models to predict side effects in patients with rheumatoid arthritis taking methotrexate treatment: a nationwide multicentre cohort study.

BMJ open
OBJECTIVES: Methotrexate (MTX) effectively controls rheumatoid arthritis (RA) but often leads to side effects (SE) such as gastrointestinal (GI) issues, liver toxicity and bone marrow suppression. To develop clinically interpretable machine learning ...