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COVID -19 Predictions using Transfer Learning based Deep Learning Model with Medical Internet of Things
International Journal on Recent and Innovation Trends in Computing and Communication ; 11(3):43-50, 2023.
Article in English | Scopus | ID: covidwho-2312532
ABSTRACT
Early detection of COVID-19 may help medical expert for proper treatment plan and infection control. Internet of Things (IoT) has vital improvement in many areas including medical field. Deep learning also provide tremendous improvement in the field of medical. We have proposed a Transfer learning based deep learning model with medical Internet of Things for predicting COVID-19 from X-ray images. In the proposed method, the X ray images of patient are stored in cloud storage using internet for wide access. Then, the images are retrieved from cloud and Transfer learning based deep learning models namely VGG-16, Inception, Alexnet, Googlenet and Convolution neural Network models are applied on the X-rays images for predicting COVID 19, Normal and pneumonia classes. The pre-trained models helps to the effectiveness of deep learning accuracy and reduced the training time. The experimental analysis show that VGG -16 model gives accuracy of 99% for detecting COVID19 than other models. © 2023 Sunarno Basuki and Perdinanto.
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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Prognostic study Language: English Journal: International Journal on Recent and Innovation Trends in Computing and Communication Year: 2023 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Prognostic study Language: English Journal: International Journal on Recent and Innovation Trends in Computing and Communication Year: 2023 Document Type: Article