The adoption of artificial intelligence (AI) algorithms is rapidly increasing in healthcare. Such
algorithms may be shaped by various factors such as social determinants of health that can …

Artificial Intelligence (AI) describes computer systems able to perform tasks that normally
require human intelligence, such as visual perception, speech recognition, decision-making …

Background: ChatGPT, an artificial intelligence-driven, pretrained, deep learning language
model, can generate natural language text in response to a given query. Its rapid growth has …

Obstructive sleep apnea (OSA) is a serious medical condition with a high prevalence,
although diagnosis remains a challenge. Existing home sleep tests may provide acceptable …

Data drift refers to differences between the data used in training a machine learning (ML)
model and that applied to the model in real-world operation. Medical ML systems can be …

Importance Given the importance of rigorous development and evaluation standards
needed of artificial intelligence (AI) models used in health care, nationwide accepted …

As the health-care industry emerges into a new era of digital health driven by cloud data
storage, distributed computing, and machine learning, health-care data have become a …

Photoplethysmography is a key sensing technology which is used in wearable devices such
as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to …

Abstract Purpose of Review Artificial intelligence (AI) has increasingly been used in
healthcare. Given the capacity of AI to handle large data and complex relationships between …

Despite major advances in artificial intelligence (AI) research for healthcare, the deployment
and adoption of AI technologies remain limited in clinical practice. This paper describes the …