Department of Management Information System, College of Business Administration, Taif University, P.O Box 11099, Taif 21944, Saudi Arabia.
Department of Computer Engineering, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia.
Comput Intell Neurosci. 2022 Jul 30;2022:7925668. doi: 10.1155/2022/7925668. eCollection 2022.
Pneumonia is a disease that spreads quickly and poses a serious risk to the health and well-being of its victims. An accurate biomedical diagnosis of pneumonia necessitates the use of various diagnostic tools and the evaluation of various clinical features, all of which are hindered by the lack of available experts and tools. According to the research presented here, a mobile app that uses deep learning techniques to classify whether or not a patient has pneumonia is being developed. It was hoped that a mobile application prototype for detecting pneumonia using neural networks would be developed as part of this study. The use of a high-level tool such as Create ML makes this process easier and eliminates issues such as how many layers a neural network has, initializing the model parameters, or which algorithms to use. The model can now be accessed by anyone, anywhere, via a mobile application. The dataset of more than 5,000 real images was used to train an image classification model using Create ML, a tool with a graphical interface, and there was no need for specialized knowledge.
肺炎是一种传播迅速的疾病，对患者的健康和福祉构成严重威胁。准确的肺炎生物医学诊断需要使用各种诊断工具和评估各种临床特征，但由于缺乏可用的专家和工具，所有这些都受到了阻碍。根据这里呈现的研究，正在开发一个使用深度学习技术来对患者是否患有肺炎进行分类的移动应用程序。本研究希望开发出一个使用神经网络检测肺炎的移动应用程序原型。使用像 Create ML 这样的高级工具可以使这个过程更加容易，并解决了神经网络有多少层、模型参数初始化或使用哪些算法等问题。现在，任何人都可以通过移动应用程序访问该模型。使用带有图形界面的 Create ML 工具，对超过 5000 张真实图像的数据集进行了图像分类模型训练，而无需专业知识。
