MedElevator Войти в исследования
← Поиск публикаций

DOI 10.1177/15330338251378314

Медицинская библиотека · Technology in cancer research & treatment · 2025

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

Chan Maria F, Wang Dongxu

Редакционная статьяПеревод пока не подготовлен

Аннотация

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.

Для цитирования: Chan Maria F, Wang Dongxu. Learning Reimagined: AI's Role in Advancing Education of Cancer Research and Treatment Technology.. Technology in cancer research & treatment. 2025. DOI: 10.1177/15330338251378314.

Предметные рубрики MeSH

Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.