Latest AI and machine learning research in refractive surgery for healthcare professionals.
BACKGROUND: Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality worldwide. Although traditional cardiovascular risk models primarily rely on biomedical factors, socioeconomic and occupational characteristics are increasingly recognized as important correlates of cardiovascular health. However, applying machine learning to population-based survey data raises methodologic...
Artificial intelligence (AI) tools are rapidly reshaping ophthalmology by improving screening and diagnosis for diabetic retinopathy, age-related macular degeneration, glaucoma, and increasingly retina-based systemic risk assessment. This narrative review provides a comparative assessment of regulatory pathways governing ophthalmic AI and software as a medical device (SaMD) across the United State...
BACKGROUND: Against the backdrop of increasing patient volumes, rising case complexity, and physicians' limited time, AI-driven systems for anamnesis,...
Extubation failure in ICU patients is associated with poor outcomes. Existing prediction models often rely on static data, missing dynamic disease flu...
To evaluate the clinical reasoning ability of large language models (LLMs) and retrieval-augmented generation (RAG) systems in pediatric myopia manage...
BACKGROUND: Lung resection is the gold-standard treatment for early stage lung cancer, but remains associated with significant mortality, highlighting...
Stroke is one of the leading causes of disability worldwide with a disproportionately high burden in low and middle-income countries. In such countrie...
BACKGROUND: Timely detection of Parkinson's disease (PD) remains limited by reliance on in-person neurological evaluations that are often costly and g...
Lung transplantation remains the only definitive treatment for end-stage respiratory failure; however, it has substantial post-operative mortality ris...
BACKGROUND: Research on artificial intelligence (AI) and mental health has focused largely on harms at deployment, including chatbot safety, sycophanc...
OBJECTIVES: The increasing presence of artificial intelligence (AI), electronic patient-reported outcomes (ePROMs), and digital infrastructures in pal...
OBJECTIVES: Digital morphology (DM) systems assisted by artificial intelligence are increasingly being introduced into hematology laboratories; howeve...
PURPOSE: To assess the performance of GPT-5 in refractive surgery planning by comparing its recommendations with expert surgeons and reporting visual ...
BACKGROUND: The complexity and rapidly evolving nature of critical patient care in Intensive Care Units underscore the importance of the accuracy and ...
In a dual-beam super-resolution laser direct-writing lithography system, the flatness error of the motion stage during XY-plane scanning (small fluctu...
Astigmatism is a prevalent refractive error in preschool children and a leading cause of preventable early visual impairment. Conventional screening m...
BACKGROUND: Current classifications used for total knee arthroplasty (TKA) are static and fail to capture the dynamic behavior of the limb during gait...
AIM: Planning for a hospital is a complex and dynamic process, traditionally not informed by evidence. A systems thinking approach can be useful in in...
INTRODUCTION: Precise intraocular lens (IOL) positioning is critical for optimal visual outcomes in cataract surgery, particularly with advanced IOLs....