The recent emergence of foundation model-based chatbots, such as ChatGPT (OpenAI, San Francisco, CA, USA), has showcased remarkable language mastery and intuitive comprehension capabilities. Despite significant efforts to identify and address the nea...
In today's digital era, hospital websites serve as crucial informational resources, providing patients with easy access to medical services. Ensuring the usability of these websites is essential, as it directly impacts users' ability to navigate and ...
The rapid growth of the healthcare industry in China has led to a significant talent gap, particularly in the areas of digital skills and management expertise. This study aims to bridge this gap by analyzing healthcare job listings using natural lang...
Heart disease is becoming more and more common in modern society because of factors like stress, inadequate diets, etc. Early identification of heart disease risk factors is essential as it allows for treatment plans that may reduce the risk of sever...
With an increased chronic disease and an ageing population, remote health monitoring is a substantial method to enhance the care of patients and decrease healthcare expenses. The Internet of Things (IoT) presents a promising solution for remote healt...
Although most physicians are interested in the use of augmented or artificial intelligence (AI) in health care, only 38% are using AI in their practices.1 Initial results from AI integrated organizations show that AI scribe programs significantly dec...
OBJECTIVES: This study aimed to systematically map the evidence and identify patterns of barriers and facilitators to clinician artificial intelligence (AI) acceptance and use across the types of AI healthcare application and levels of income of geog...
BACKGROUND: Social robots (SR), sensorimotor machines designed to interact with humans, can help to respond to the increasing demands in the health care sector. To ensure the successful use of this technology, acceptance is paramount. Generative arti...
This commentary explores the current state, challenges, and potential of artificial intelligence (AI) in health care revenue cycle management, emphasizing collaboration, data standardization, and targeted implementation to enhance adoption.
Artificial intelligence (AI) in healthcare promises transformative advancements, from enhancing diagnostics to optimizing personalized treatments. Realizing its full potential, however, requires addressing key challenges, including explainability, bi...