Artificial Intelligence in Palliative Care: A Scoping Review of Current Applications, Challenges, and Future Directions.

IF 1.4
Maria Nikoloudi, Kyriaki Mystakidou
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Abstract

BackgroundArtificial Intelligence (AI) is increasingly integrated into healthcare systems, presenting opportunities to improve clinical outcomes. In the context of palliative care, AI holds potential to enhance quality of life through improved symptom management, effective communication, and greater prognostic accuracy. For this review, AI refers to computational systems capable of learning, reasoning, or predicting outcomes. As integration advances, a critical examination of its applications, practical challenges, and ethical implications in palliative care is warranted.MethodsA scoping review was conducted using 4 major databases: PubMed, Google Scholar, Scopus, and CINAHL. A total of 7 studies were included, each addressing the use of AI technologies in palliative care settings, with a focus on clinical implementation, ethical challenges, and system integration. Both quantitative and qualitative studies were considered.ResultsAI applications in palliative care include predictive analytics, symptom control, and enhanced patient-caregiver communication. These tools demonstrate potential in facilitating early identification of patient needs and supporting timely interventions. However, significant challenges persist, particularly around data privacy, patient autonomy, algorithmic bias, and the "black box" nature of many AI models. Additional practical limitations include integration into clinician workflows, clinician trust, and concerns about the depersonalization of care.ConclusionAI offers substantial potential to improve palliative care, but implementation must be grounded in ethical frameworks prioritizing dignity, compassion, and patient-centeredness. Multidisciplinary collaboration is essential to ensure that AI augments rather than replaces the humanistic core of palliative care. Ongoing research and development of transparent, equitable algorithms are critical to responsibly harnessing AI's transformative potential.

姑息治疗中的人工智能:当前应用、挑战和未来方向的范围综述。
人工智能(AI)越来越多地融入医疗保健系统,为改善临床结果提供了机会。在姑息治疗的背景下,人工智能有可能通过改善症状管理、有效沟通和更高的预后准确性来提高生活质量。在本文中,人工智能指的是能够学习、推理或预测结果的计算系统。随着整合的推进,对其在姑息治疗中的应用、实际挑战和伦理影响进行批判性检查是有必要的。方法采用PubMed、谷歌Scholar、Scopus和CINAHL 4个主要数据库进行文献综述。共纳入7项研究,每项研究都涉及人工智能技术在姑息治疗环境中的应用,重点是临床实施、伦理挑战和系统集成。定量和定性研究都被考虑。结果人工智能在姑息治疗中的应用包括预测分析、症状控制和加强患者与护理者的沟通。这些工具在促进早期识别患者需求和支持及时干预方面显示出潜力。然而,重大挑战依然存在,特别是在数据隐私、患者自主权、算法偏见以及许多人工智能模型的“黑箱”性质方面。其他实际限制包括融入临床医生的工作流程,临床医生的信任,以及对护理的去人格化的担忧。结论人工智能为改善姑息治疗提供了巨大的潜力,但实施必须基于优先考虑尊严、同情和以患者为中心的伦理框架。多学科合作对于确保人工智能增强而不是取代姑息治疗的人文核心至关重要。持续研究和开发透明、公平的算法对于负责任地利用人工智能的变革潜力至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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