AIMC Topic: Advance Directives

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Natural Language Processing to Identify Home Health Care Patients at Risk for Becoming Incapacitated With No Evident Advance Directives or Surrogates.

Journal of the American Medical Directors Association May 14, 2024
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...
Male Middle Aged Natural Language Processing Aged, 80 and over Cross-Sectional Studies Humans New York City Algorithms Advance Directives Mental Competency Female Advance Care Planning Aged Home Care Services Electronic Health Records
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Artificial intelligence and mental capacity legislation: Opening Pandora's modem.

International journal of law and psychiatry Apr 4, 2024
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...
Humans Artificial Intelligence Decision Making Advance Directives Ireland Mental Competency
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Bolstering Advance Care Planning Measurement Using Natural Language Processing.

Journal of palliative medicine Feb 6, 2024
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...
Electronic Health Records Natural Language Processing Advance Care Planning Humans Advance Directives Quality Improvement Documentation
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Artificial intelligence paternalism.

Journal of medical ethics Jan 20, 2023
Paternalism Humans Personal Autonomy Advance Directives Artificial Intelligence
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Ethics of the algorithmic prediction of goal of care preferences: from theory to practice.

Journal of medical ethics Nov 8, 2022
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...
Advance Directives Goals Patient Preference Artificial Intelligence Ethics, Medical Humans
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When proxy-driven learning is no better than random: The consequences of representational incompleteness.

PloS one Jul 13, 2022
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...
Humans Machine Learning Advance Directives Reinforcement, Psychology Proxy
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Using natural language processing to identify acute care patients who lack advance directives, decisional capacity, and surrogate decision makers.

PloS one Jul 11, 2022
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...
Decision Making Natural Language Processing Advance Directives Critical Care Electronic Health Records Humans Adult Male Algorithms
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Using natural language processing to provide personalized learning opportunities from trainee clinical notes.

Journal of biomedical informatics Jun 10, 2015
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...
Clinical Competence Academic Medical Centers Advance Directives User-Computer Interface Electronic Health Records Clinical Clerkship Natural Language Processing Education, Medical Educational Measurement Geriatrics Hospitals, Veterans Automation Outcome Assessment, Health Care Students, Medical Tennessee Algorithms Reproducibility of Results Middle Aged Humans Learning Mental Disorders Aged Software
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