Growing populations of older adults with life-limiting diseases are straining healthcare systems worldwide, while palliative care specialists remain in critically short supply. This mismatch between rising demand and limited human resources creates gaps in end-of-life care precisely when demographic trends suggest the need will only intensify. The convergence of aging populations with technological advancement presents both challenge and opportunity for how societies approach terminal illness care.
This comprehensive review examined artificial intelligence applications in palliative care across major medical databases from 2015 to 2025. The analysis identified specific domains where machine learning tools demonstrate clinical utility, from symptom prediction algorithms to decision support systems for pain management. AI-powered platforms showed particular promise in identifying patients who would benefit from palliative interventions earlier in their disease trajectory, potentially improving quality of life during final months.
The integration of AI into end-of-life care represents uncharted ethical territory in healthcare technology. Unlike acute care applications where AI assists diagnosis and treatment, palliative care AI must navigate deeply personal decisions about comfort, dignity, and family preferences. The review highlights fundamental questions about algorithm transparency when supporting emotionally charged medical decisions, and whether technological solutions can adequately address the profoundly human dimensions of dying. While AI may help distribute palliative expertise more broadly, the field must carefully evaluate which aspects of terminal care benefit from computational support versus requiring irreplaceable human judgment and compassion.
