Abstract
Dermatological diseases are a significant global health concern, and advanced technologies have demonstrated considerable potential to improve the diagnosis and treatment of these conditions. The overall objective of this systematic review is to analyze and evaluate the use of preliminary digital diagnostic technologies in the field of dermatological diseases. The PRISMA methodology was used to collect approximately 50 products to support the article. The results obtained reveal several key findings. First, we investigate for which dermatological diseases these specialized technologies are used, finding that conditions such as skin cancer, rosacea and acne are the most diagnosed using advanced tools. Second, the technologies used to improve preliminary diagnosis are explored, with neural networks standing out, contributing to more accurate and efficient diagnosis. Third, the benefits of these technologies are evaluated, highlighting diagnostic accuracy, early detection and improved quality of patient care. In conclusion, this review highlights the crucial role of technologies in dermatology, not only improving diagnostic accuracy and treatment efficiency, but also optimizing resources and improving the patient experience.
| Original language | English |
|---|---|
| Article number | 146 |
| Journal | Archives of Dermatological Research |
| Volume | 317 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Artificial intelligence
- Convolutional neural networks
- Dermatology
- Diagnostic accuracy
- Early detection
- Image processing
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