Purpose

Artificial Intelligence is being applied in oncology to improve patient and service outcomes. Yet, there is a limited understanding of how these advanced computational techniques are employed in cancer nursing to inform clinical practice. This review aimed to identify and synthesise evidence on artificial intelligence in cancer nursing.

Methods

CINAHL, MEDLINE, PsycINFO, and PubMed were searched using key terms between January 2010 and December 2022. Titles, abstracts, and then full texts were screened against eligibility criteria, resulting in twenty studies being included. Critical appraisal was undertaken, and relevant data extracted and analysed. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed.

Results

Artificial intelligence was used in numerous areas including breast, colorectal, liver, and ovarian cancer care among others. Algorithms were trained and tested on primary and secondary datasets to build predictive models of health problems related to cancer. Studies reported this led to improvements in the accuracy of predicting health outcomes or identifying variables that improved outcome prediction. While nurses led most studies, few deployed an artificial intelligence based digital tool with cancer nurses in a real-world setting as studies largely focused on developing and validating predictive models.

Conclusion

Electronic cancer nursing datasets should be established to enable artificial intelligence techniques to be tested and if effective implemented in digital prediction and other AI-based tools. Cancer nurses need more education on machine learning and natural language processing, so they can lead and contribute to artificial intelligence developments in oncology.

中文翻译：

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人工智能在癌症护理中的应用和使用：系统评价

目的

人工智能正在应用于肿瘤学，以改善患者和服务结果。然而，对于如何在癌症护理中应用这些先进的计算技术来为临床实践提供信息，人们的了解还很有限。本综述旨在识别和综合癌症护理中人工智能的证据。

方法

2010 年 1 月至 2022 年 12 月期间，使用关键术语对 CINAHL、MEDLINE、PsycINFO 和 PubMed 进行了检索。根据资格标准对标题、摘要和全文进行了筛选，最终纳入了 20 项研究。进行了批判性评估，并提取和分析了相关数据。遵循系统评价和荟萃分析 (PRISMA) 指南的首选报告项目。

结果

人工智能被应用于许多领域，包括乳腺癌、结直肠癌、肝癌和卵巢癌护理等。在主要和次要数据集上训练和测试算法，以建立与癌症相关的健康问题的预测模型。研究报告称，这提高了预测健康结果或识别改善结果预测的变量的准确性。虽然护士主导了大多数研究，但很少有人在现实环境中与癌症护士一起部署基于人工智能的数字工具，因为研究主要集中在开发和验证预测模型上。

结论

应建立电子癌症护理数据集，以便测试人工智能技术，并在数字预测和其他基于人工智能的工具中有效实施。癌症护士需要更多有关机器学习和自然语言处理的教育，以便他们能够领导并为肿瘤学人工智能的发展做出贡献。