PURPOSE OF REVIEW: Artificial Intelligence (AI) has produced a significant impact across various industries, including healthcare. In the outpatient clinic setting, AI offers promising improvements in efficiency through Chatbots, streamlined medical ...
PURPOSE: Exploring the integration of artificial intelligence in clinical settings, this study examined the feasibility of using Generative Pretrained Transformer 4 (GPT-4), a large language model, as a consultation assistant in a hand surgery outpat...
Artificial intelligence (AI) decision support systems in pediatric healthcare have a complex application background. As an AI decision support system (AI-DSS) can be costly, once applied, it is crucial to focus on its performance, interpret its succe...
IMPORTANCE: The emergence and promise of generative artificial intelligence (AI) represent a turning point for health care. Rigorous evaluation of generative AI deployment in clinical practice is needed to inform strategic decision-making.
The effective management of chronic conditions requires an approach that promotes a shift in care from the clinic to the home, improves the efficiency of health care systems, and benefits all users irrespective of their needs and preferences. Digital...
Acta radiologica (Stockholm, Sweden : 1987)
Sep 26, 2023
BACKGROUND: There have been no reports on diagnostic performance of deep learning-based automated detection (DLAD) for thoracic diseases in real-world outpatient clinic.
Unrecognized deterioration of COVID-19 patients can lead to high morbidity and mortality. Most existing deterioration prediction models require a large number of clinical information, typically collected in hospital settings, such as medical images o...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Feb 21, 2022
. A key to a more efficient scheduling systems is to ensure appointments are designed to meet patient's needs and to design and simplify appointment scheduling less prone to error. Electronic Health Records (EHR) consist of valuable information about...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
Patient "no-shows" are missed appointments resulting in clinical inefficiencies, revenue loss, and discontinuity of care. Using secondary electronic health record (EHR) data, we used machine learning to predict patient no-shows in follow-up and new p...