AI Medical Compendium Topic:
Delivery of Health Care

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Public views on ethical issues in healthcare artificial intelligence: protocol for a scoping review.

Systematic reviews
BACKGROUND: In recent years, innovations in artificial intelligence (AI) have led to the development of new healthcare AI (HCAI) technologies. Whilst some of these technologies show promise for improving the patient experience, ethicists have warned ...

[The effects of the deployment of artificial intelligence on the healthcare professions].

Soins; la revue de reference infirmiere
Understanding the effects of the spread of artificial intelligence and robotization on the healthcare professions must be free of prejudice. In this way, it will be possible to promote a real methodology for evaluating and supporting these transforma...

Mapping the evidence on identity processes and identity-related interventions in the smoking and physical activity domains: a scoping review protocol.

BMJ open
INTRODUCTION: Smoking and insufficient physical activity (PA), independently but especially in conjunction, often lead to disease and (premature) death. For this reason, there is need for effective smoking cessation and PA-increasing interventions. I...

Perception of the Impact of Artificial Intelligence in the Decision-Making Processes of Public Healthcare Professionals.

Journal of environmental and public health
Technologies are increasingly independent and play important roles in society. Artificial intelligence (AI) is a branch of science that can improve various environments and processes. The health sector stands out among these contexts, especially opht...

Building Process-Oriented Data Science Solutions for Real-World Healthcare.

International journal of environmental research and public health
The COVID-19 pandemic has highlighted some of the opportunities, problems and barriers facing the application of Artificial Intelligence to the medical domain. It is becoming increasingly important to determine how Artificial Intelligence will help h...

Machine learning for improving high-dimensional proxy confounder adjustment in healthcare database studies: An overview of the current literature.

Pharmacoepidemiology and drug safety
PURPOSE: Supplementing investigator-specified variables with large numbers of empirically identified features that collectively serve as 'proxies' for unspecified or unmeasured factors can often improve confounding control in studies utilizing admini...

Shifting machine learning for healthcare from development to deployment and from models to data.

Nature biomedical engineering
In the past decade, the application of machine learning (ML) to healthcare has helped drive the automation of physician tasks as well as enhancements in clinical capabilities and access to care. This progress has emphasized that, from model developme...

Adopting artificial intelligence in dental education: A model for academic leadership and innovation.

Journal of dental education
INTRODUCTION: The continual evolution of dental education, dental practice and the delivery of optimal oral health care is rooted in the practice of leadership. This paper explores opportunities and challenges facing dental education with a specific ...

Challenges to implementing artificial intelligence in healthcare: a qualitative interview study with healthcare leaders in Sweden.

BMC health services research
BACKGROUND: Artificial intelligence (AI) for healthcare presents potential solutions to some of the challenges faced by health systems around the world. However, it is well established in implementation and innovation research that novel technologies...

Incorporating artificial intelligence in medical diagnosis: A case for an invisible and (un)disruptive approach.

Journal of evaluation in clinical practice
As big data becomes more publicly accessible, artificial intelligence (AI) is increasingly available and applicable to problems around clinical decision-making. Yet the adoption of AI technology in healthcare lags well behind other industries. The ga...