Publication:
Design and Implementation of a Deep Learning-Empowered m-Health Application

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Except where otherwised noted, this item's license is described as info:eu-repo/semantics/openAccess

Abstract

Many people are unaware of the severity of melanoma disease even though such a disease can be fatal if not treated early. This research aims to facilitate the diagnosis of melanoma disease in people using a mobile health application because some people do not prefer to visit a dermatologist due to several concerns such as feeling uncomfortable by exposing their bodies. As such, a skincare application was developed so that a user can easily analyze a mole at any part of the body and get the diagnosis results quickly. In the first phase, the corresponding image is extracted and sent to a web service. Later, the web service classifies using the pre-trained model built based on a deep learning algorithm. The final phase displays the confidence rates on the mobile application. The proposed model utilizes the Convolutional Neural Network and provides 84% accuracy and 72% precision. The results demonstrate that the proposed model and the corresponding mobile application provide remarkable results for addressing the specified health problem.

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Akbulut, A., Desouki, S., AbdelKhaliq, S. et al. Design and implementation of a deep learning-empowered m-Health application. Multimed Tools Appl (2023).

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