Early skin disease diagnosis by using artificial neural network for internet of healthcare things

Wan Bejuri, Wan Mohd Ya'akob and Mohamad, Mohd Murtadha and Michelle, Tang and Ahmad Khair, Aina Khairina and Adriyansyah, Yusuf Athallah and Kasmin, Fauziah and Tahir, Zulkifli (2025) Early skin disease diagnosis by using artificial neural network for internet of healthcare things. Indonesian Journal Of Electrical Engineering And Computer Science, 37 (2). pp. 1032-1041. ISSN 2502-4752

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Abstract

Internet of healthcare things (IoHT) represents a burgeoning field that leverages pervasive technologies to create technology driven environments for healthcare professionals, thereby enhancing the delivery of efficient healthcare services. In remote and isolated areas, such as rural communities and boarding schools, access to healthcare professionals (especially dermatologists) can be particularly challenging. However, these areas often lack the specialized expertise required for effective skin disease consultations. Thus, the purpose of this research is to design a scheme of early skin disease diagnosis for internet of healthcare things that is accessible anywhere and anytime. In this research, the image of skin disease from patient will be taken by using a mobile phone for predicting and identifying the disease. This proposed scheme will diagnose skin disease and convert it be meaningful information. As a result, it show our proposed scheme can be the most consistent in term of accuracy and loss compared to others method. Overall, this research represents a significant step toward improving healthcare accessibility and empowering individuals to manage their own health. Furthermore, the proposed scheme is anticipated to contribute significantly to the IoHT field, benefiting both academia and societal health outcomes.

Item Type:	Article
Uncontrolled Keywords:	Artificial intelligence, Artificial neural networks, Early skin disease diagnosis, Skin detection, Internet of healthcare things
Divisions:	Faculty of Information and Communication Technology
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	11 Dec 2025 02:31
Last Modified:	11 Dec 2025 02:31
URI:	http://eprints.utem.edu.my/id/eprint/29175
Statistic Details:	View Download Statistic

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