TY - JOUR
T1 - Analysis of the use of digital technologies in the preliminary diagnosis of dermatological diseases
T2 - a systematic review
AU - Sapaico-Alberto, Angie Fiorella
AU - Olaya-Cotera, Sandro
AU - Flores-Castañeda, Rosalynn Ornella
N1 - Publisher Copyright:
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
PY - 2025/12
Y1 - 2025/12
N2 - 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.
AB - 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.
KW - Artificial intelligence
KW - Convolutional neural networks
KW - Dermatology
KW - Diagnostic accuracy
KW - Early detection
KW - Image processing
UR - http://www.scopus.com/inward/record.url?scp=85212704110&partnerID=8YFLogxK
U2 - 10.1007/s00403-024-03650-5
DO - 10.1007/s00403-024-03650-5
M3 - Artículo de revisión
AN - SCOPUS:85212704110
SN - 0340-3696
VL - 317
JO - Archives of Dermatological Research
JF - Archives of Dermatological Research
IS - 1
M1 - 146
ER -