Background Research in embodied artificial intelligence (AI) has increasing clinical
relevance for therapeutic applications in mental health services. With innovations ranging …

Background Machine learning systems are part of the field of artificial intelligence that
automatically learn models from data to make better decisions. Natural language processing …

Abstract Background The application of Big Data analytics in healthcare has immense
potential for improving the quality of care, reducing waste and error, and reducing the cost of …

When put into practice in the real world, predictive maintenance presents a set of challenges
for fault detection and prognosis that are often overlooked in studies validated with data from …

The majority of mental health disorders remain untreated. Many limitations of traditional
psychological interventions such as limited availability of evidence-based interventions and …

Background Only a few telemedicine applications have made their way into regular care.
One reason is the lack of acceptance of telemedicine by potential end users. Objective The …

An artificially intelligent computer program can now diagnose skin cancer more accurately
than a board-certified dermatologist. 1 Better yet, the program can do it faster and more …

This paper presents a critical review of key ethical issues raised by the emergence of mental
health chatbots. Chatbots use varying degrees of artificial intelligence and are increasingly …

Background: The use of conversational agent interventions (including chatbots and robots)
in mental health is growing at a fast pace. Recent existing reviews have focused exclusively …

Health care is shifting toward become proactive according to the concept of P5 medicine–a
predictive, personalized, preventive, participatory and precision discipline. This patient …