Artificial intelligence (AI) and machine learning have been playing an increasing role in healthcare, offering opportunities to enhance symptom management, prognostication, and personalized care for patients with life-limiting illnesses. In palliative care, AI applications can encompass a wide range of areas, including but not limited to decision support systems, predictive modeling, natural language processing (NLP) for patient communication, education, and the analysis of large datasets to identify patterns and trends in patient care. By using AI in novel ways, it has the potential to improve patient outcomes and the delivery of palliative care services.
Recent advances have demonstrated the feasibility of using AI algorithms to predict patient deterioration, optimize pain management strategies, and tailor care plans to individual patient needs. Additionally, AI-driven tools have shown promise in facilitating more efficient resource allocation and enhancing communication between healthcare providers, patients, and their families.
This Collection invites submissions exploring the multifaceted landscape of AI applications in palliative care, with a particular focus on elucidating these applications and addressing the ethical dimensions in their implementation. Potential topics of interest include:
- AI-driven decision support systems in palliative care
- Machine learning for prognostication in end-of-life care
- Natural language processing for patient communication in palliative care
- Ethical considerations in the use of AI in palliative care
- AI applications for symptom management in palliative care
- AI as a tool to foster palliative care training and education
- AI applications for audiovisual monitoring to enhance patient comfort and functional assessment
- Further uses in palliative care
This Collection supports and amplifies research related to SDG 3 (Good Health and Well-Being).
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