INTRODUCTION: Stress urinary incontinence (SUI) affects countless women worldwide. Given ChatGPT's rising ubiquity, patients may turn to the platform for SUI advice. Our objective was to evaluate the quality of clinical information about SUI from the...
OBJECTIVE: Large language models (LLMs) are gaining popularity due to their ability to communicate in a human-like manner. Their potential for science, including urology, is increasingly recognized. However, unresolved concerns regarding transparency...
BACKGROUND: Male infertility is defined as the inability of a male to achieve a pregnancy in a fertile female by the American Urological Association (AUA) and the American Society for Reproductive Medicine (ASRM). Artificial intelligence, particularl...
European journal of obstetrics, gynecology, and reproductive biology
38986272
In an epoch where digital innovation is redefining the medical landscape, electronic health records (EHRs) stand out as a pivotal transformative force. Urogynecology, a discipline anchored in intricate patient histories and meticulous follow-ups, is ...
The multidisciplinary nature of artificial intelligence (AI) has allowed for rapid growth of its application in medical imaging. Artificial intelligence algorithms can augment various imaging modalities, such as X-rays, CT, and MRI, to improve image ...
Diffusion of Innovation Theory explains how ideas or products gain momentum and diffuse (or spread) through specific populations or social systems over time. The theory analyzes primary influencers of the spread of new ideas, including the innovatio...
This research presents our application of artificial intelligence (AI) in predicting urolithiasis risk. Previous applications, including AI for stone disease, have focused on stone composition and aiding diagnostic imaging. AI applications centered a...
Among emerging AI technologies, Chat-Generative Pre-Trained Transformer (ChatGPT) emerges as a notable language model, uniquely developed through artificial intelligence research. Its proven versatility across various domains, from language translat...
We aimed to develop machine learning (ML) algorithms for the automated prediction of postoperative ureteroscopy outcomes for pediatric kidney stones based on preoperative characteristics. Data from pediatric patients who underwent ureteroscopy for ...