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Applications of Machine Learning in Palliative Care: A Systematic Review.机器学习在姑息治疗中的应用:一项系统综述
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调查姑息治疗和临终关怀中 AI 应用的数据多样性和模型稳健性:范围综述方案。

Investigating Data Diversity and Model Robustness of AI Applications in Palliative Care and Hospice: Protocol for Scoping Review.

机构信息

Department of Biomedical Informatics, Emory University, Atlanta, GA, United States.

Division of Palliative Medicine, Department of Family and Preventive Medicine, Emory University, Atlanta, GA, United States.

出版信息

JMIR Res Protoc. 2024 Oct 8;13:e56353. doi: 10.2196/56353.

DOI:10.2196/56353
PMID:39378420
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11496913/
Abstract

BACKGROUND

Artificial intelligence (AI) has become a pivotal element in health care, leading to significant advancements across various medical domains, including palliative care and hospice services. These services focus on improving the quality of life for patients with life-limiting illnesses, and AI's ability to process complex datasets can enhance decision-making and personalize care in these sensitive settings. However, incorporating AI into palliative and hospice care requires careful examination to ensure it reflects the multifaceted nature of these settings.

OBJECTIVE

This scoping review aims to systematically map the landscape of AI in palliative care and hospice settings, focusing on the data diversity and model robustness. The goal is to understand AI's role, its clinical integration, and the transparency of its development, ultimately providing a foundation for developing AI applications that adhere to established ethical guidelines and principles.

METHODS

Our scoping review involves six stages: (1) identifying the research question; (2) identifying relevant studies; (3) study selection; (4) charting the data; (5) collating, summarizing, and reporting the results; and (6) consulting with stakeholders. Searches were conducted across databases including MEDLINE through PubMed, Embase.com, IEEE Xplore, ClinicalTrials.gov, and Web of Science Core Collection, covering studies from the inception of each database up to November 1, 2023. We used a comprehensive set of search terms to capture relevant studies, and non-English records were excluded if their abstracts were not in English. Data extraction will follow a systematic approach, and stakeholder consultations will refine the findings.

RESULTS

The electronic database searches conducted in November 2023 resulted in 4614 studies. After removing duplicates, 330 studies were selected for full-text review to determine their eligibility based on predefined criteria. The extracted data will be organized into a table to aid in crafting a narrative summary. The review is expected to be completed by May 2025.

CONCLUSIONS

This scoping review will advance the understanding of AI in palliative care and hospice, focusing on data diversity and model robustness. It will identify gaps and guide future research, contributing to the development of ethically responsible and effective AI applications in these settings.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/56353.

摘要

背景

人工智能(AI)已成为医疗保健领域的关键要素,推动了包括姑息治疗和临终关怀服务在内的各个医学领域的重大进展。这些服务专注于提高患有绝症患者的生活质量,而 AI 处理复杂数据集的能力可以增强这些敏感环境中的决策制定和个性化护理。然而,将 AI 纳入姑息治疗和临终关怀需要仔细检查,以确保其反映这些环境的多面性。

目的

本范围综述旨在系统地描绘 AI 在姑息治疗和临终关怀环境中的应用,重点关注数据多样性和模型稳健性。目标是了解 AI 的作用、其临床整合以及其开发的透明度,最终为开发符合既定伦理准则和原则的 AI 应用提供基础。

方法

我们的范围综述涉及六个阶段:(1)确定研究问题;(2)确定相关研究;(3)研究选择;(4)绘制数据;(5)整理、总结和报告结果;(6)与利益相关者协商。检索涵盖了 MEDLINE 通过 PubMed、Embase.com、IEEE Xplore、ClinicalTrials.gov 和 Web of Science Core Collection 等数据库,涵盖了每个数据库创建以来至 2023 年 11 月 1 日的研究。我们使用了一套全面的搜索词来捕获相关研究,如果摘要不是英文,则排除非英文记录。数据提取将遵循系统方法,利益相关者协商将完善研究结果。

结果

2023 年 11 月进行的电子数据库检索产生了 4614 项研究。去除重复项后,选择了 330 项研究进行全文审查,根据预设标准确定其是否符合入选标准。提取的数据将组织成表格,以帮助撰写叙述性摘要。预计审查将于 2025 年 5 月完成。

结论

本范围综述将深入了解姑息治疗和临终关怀中的 AI,重点关注数据多样性和模型稳健性。它将确定差距并指导未来的研究,为这些环境中开发符合道德规范且有效的 AI 应用做出贡献。

国际注册报告标识符(IRRID):DERR1-10.2196/56353.