AKBULUT, AKHANDESOUKI, SARAABDELKHALIQ, SARAKHANTOMANI, LAYALÇatal, Çağatay2023-10-272023-10-272023Akbulut, A., Desouki, S., AbdelKhaliq, S. et al. Design and implementation of a deep learning-empowered m-Health application. Multimed Tools Appl (2023).1380-7501https://doi.org/10.1007/s11042-023-17041-xhttps://hdl.handle.net/11413/8849Many 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.eninfo:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivs 3.0 United Stateshttp://creativecommons.org/licenses/by-nc-nd/3.0/us/MelanomaMachine LearningDeep Learningm-HealthSkin Lesion AnalysisArticle Early Access0010766392000012-s2.0-85172917797