重新想象的学习:人工智能在推进癌症研究和治疗技术教育中的作用。

IF 2.8 4区 医学 Q3 ONCOLOGY
Technology in Cancer Research & Treatment Pub Date : 2025-01-01 Epub Date: 2025-09-16 DOI:10.1177/15330338251378314
Maria F Chan, Dongxu Wang
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引用次数: 0

摘要

通过图形、图表和其他视觉工具进行视觉学习,已被证明可以显著增强信息保留,研究表明,高达83%的学习是视觉的。在放射肿瘤学领域,继续教育对安全有效地治疗癌症至关重要,传统资源的复杂性和大量文本的性质可能对有效学习构成障碍。这篇社论探讨了生成式人工智能(AI)的变革潜力,通过定制的视觉学习模块增强对放射肿瘤学文件的理解,为癌症护理专业人员提供支持。利用AAPM TG-100报告“风险分析方法在放射治疗质量管理中的应用”作为概念证明,作者首先手动开发了基于网络的信息图表,然后演示了ChatGPT、ClickUp和NotebookLM等人工智能工具如何极大地加快了这一过程。这些工具不仅可以自动创建高质量的视觉效果,还支持个性化和多模式学习,包括为听觉学习者生成的人工智能播客。通过使复杂的肿瘤特定内容更易于获取,人工智能使放射肿瘤学临床医生和学员能够更好地理解、实施和创新癌症治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Learning Reimagined: AI's Role in Advancing Education of Cancer Research and Treatment Technology.

Learning Reimagined: AI's Role in Advancing Education of Cancer Research and Treatment Technology.

Learning Reimagined: AI's Role in Advancing Education of Cancer Research and Treatment Technology.

Learning Reimagined: AI's Role in Advancing Education of Cancer Research and Treatment Technology.

Visual learning, through graphics, diagrams, and other visual tools, has been shown to significantly enhance information retention, with studies indicating that up to 83% of learning is visual. In the field of radiation oncology, where continuous education is critical to the safe and effective treatment of cancer, the complexity and text-heavy nature of traditional resources can pose barriers to effective learning. This editorial examines the transformative potential of generative artificial intelligence (AI) in supporting cancer care professionals by enhancing comprehension of radiation oncology documents through tailored, visual learning modules. Using the AAPM TG-100 report "Application of risk analysis methods to radiation therapy quality management" as a proof of concept, the authors first developed web-based infographics manually and then demonstrated how AI tools such as ChatGPT, ClickUp, and NotebookLM dramatically expedite the process. These tools not only automate the creation of high-quality visuals but also support personalized and multimodal learning, including AI-generated podcasts for auditory learners. By making complex oncology-specific content more accessible, AI empowers radiation oncology clinicians and trainees to better understand, implement, and innovate in cancer treatment.

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来源期刊
CiteScore
4.40
自引率
0.00%
发文量
202
审稿时长
2 months
期刊介绍: Technology in Cancer Research & Treatment (TCRT) is a JCR-ranked, broad-spectrum, open access, peer-reviewed publication whose aim is to provide researchers and clinicians with a platform to share and discuss developments in the prevention, diagnosis, treatment, and monitoring of cancer.
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