AN AUTOMATED SKIN DISEASE DIAGNOSTIC SYSTEM BASED ON DEEP LEARNING MODEL
The use of computer technology has greatly enhanced the medical field, many computer applications, such as patient information system, monitoring and control systems, and diagnostic systems have been used to enhance healthcare. Technological developments in healthcare has helped in saving countless...
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| Veröffentlicht in: | Annals of Faculty Engineering Hunedoara 2021-08, Vol.19 (3), p.135-140 |
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| container_title | Annals of Faculty Engineering Hunedoara |
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| creator | Adegoke, Benjamin O Sotonwa, Kehinde A Omotosho, Lawrence O Oyeniran, Oluwashina A Oyeniyi, Joshua O |
| description | The use of computer technology has greatly enhanced the medical field, many computer applications, such as patient information system, monitoring and control systems, and diagnostic systems have been used to enhance healthcare. Technological developments in healthcare has helped in saving countless patients and are continuously improving our quality of life. Also technology in the medical field has had a massive impact on nearly all processes and practices of healthcare professionals. This study developed a robust system to enhance the decision making of dermatologist in Nigeria in terms of diagnosis of selected skin diseases, so as to foster quick diagnosis and treatment of various skin diseases through the use of a deep learning model. The developed system achieved the network accuracy of 98.44% and the validation accuracy of the test set is 99.44 % as specified by the training results, further testing reveal that the developed system yielded rejection rate of 2.2% and recognition accuracy of 97.8%. |
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| ispartof | Annals of Faculty Engineering Hunedoara, 2021-08, Vol.19 (3), p.135-140 |
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| language | eng |
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| source | DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals |
| subjects | Accuracy Artificial intelligence Bacterial infections Classification Cysts Decision making Deep learning Dermatitis Dermatology Diagnostic systems Disease Hair Health care Infections Medical diagnosis Neural networks Rejection rate Skin cancer Skin diseases Viral infections |
| title | AN AUTOMATED SKIN DISEASE DIAGNOSTIC SYSTEM BASED ON DEEP LEARNING MODEL |
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