基于深度学习的心脏病检测的研究

Detection of Heart Disease By Echocardiography Based on Deep Learning

心脏病是一类比较常见的循环系统疾病。医生可以通过超声心动图对患者进行检查,了解患者的心脏结构。超声心动图的图像质量直接影响结果判定的准确性,通过超声心动图来判定心脏病的类型具有一定的难度。深度学习是由多个处理层构成的计算模型,可以通过多层的抽象来学习数据的特征。在语音识别、视觉识别、目标检测和其他如药物鉴定,基因检测等领域,深度学习被广泛应用。介绍通过深度学习快速准确地识别出患者的心脏病变的类型,降低医生操作的复杂性。

Heart disease is a common disease of circulatory system. The clinician can examine the patient with the echocardiography, and then know about the heart structure of patient. The quality of echocardiographic images directly affects the accuracy of the examination. It is difficult to determine the type of heart disease by echocardiography. Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically improved the state-of- the-art in speech recognition, visual object recognition, object detection and many other domains such as drug discovery and genomics. Introduces the application of deep learning in quick and precise detection of heart disease types and the application can reduce the complexity of operation.