Simple Summary To investigate the adoption of machine learning in palliative care research
and clinical practice, we systematically searched for published research papers on the topic …

Background Clinical notes are ubiquitous resources offering potential value in optimizing
critical care via data mining technologies. Objective To determine the predictive value of …

The aim of this study is to build machine learning models to predict severe complications
using administrative and clinical elements that are collected immediately after patient …

Context Prognostication challenges contribute to delays in advance care planning (ACP) for
patients with cancer near the end of life (EOL). Objectives Examine a quality improvement …

Palliative care is an alternative to standard care for gravely ill patients that has demonstrated
many clinical benefits in cost-effective interventions. It is expected to grow in demand soon …

Palliative care (PC) has demonstrated benefits for life-limiting illnesses. Bad survival
prognosis and patients' decline are working criteria to guide PC decision-making for older …

Machine learning (ML) techniques can help predict survival among cancer patients and
might help with a timely integration in palliative care. We aim to explore the importance of …

Background: Polypharmacy is a growing issue that affects individuals of all ages yet is most
prevalent among patients aged 65 and older with chronic comorbidities. Although integral to …

Context. Prognostication challenges contribute to delays in advance care planning (ACP) for
patients with cancer near the end of life (EOL). Objectives. Examine a quality improvement …

[CA] Les Cures Pal· liatives (PC) són cures mèdiques especialitzades l'objectiu de les
qualsés millorar la qualitat de vida dels pacients amb malalties greus. Històricament, s' …