- Tytuł:
- Classification and detection of skin disease based on machine learning and image processing evolutionary models
- Autorzy:
-
Bordoloi, Dibyahash
Singh, Vijay
Kaliyaperumal, Karthikeyan
Ritonga, Mahyudin
Jawarneh, Malik
Kassanuk, Thanwamas
Quiñonez-Choquecota, Jose - Powiązania:
- https://bibliotekanauki.pl/articles/38700501.pdf
- Data publikacji:
- 2023
- Wydawca:
- Instytut Podstawowych Problemów Techniki PAN
- Tematy:
-
skin disorder
machine learning
classification
image enhancement
image segmentation
disease detection
schorzenie skóry
nauczanie maszynowe
klasyfikacja
ulepszenie obrazu
segmentacja obrazów
wykrywanie choroby - Opis:
- Skin disorders, a prevalent cause of illnesses, may be identified by studying their physical structure and history of the condition. Currently, skin diseases are diagnosed using invasive procedures such as clinical examination and histology. The examinations are quite effective and beneficial. This paper describes an evolutionary model for skin disease classification and detection based on machine learning and image processing. This model integrates image preprocessing, image augmentation, segmentation, and machine learning algorithms. The experimental investigation makes use of a dermatology data set. The model employs the machine learning methods: the support vector machine (SVM), the k-nearest neighbors (KNN), and random forest algorithms for image categorization and detection. This suggested methodology is beneficial for the accurate identification of skin disease using image analysis. The SVM algorithm achieved an accuracy of 98.8%. The KNN algorithm achieved a sensitivity of 91%. The specificity of KNN was 99%.
- Źródło:
-
Computer Assisted Methods in Engineering and Science; 2023, 30, 2; 247-256
2299-3649 - Pojawia się w:
- Computer Assisted Methods in Engineering and Science
- Dostawca treści:
- Biblioteka Nauki
Artykuł