We present a comprehensive Framework for Digital Health Equity, detailing key digital
determinants of health (DDoH), to support the work of digital health tool creators in industry …

Background Digital health technologies (ie, the integration of digital technology and health
information) aim to increase the efficiency of health care delivery; they are rapidly adapting …

People supported by AI-powered decision support tools frequently overrely on the AI: they
accept an AI's suggestion even when that suggestion is wrong. Adding explanations to the …

Conversational agents powered by large language models (LLM) have increasingly been
utilized in the realm of mental well-being support. However, the implications and outcomes …

Data-driven digital health technologies have the power to transform health care. If these
tools could be sustainably delivered at scale, they might have the potential to provide …

Until now, much of the work on machine learning and health has focused on processes
inside the hospital or clinic. However, this represents only a narrow set of tasks and …

Machine learning is used increasingly in clinical care to improve diagnosis, treatment
selection, and health system efficiency. Because machine-learning models learn from …

Although cancer mortality rates declined in the United States in recent decades, some
populations experienced little benefit from advances in cancer prevention, early detection …

Background Health care systems have become increasingly more reliant on patients' ability
to navigate the digital world. However, little research has been conducted on why some …

The new coronavirus disease (COVID-19) pandemic is changing how society operates.
Environmental changes, disrupted routines, and reduced access to services and social …