Objective Our objective was to review the characteristics, current applications, and
evaluation measures of conversational agents with unconstrained natural language input …

The incorporation of data analytics in the healthcare industry has made significant progress,
driven by the demand for efficient and effective big data analytics solutions. Knowledge …

This editorial aims to contribute to the current debate about the quality of studies that apply
machine learning (ML) methodologies to medical data to extract value from them and …

Background The personalization of conversational agents with natural language user
interfaces is seeing increasing use in health care applications, sha** the content …

Background Electronic health records (EHRs) are increasingly implemented internationally,
whereas digital sharing of EHRs with service users (SUs) is a relatively new practice …

Machine learning algorithms are being used to screen and diagnose disease, prognosticate
and predict therapeutic responses. Hundreds of new algorithms are being developed, but …

LACK OF INTEGRATION AS A BARRIER TO USE Clinical risk prediction models have clear
potential to influence clinical decision-making and enhance the quality of care delivered to …

Background Jupyter notebooks facilitate the bundling of executable code with its
documentation and output in one interactive environment, and they represent a popular …

Background Machine learning (ML) is increasingly used in research for subtype definition
and risk prediction, particularly in cardiovascular diseases. No existing ML models are …

Dish names and dish images can be widely found online, providing consumers with
important information. Meanwhile, implied explosion (ie, the perception of explosion induced …