Large language models (LLMs) can respond to free-text queries without being specifically
trained in the task in question, causing excitement and concern about their use in healthcare …

Artificial intelligence (AI) is rapidly emerging in healthcare, yet applications in surgery
remain relatively nascent. Here we review the integration of AI in the field of surgery …

The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual
Prognosis Or Diagnosis) statement was published in 2015 to provide the minimum reporting …

We evaluated the performance of a large language model called ChatGPT on the United
States Medical Licensing Exam (USMLE), which consists of three exams: Step 1, Step 2CK …

Artificial intelligence (AI) has emerged as a crucial tool in healthcare with the primary aim of
improving patient outcomes and optimizing healthcare delivery. By harnessing machine …

The personalized titration and optimization of insulin regimens for treatment of type 2
diabetes (T2D) are resource-demanding healthcare tasks. Here we propose a model-based …

Intelligent diagnosis processes rely on Artificial Intelligence (AI) techniques to provide
possible diagnoses by analyzing patient data and medical information. To make accurate …

The next generation of surgical robotics is poised to disrupt healthcare systems worldwide,
requiring new frameworks for evaluation. However, evaluation during a surgical robot's …

The use of real-world data (RWD) for generating real-world evidence (RWE) to complement
interventional clinical trial-based research is rapidly increasing. This evolving field is …

Artificial intelligence (AI) in healthcare has the potential to improve patient outcomes, but
clinician acceptance remains a critical barrier. We developed a novel decision support …