Latest AI and machine learning research in refractive surgery for healthcare professionals.
The relationship between structural and functional damage in glaucoma, the structure-function relationship, forms the cornerstone of disease assessment, monitoring, and prognosis. We provide an updated synthesis of current knowledge on the structure-function relationship, emphasizing recent advances in imaging, analytical methodologies, and artificial intelligence (AI)-driven modelling. we summari...
The Expected Pass Turnovers (xPT) model advances turnover probability quantification in professional football, but the inclusion of post-pass descriptive features such as ball speed and distance moved introduces temporal leakage and limits real-time tactical utility. This study compares the original xPT framework with leakage-corrected alternatives across four modeling approaches: mixed-effects lo...
BACKGROUND: Ubiquitination is a highly dynamic post-translational modification that plays central roles in protein homeostasis, signal transduction, i...
PURPOSE: To develop and validate machine learning models to predict post-tonsillectomy hemorrhage. METHODS: This was a machine learning analysis of a ...
Organ transplantation remains a gold-standard intervention for numerous end-stage organ failure diseases. However, allograft rejection is still a barr...
Recurrent acute care visits are a common yet preventable outcome for many children with asthma. Machine learning (ML) applied to electronic medical re...
Using publicly accessible Reddit posts, we developed a manually annotated dataset for traditional and aspect-based sentiment analysis (ABSA) of cannab...
STUDY OBJECTIVE: To compare the quality of AI-generated responses to gynecologic post-operative questions with educational materials published by prof...
PURPOSE: To investigate the effect of cataracts on a deep learning (DL) model for cardiovascular disease (CVD) risk prediction. METHODS: This retrospe...
BackgroundPost-stroke cognitive impairment (PSCI) is a major vascular contributor to dementia, significantly impacting long-term recovery and quality ...
Epilepsy surgery in language areas is challenged by the intricacies of presurgical workup and surgical planning. In recent decades, the view of langua...
Accurate estimation of the Post-Mortem Interval (PMI) and Post-Mortem Submersion Interval (PMSI) remains a persistent challenge in forensic science, e...
AIM: To identify and differentiate workload patterns across shifts and to provide evidence for optimizing nursing workforce allocation in emergency de...
OBJECTIVES: Chat Generative Pretrained Transformer (ChatGPT) is a widely adopted tool that can provide immediate parenting guidance. The aim of this s...
BACKGROUND AND OBJECTIVE: Neoadjuvant immune-checkpoint inhibitors (ICIs) in muscle-invasive bladder cancer (MIBC) were tested in patient's ineligible...
Artificial intelligence is expanding rapidly in cardiovascular medicine, but its value in internal medicine depends less on raw model performance than...
Accurate assessment of lymph node metastasis (LNM) following neoadjuvant chemoradiotherapy (nCRT) presents a significant clinical challenge and is ess...
Healthcare IoT systems increasingly rely on interconnected, resource-constrained devices that are vulnerable to both classical and emerging quantum-en...
The post-intervention effects of non-invasive neuromodulation techniques are critical for their translational potential in neurorehabilitation and dep...
Heart failure (HF) following myocardial infarction (MI) remains a major threat to health worldwide. While transcriptomics has revealed numerous genes ...