AIMC Topic: Palliative Care
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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...
Machine learning model for prediction of palliative care phases in patients with advanced cancer: a retrospective study.
BMC palliative care
May 24, 2025
BACKGROUND: Developing an accurate predictive model for palliative care phases is crucial for improving cancer patient management, enabling healthcare providers to identify those in need of specific care plans and streamlining decision-making process...
Lexical associations can characterize clinical documentation trends related to palliative care and metastatic cancer.
Scientific reports
May 18, 2025
Palliative care is known to improve quality of life in advanced cancer. Natural language processing offers insights to how documentation around palliative care in relation to metastatic cancer has changed. We analyzed inpatient clinical notes using u...
Multidisciplinary clinician perceptions on utility of a machine learning tool (ALERT) to predict 6-month mortality and improve end-of-life outcomes for advanced cancer patients.
Cancer medicine
Mar 1, 2025
BACKGROUND: There are significant disparities in outcomes at the end-of-life (EOL) for minoritized patients with advanced cancer, with most dying without a documented serious illness conversation (SIC). This study aims to assess clinician perceptions...
Using voice recognition and machine learning techniques for detecting patient-reported outcomes from conversational voice in palliative care patients.
Japan journal of nursing science : JJNS
Jan 1, 2025
AIM: Patient-reported outcome measures (PROMs) are increasingly used in palliative care to evaluate patients' symptoms and conditions. Healthcare providers often collect PROMs through conversations. However, the manual entry of these data into electr...
A prospectively deployed deep learning-enabled automated quality assurance tool for oncological palliative spine radiation therapy.
The Lancet. Digital health
Jan 1, 2025
BACKGROUND: Palliative spine radiation therapy is prone to treatment at the wrong anatomic level. We developed a fully automated deep learning-based spine-targeting quality assurance system (DL-SpiQA) for detecting treatment at the wrong anatomic lev...
Harnessing Natural Language Processing to Assess Quality of End-of-Life Care for Children With Cancer.
JCO clinical cancer informatics
Sep 1, 2024
PURPOSE: Data on end-of-life care (EOLC) quality, assessed through evidence-based quality measures (QMs), are difficult to obtain. Natural language processing (NLP) enables efficient quality measurement and is not yet used for children with serious i...
Assessment of readability, reliability, and quality of ChatGPT®, BARD®, Gemini®, Copilot®, Perplexity® responses on palliative care.
Medicine
Aug 16, 2024
There is no study that comprehensively evaluates data on the readability and quality of "palliative care" information provided by artificial intelligence (AI) chatbots ChatGPT®, Bard®, Gemini®, Copilot®, Perplexity®. Our study is an observational and...
Machine Learning-Based Prediction of 1-Year Survival Using Subjective and Objective Parameters in Patients With Cancer.
JCO clinical cancer informatics
Aug 1, 2024
PURPOSE: Palliative care is recommended for patients with cancer with a life expectancy of <12 months. Machine learning (ML) techniques can help in predicting survival outcomes among patients with cancer and may help distinguish who benefits the most...
Using Generative AI to Translate Administrative Claims Data into Narrative Summaries for Palliative Care Needs Assessment: A Case Study.
Studies in health technology and informatics
Jul 24, 2024
Community-based palliative care is a useful, but underutilized service to support seriously ill older adults to remain safely at home and improve quality of life. Clinical decision support tools can assist palliative care need assessments if presente...
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