Design and implementation of a deep learning-empowered m-Health application

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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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APA

Akbulut, A., Desouki, S., AbdelKhaliq, S., Khantomani, L., & Catal, C. (2024). Design and implementation of a deep learning-empowered m-Health application. Multimedia Tools and Applications, 83(12), 35995–36011. https://doi.org/10.1007/s11042-023-17041-x

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