Stroke ranks among the leading causes for morbidity and mortality worldwide. New and
continuously improving treatment options such as thrombolysis and thrombectomy have …

BACKGROUND: The surprise question—“Would I be surprised if this patient died in the next
12 months?”—has been used to identify patients at high risk of death who might benefit from …

Background Access to palliative care is a key quality metric which most healthcare
organizations strive to improve. The primary challenges to increasing palliative care access …

Radiomics extracts and mines large number of medical imaging features quantifying tumor
phenotypic characteristics. Highly accurate and reliable machine-learning approaches can …

Background: Meeting the needs of relatives when a family member is dying can help
facilitate better psychological adjustment in their grief. However, end of life experiences for …

Background. The role of cognitive biases and heuristics in medical decision making is of
growing interest. The purpose of this study was to determine whether studies on cognitive …

Background Prognostic accuracy in palliative care is valued by patients, carers, and
healthcare professionals. Previous reviews suggest clinicians are inaccurate at survival …

Shared decision making for advanced heart failure has become both more challenging and
more crucial as duration of disease and treatment options have increased. High-quality …

Importance Machine learning algorithms could identify patients with cancer who are at risk of
short-term mortality. However, it is unclear how different machine learning algorithms …

The evidence base demonstrating the benefits of an early focus on palliative care for
patients with serious cancers, including advanced lung cancer, is substantial. Early …