AIMC Topic: Terminal Care
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Artificial intelligence for better goals of care documentation.
BMJ supportive & palliative care
Dec 19, 2024
OBJECTIVES: Lower rates of goals of care (GOC) conversations have been observed in non-white hospitalised patients, which may contribute to racial disparities in end-of-life care. We aimed to assess how a targeted initiative to increase GOC documenta...
Machine Learning for Targeted Advance Care Planning in Cancer Patients: A Quality Improvement Study.
Journal of pain and symptom management
Sep 3, 2024
CONTEXT: Prognostication challenges contribute to delays in advance care planning (ACP) for patients with cancer near the end of life (EOL).
Bioethical aspects of artificial intelligence: COVID-19 & end of life.
Revista da Associacao Medica Brasileira (1992)
Sep 21, 2020
Integrating machine-generated mortality estimates and behavioral nudges to promote serious illness conversations for cancer patients: Design and methods for a stepped-wedge cluster randomized controlled trial.
Contemporary clinical trials
Jan 23, 2020
INTRODUCTION: Patients with cancer often receive care that is not aligned with their personal values and goals. Serious illness conversations (SICs) between clinicians and patients can help increase a patient's understanding of their prognosis, goals...
Documentation of Palliative and End-of-Life Care Process Measures Among Young Adults Who Died of Cancer: A Natural Language Processing Approach.
Journal of adolescent and young adult oncology
Aug 14, 2019
Few studies have investigated palliative and end-of-life care processes among young adults (YAs), aged 18-34 years, who died of cancer. This retrospective study used a natural language processing algorithm to identify documentation and timing of four...
Development and Validation of a Deep Learning Algorithm for Mortality Prediction in Selecting Patients With Dementia for Earlier Palliative Care Interventions.
JAMA network open
Jul 3, 2019
IMPORTANCE: Early palliative care interventions drive high-value care but currently are underused. Health care professionals face challenges in identifying patients who may benefit from palliative care.
Robotic technology for palliative and supportive care: Strengths, weaknesses, opportunities and threats.
Palliative medicine
Jun 28, 2019
BACKGROUND: Medical robots are increasingly used for a variety of applications in healthcare. Robots have mainly been used to support surgical procedures, and for a variety of assistive uses in dementia and elderly care. To date, there has been limit...
Disease Trajectories and End-of-Life Care for Dementias: Latent Topic Modeling and Trend Analysis Using Clinical Notes.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Dec 5, 2018
Despite the increasing prevalence, growing costs, and high mortality of dementia in older adults in the U.S., little is known about the course of these diseases and what care dementia patients receive in their final years of life. Using a large volum...
External validation of a proprietary risk model for 1-year mortality in community-dwelling adults aged 65 years or older.
Journal of the American Medical Informatics Association : JAMIA
Jul 1, 2025
OBJECTIVE: To examine the discrimination, calibration, and algorithmic fairness of the Epic End of Life Care Index (EOL-CI).
Needs of bereaved families of patients with cancer towards artificial intelligence in palliative care: A web-based survey.
European journal of oncology nursing : the official journal of European Oncology Nursing Society
Jun 1, 2025
PURPOSE: Artificial intelligence (AI) systems in palliative care have garnered attention and popularity in recent years. Understanding patient and family needs is crucial for developing and implementing AI systems in palliative care. Few studies in p...
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