人工智能在乳腺超声教学中的应用价值

The Application Value of Artificial Intelligence in Breast Ultrasound Teaching

随着超声仪器分辨率提高和乳腺超声成像报告和数据系统(breast imaging reporting and data system,BIRADS)在乳腺结节诊断中的规范应用,超声已成为我国目前公认的诊断乳腺疾病的影像学检查手段之一。由于超声医学实践性较强,所以要求带教老师在教学过程中不仅要注重理论教学,更要重视实践教学。传统的教学模式存在不足,迫切需要新的教学模式应用于乳腺超声教学。近年来,人工智能(artificial intelligence,AI)发展日新月异,逐步应用于教学活动。人工智能是计算机科学的分支,是研究、开发用于模拟、延伸和扩展人类智能的理论、方法、技术及应用系统的一门新兴技术科学。将AI应用于乳腺超声教学是最具发展前景的领域,更新教育方式,创新教学理念,顺应时代发展潮流。文章从乳腺超声教学的现状、人工智能的发展现状、人工智能在乳腺超声教学中的优势及局限性四个方面详细阐述了人工智能在乳腺超声教学中的应用价值。

With the improvement of the resolution of ultrasound instruments and the standardized application of Breast Imaging Reporting and Data System(BI-RADS)in the diagnosis of breast nodules,ultrasound has become one of the recognized imaging examination methods for the diagnosis of breast diseases in China.Due to the strong practicality of ultrasound medicine,teachers are required to pay attention not only to theoretical teaching,but also to practical teaching.The traditional teaching mode has shortcomings,and a new teaching mode is urgently needed to be applied to breast ultrasound teaching.In recent years,artificial intelligence(AI)has developed rapidly and has been gradually applied to teaching activities.Artificial intelligence is a branch of computer science and an emerging technological science that studies and develops theories,methods,techniques and application systems for simulating,extending and expanding human intelligence.With the rapid development of artificial intelligence,it has been gradually applied to the theoretical teaching and clinical practice of breast ultrasound.The application of AI in breast ultrasound teaching is the most promising field,updating the education method,innovating the teaching concept,and conforming to the development trend of the times.This paper elaborates the application value of artificial intelligence in breast ultrasound teaching from four aspects:the current situation of breast ultrasound teaching,the development status of artificial intelligence,the advantages and limitations of artificial intelligence in breast ultrasound teaching.