TY - JOUR AU - Zhang, Kai AU - Liu, Xiyang AU - Liu, Fan AU - He, Lin AU - Zhang, Lei AU - Yang, Yahan AU - Li, Wangting AU - Wang, shuau - Liu, Lin AU - Liu, Zhenzhen AU - Wu, Xiaohang AU - Lin，昊天PY - 2018 DA - 2018/11/14 TI -一个可解释性和可扩展的多眼部疾病深度学习诊断系统:定性研究JO - J Med Internet Res SP - e11144 VL - 20 IS - 11 KW -深度学习KW -对象定位KW -多眼疾病KW -可解释和可扩展诊断框架KW -医疗决策AB -背景:尽管人工智能在医学领域表现良好，但很少有自动疾病诊断平台能够清楚地解释为什么要做出特定的医疗决策。目的:我们旨在设计和开发一个可解释和可扩展的诊断框架，用于自动诊断多种眼部疾病，并为特定患者的特定疾病提供治疗建议。方法:由于眼科疾病的诊断高度依赖于医学图像的观察，我们选择了眼科图像作为研究材料。所有医学图像均被标记为4类疾病或正常(共5类);根据解剖知识将每张图像分解成不同的部分，然后进行标注。该过程产生了医学图像中观察到的不同解剖部位和病灶的位置和主要信息，从而弥合了医学图像和诊断过程之间的差距。接下来，我们应用图像和注释过程中产生的信息，实现了一个具有深度学习的可解释和可扩展的自动诊断框架。结果:该诊断框架包括4个阶段。第一阶段确定疾病类型(识别准确率93%)。 The second stage localizes the anatomical parts and foci of the eye (localization accuracy: images under natural light without fluorescein sodium eye drops, 82%; images under cobalt blue light or natural light with fluorescein sodium eye drops, 90%). The third stage carefully classifies the specific condition of each anatomical part or focus with the result from the second stage (average accuracy for multiple classification problems, 79%-98%). The last stage provides treatment advice according to medical experience and artificial intelligence, which is merely involved with pterygium (accuracy, >95%). Based on this, we developed a telemedical system that can show detailed reasons for a particular diagnosis to doctors and patients to help doctors with medical decision making. This system can carefully analyze medical images and provide treatment advices according to the analysis results and consultation between a doctor and a patient. Conclusions: The interpretable and expandable medical artificial intelligence platform was successfully built; this system can identify the disease, distinguish different anatomical parts and foci, discern the diagnostic information relevant to the diagnosis of diseases, and provide treatment suggestions. During this process, the whole diagnostic flow becomes clear and understandable to both doctors and their patients. Moreover, other diseases can be seamlessly integrated into this system without any influence on existing modules or diseases. Furthermore, this framework can assist in the clinical training of junior doctors. Owing to the rare high-grade medical resource, it is impossible that everyone receives high-quality professional diagnosis and treatment service. This framework can not only be applied in hospitals with insufficient medical resources to decrease the pressure on experienced doctors but also deployed in remote areas to help doctors diagnose common ocular diseases. SN - 1438-8871 UR - //www.mybigtv.com/2018/11/e11144/ UR - https://doi.org/10.2196/11144 UR - http://www.ncbi.nlm.nih.gov/pubmed/30429111 DO - 10.2196/11144 ID - info:doi/10.2196/11144 ER -