AZ-skin: Inclusive system for skin disease recognition from hybrid data
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2023/10/16
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Indian UGC (journal)
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Refrences48
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Asma Zhiou
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Hasna Njah ORCID (unauthenticated)
Cite
Zhiou, Asma, and Hasna Njah. “AZ-Skin: Inclusive System for Skin Disease Recognition from Hybrid Data”. Multimedia Tools and Applications, vol. 83, no. 14, 2023, pp. 43199-21, https://doi.org/10.1007/s11042-023-17225-5.
Zhiou, A., & Njah, H. (2023). AZ-skin: Inclusive system for skin disease recognition from hybrid data. Multimedia Tools and Applications, 83(14), 43199-43221. https://doi.org/10.1007/s11042-023-17225-5
Zhiou, Asma, and Hasna Njah. “AZ-Skin: Inclusive System for Skin Disease Recognition from Hybrid Data”. Multimedia Tools and Applications 83, no. 14 (2023): 43199-221. https://doi.org/10.1007/s11042-023-17225-5.
Zhiou A, Njah H. AZ-skin: Inclusive system for skin disease recognition from hybrid data. Multimedia Tools and Applications. 2023;83(14):43199-221.
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Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Accessibility of direct-to-consumer teledermatology to underserved populations | Journal of the American Academy of Dermatology |
| 4 | 2022 |
| A Point-of-Care, Real-Time Artificial Intelligence System to Support Clinician Diagnosis of a Wide Range of Skin Diseases | Journal of Investigative Dermatology |
| 9 | 2021 |
| A deep learning system for differential diagnosis of skin diseases | Nature Medicine |
| 275 | 2020 |
| Use of Teledermatology to Improve Dermatological Access in Rural Areas | Telemedicine Journal and e-Health |
| 58 | 2019 |
Skin Lesion Segmentation in Dermoscopic Images with Combination of YOLO and GrabCut Algorithm | Diagnostics |
| 131 | 2019 |