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通过深度学习对儿科 tympanostomy 管进行评估

K M Chang¹, S S Surapaneni², N Shaikh³

¹Tufts University School of Medicine, Boston, MA, United States of America.

American journal of otolaryngology

|May 9, 2024

概括

一个人工智能算法准确地检测儿童的 tympanostomy 管 (TTs).

科学领域:

耳鼻喉科耳鼻喉科耳鼻喉科
医疗人工智能医疗人工智能
儿科手术儿科手术

背景情况:

tympanostomy管 (TT) 放置是一种常见的儿科手术.
对于TT检查的手术后后续,家庭需要付出大量的费用.
目前的后续方法需要亲自进行临床检查.

研究的目的:

为了评估人工智能算法的有效性,以确定 tympanostomy 管的存在.
将基于AI的TM评估与临床工作人员评估进行比较.
探索AI在减少后续访问负担方面的潜力.

主要方法:

对儿童 (10个月-10岁) 有TT病史的前性研究.
智能手机的耳镜用于捕获耳膜 (TM) 图像.
深度学习算法在TM图像上进行训练和测试,与临床医生的评估相比.

主要成果:

人工智能算法实现了97.7%的整体分类准确度.
用于检测带有或没有管的TM的高精度和回忆率.
人工智能在识别 tympanostomy 管存在方面表现强.

结论:

一个深度学习算法显示,使用耳镜图像对耳道存在的分类有前途.
人工智能可能会被普通人使用,他们可以使用可访问的眼镜.
未来的研究旨在开发AI来评估管道通透性和挤出.

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