AI-Driven Personalization of End-of-Life Care for the Elderly

This section provides a comprehensive overview of the study design, objectives, population, interventions, and methods without repeating information already included in other sections of the record. It elaborates on the rationale for using AI-based software to personalize end-of-life care for elderly patients, details the randomized controlled trial setup, explains inclusion and exclusion criteria, intervention specifics, outcome measures, data collection methods, and planned statistical analyses. This description ensures a clear understanding of the study's scope and methodology.

Inclusion criteria

Age ≥ 60 years

Clinical diagnosis of being in the end-of-life stage, based on criteria such as the Karnofsky Performance Scale or Palliative Performance Scale

Informed consent obtained from the participant or legal representative

Ability to use technology independently or with support provided by the research team

Access to necessary equipment for the intervention (e.g., wearable sensors, smartphone/tablet)

Exclusion criteria

Presence of severe cognitive impairment preventing software use

Voluntary withdrawal from the study at any stage

Critical medical deterioration or death during the study

Poor adherence or insufficient engagement with the intervention software in the intervention group