Latest AI and machine learning research in refractive surgery for healthcare professionals.
Pre-deployment validation is commonly used to establish the safety and effectiveness of clinical artificial intelligence systems, but acceptable validation performance does not guarantee stable behavior after deployment into routine clinical workflows. We conducted a longitudinal retrospective observational study of four clinically deployed AI systems operating across distinct clinical domains and...
PURPOSE: This study compared traditional statistical models with machine learning algorithms for predicting surgically induced astigmatism after cataract surgery, aiming to identify the most accurate and generalizable method among linear regression, regression trees, random forests, and neural networks. METHODS: Retrospective analysis was performed on 321 eyes (321 patients) undergoing phacoemulsi...
The exponential growth of unstructured data has presented new opportunities for leveraging computational techniques to uncover meaningful insights in ...
BACKGROUND: The early identification of early allograft dysfunction (EAD) and the long-term prediction of graft-related adverse event-free survival (G...
BACKGROUND: Large language models (LLMs) are increasingly used in health care, with emerging applications in clinical decision support and nursing edu...
This review highlights that integrating physiological, molecular, imaging, and AI-based approaches enables early and reliable detection of graft incom...
BACKGROUND: The EyeMate-SC (G-Metrics GmbH, Hanover, Germany) is a permanently implantable microsensor positioned in the suprachoroidal space for tele...
BACKGROUND: Outcome prediction models for patients with ischemic stroke after endovascular thrombectomy (EVT) demonstrated the value of including post...
BACKGROUND: Neoadjuvant therapy (NAT) is crucial for locally advanced breast cancer, but post-NAT lymph node assessment is challenging due to histolog...
BACKGROUND: Generative artificial intelligence (GenAI), particularly large language models (LLMs), is being integrated into healthcare documentation, ...
INTRODUCTION: Post COVID-19 condition (PCC) denotes the persistence of symptoms following Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)...
INTRODUCTION: On average, women now spend more than one-third of their lives in the post-reproductive period, yet menopause care across Europe remains...
BACKGROUND: Body image dissatisfaction, disordered eating, and eating disorders represent significant public health concerns; however, many affected i...
Accurate assessment of redisplacement risk in distal radius fractures during initial treatment is crucial for selecting the optimal management plan. T...
BACKGROUND: Patient perceptions influence the success of bariatric surgery and pharmacologic weight loss therapies, yet many concerns never reach prov...
Lane-change intention prediction is critical for intelligent vehicles, and driver decisions depend on the perception and processing of driving context...
BACKGROUND: Immersive virtual reality (IVR) simulation is increasingly used in nursing education to support experiential learning and the development ...
Cerebral amyloid angiopathy (CAA) commonly co-occurs with Alzheimer's disease (AD), yet the molecular changes that accompany vascular [Formula: see te...
AIM: To develop and evaluate the diagnostic accuracy of deep learning (DL) models in differentiating keratoconus (KC) from normal eyes with regular as...
BACKGROUND: Estimating the post-mortem interval (PMI) is pivotal in forensic casework, yet traditional approaches are imprecise and context-dependent....