To investigate the potential of employing artificial intelligence (AI) -driven breast ultrasound analysis models for the classification of glandular tissue components (GTC) in dense breast tissue. A total of 1,848 healthy women with mammograms classi...
Radiological expertise develops through extensive experience in specific imaging modalities. While previous research has focused on long-term learning and neural mechanisms of expertise, the effects of short-term radiological training on resting-stat...
Interstitial cells of Cajal (ICCs) play a key role in gastrointestinal smooth muscle contractions, but their relationship with anal canal function in advanced haemorrhoidal disease (HD) remains poorly understood. This study uses deep neural network (...
OBJECTIVES: Machine learning (ML) is an emerging discipline centered around complex pattern matching and large data-based prediction modeling and can improve precision medicine healthcare. Cochlear implants (CI) are highly effective, however, outcome...
PURPOSE: To validate a deep learning (DL) framework for detecting and quantifying cystoid fluid collections (CFC) on spectral-domain optical coherence tomography (SD-OCT) in X-linked retinoschisis (XLRS) patients.
International journal of medical informatics
Apr 4, 2025
BACKGROUND: Early identification and prevention of ventilator-associated pneumonia (VAP) in patients with mechanical ventilation (MV) through reliable prediction model undergoing a rigorous and standardized process is essential for clinical decision-...
OBJECTIVE: To investigate the determinants affecting live birth outcomes in fresh embryo transfer among polycystic ovary syndrome (PCOS) patients using various machine learning (ML) algorithms and to construct predictive models, offering novel insigh...
BACKGROUND: Finding a biomarker to diagnose migraine remains a significant challenge in the headache field. Migraine patients exhibit dynamic and recurrent alterations in the brainstem-thalamo-cortical loop, including reduced thalamocortical activity...
In the artificial intelligence (AI) domain, effectively integrating deep learning (DL) technology with the content, teaching methodologies, and learning processes of music aesthetic education remains a subject worthy of in-depth exploration and discu...
There is increasing interest in using assistive robotic devices to support motor re-learning and recovery in individuals with neurological impairments. These robots aim to enhance overall motor control by providing adaptive assistance. However, using...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.