AN AUTOMATED SKIN DISEASE DIAGNOSTIC SYSTEM BASED ON DEEP LEARNING MODEL
The use of computer technology has significantly advanced the medical sector, and many computer technologies have been used to develop healthcare, such as the patient management system, monitoring and control systems, and diagnostic systems. Technological advances in healthcare have also helped in...
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| Format: | Article |
| Language: | English |
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Alma Mater Publishing House "Vasile Alecsandri" University of Bacau
2022-01-01
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| Series: | Journal of Engineering Studies and Research |
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| Online Access: | https://jesr.ub.ro/index.php/1/article/view/287 |
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| author | LAWRENCE OMOTOSHO KEHINDE SOTONWA BENJAMIN ADEGOKE OLUWASHINA OYENIRAN JOSHUA OYENIYI |
| author_facet | LAWRENCE OMOTOSHO KEHINDE SOTONWA BENJAMIN ADEGOKE OLUWASHINA OYENIRAN JOSHUA OYENIYI |
| author_sort | LAWRENCE OMOTOSHO |
| collection | DOAJ |
| description |
The use of computer technology has significantly advanced the medical sector, and many computer technologies have been used to develop healthcare, such as the patient management system, monitoring and control systems, and diagnostic systems. Technological advances in healthcare have also helped in saving numerous patients and are constantly improving our quality of life. Technology in the medical sector has also had a major effect on almost all healthcare professional techniques and practices. In order to facilitate rapid diagnosis and treatment of different skin diseases by the use of a deep learning model, this study developed a comprehensive framework to improve the decision-making of dermatologists in Nigeria in terms of the diagnosis of selected skin diseases. 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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| format | Article |
| id | doaj-art-803d736d9aa44b84ac491c4b88bd4c8b |
| institution | Kabale University |
| issn | 2068-7559 2344-4932 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Alma Mater Publishing House "Vasile Alecsandri" University of Bacau |
| record_format | Article |
| series | Journal of Engineering Studies and Research |
| spelling | doaj-art-803d736d9aa44b84ac491c4b88bd4c8b2025-02-11T11:39:57ZengAlma Mater Publishing House "Vasile Alecsandri" University of BacauJournal of Engineering Studies and Research2068-75592344-49322022-01-0127310.29081/jesr.v27i3.287AN AUTOMATED SKIN DISEASE DIAGNOSTIC SYSTEM BASED ON DEEP LEARNING MODELLAWRENCE OMOTOSHOKEHINDE SOTONWABENJAMIN ADEGOKEOLUWASHINA OYENIRANJOSHUA OYENIYI The use of computer technology has significantly advanced the medical sector, and many computer technologies have been used to develop healthcare, such as the patient management system, monitoring and control systems, and diagnostic systems. Technological advances in healthcare have also helped in saving numerous patients and are constantly improving our quality of life. Technology in the medical sector has also had a major effect on almost all healthcare professional techniques and practices. In order to facilitate rapid diagnosis and treatment of different skin diseases by the use of a deep learning model, this study developed a comprehensive framework to improve the decision-making of dermatologists in Nigeria in terms of the diagnosis of selected skin diseases. 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 %. https://jesr.ub.ro/index.php/1/article/view/287dermatology, artificial intelligence, deep learning, AlexNet |
| spellingShingle | LAWRENCE OMOTOSHO KEHINDE SOTONWA BENJAMIN ADEGOKE OLUWASHINA OYENIRAN JOSHUA OYENIYI AN AUTOMATED SKIN DISEASE DIAGNOSTIC SYSTEM BASED ON DEEP LEARNING MODEL Journal of Engineering Studies and Research dermatology, artificial intelligence, deep learning, AlexNet |
| title | AN AUTOMATED SKIN DISEASE DIAGNOSTIC SYSTEM BASED ON DEEP LEARNING MODEL |
| title_full | AN AUTOMATED SKIN DISEASE DIAGNOSTIC SYSTEM BASED ON DEEP LEARNING MODEL |
| title_fullStr | AN AUTOMATED SKIN DISEASE DIAGNOSTIC SYSTEM BASED ON DEEP LEARNING MODEL |
| title_full_unstemmed | AN AUTOMATED SKIN DISEASE DIAGNOSTIC SYSTEM BASED ON DEEP LEARNING MODEL |
| title_short | AN AUTOMATED SKIN DISEASE DIAGNOSTIC SYSTEM BASED ON DEEP LEARNING MODEL |
| title_sort | automated skin disease diagnostic system based on deep learning model |
| topic | dermatology, artificial intelligence, deep learning, AlexNet |
| url | https://jesr.ub.ro/index.php/1/article/view/287 |
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