AIMC Topic: Attitude of Health Personnel

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Does AI explainability affect physicians' intention to use AI?

International journal of medical informatics
BACKGROUND: Artificial Intelligence (AI) is increasingly being developed to support clinical decisions for better health service quality, but the adoption of AI in hospitals is not as popular as expected. A possible reason is that the unclear AI expl...

How robots impact nurses' time pressure and turnover intention: A two-wave study.

Journal of nursing management
AIMS: To examine the relationships among effort ensuring robots' smooth operation (EERSO), time pressure, missed care, and nurses' turnover intention, and how robot performance moderates such relations.

Artificial intelligence in paediatric radiology: international survey of health care professionals' opinions.

Pediatric radiology
BACKGROUND: The nature of paediatric radiology work poses several challenges for developing and implementing artificial intelligence (AI) tools, but opinions of those working in the field are currently unknown.

Role of Robotics and Artificial Intelligence in Oral Health and Preventive Dentistry - Knowledge, Perception and Attitude of Dentists.

Oral health & preventive dentistry
PURPOSE: To assess the knowledge, attitude and perception of dentists (dental students, dental school graduates/interns, postgraduate dentists) of the role of robotics (R) and artificial intelligence (AI) in oral health and preventive dentistry. The ...

Understanding providers' attitudes and key concerns toward incorporating CVD risk prediction into clinical practice: a qualitative study.

BMC health services research
BACKGROUND: Although risk prediction has become an integral part of clinical practice guidelines for cardiovascular disease (CVD) prevention, multiple studies have shown that patients' risk still plays almost no role in clinical decision-making. Beca...

Quantitating the art and science of esthetic clinical success.

Journal of the World federation of orthodontists
BACKGROUND: Beginning with the biobehavioral bases of esthetic experiences, this article presents a quantitative analytic review of the motives and methods of providers and consumers of orthodontic treatment.