# Early skin disease diagnosis by using artificial neural network for internet of healthcare things
> Wan Bejuri W.M.Y.

URL kanonis: https://discover.unhas.ac.id/publications/early-skin-disease-diagnosis-by-using-artificial-neural-network-for-internet-of
Jurnal / Konferensi: Indonesian Journal of Electrical Engineering and Computer Science
Tahun terbit: 2025
DOI: https://doi.org/10.11591/ijeecs.v37.i2.pp1032-1041
ISSN: 25024752
Kuartil SJR: Q4
Citations: 1

## Authors
- Wan Bejuri W.M.Y.

## Abstract
<span lang="EN-US">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.</span>

## Keywords
- The Internet
- Artificial neural network
- Health care
- Disease
- Computer science
- Internet of Things
- Internet privacy
- Medicine
- Artificial intelligence
- Business
- World Wide Web
- Pathology
- Political science
- Law

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Sumber: Discover Unhas — RIMS Universitas Hasanuddin.
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