OBJECTIVE: Assessment of medical trainee learning through pre-defined competencies is now commonplace in schools of medicine. We describe a novel electronic advisor system using natural language processing (NLP) to identify two geriatric medicine com...
Machine learning is widely used for personalisation, that is, to tune systems with the aim of adapting their behaviour to the responses of humans. This tuning relies on quantified features that capture the human actions, and also on objective functio...
The prevalence of patients who are Incapacitated with No Evident Advance Directives or Surrogates (INEADS) remains unknown because such data are not routinely captured in structured electronic health records. This study sought to develop and validate...
Artificial intelligence (AI) systems are quickly gaining ground in healthcare and clinical decision-making. However, it is still unclear in what way AI can or should support decision-making that is based on incapacitated patients' values and goals of...
Despite its growth as a clinical activity and research topic, the complex dynamic nature of advance care planning (ACP) has posed serious challenges for researchers hoping to quantitatively measure it. Methods for measurement have traditionally depen...
International journal of law and psychiatry
38579525
People with impaired decision-making capacity enjoy the same rights to access technology as people with full capacity. Our paper looks at realising this right in the specific contexts of artificial intelligence (AI) and mental capacity legislation. I...
Journal of the American Medical Directors Association
38754475
OBJECTIVES: Home health care patients who are at risk for becoming Incapacitated with No Evident Advance Directives or Surrogates (INEADS) may benefit from timely intervention to assist them with advance care planning. This study aimed to develop nat...