Automated Facial Acne Lesion Detecting and Counting Algorithm for Acne Severity Evaluation and Its Utility in Assisting Dermatologists.

Kim, Dong Hyo; Sun, Sukkyu; Cho, Soo Ick; Kong, Hyoun-Joong; Lee, Ji Won; Lee, Jun Hyo; Suh, Dae Hun

Kim, Dong Hyo; Sun, Sukkyu; Cho, Soo Ick; Kong, Hyoun-Joong; Lee, Ji Won; Lee, Jun Hyo; Suh, Dae Hun.

Afiliación

Kim DH; Department of Dermatology, Seoul National University College of Medicine, Seoul, South Korea.
Sun S; Acne, Rosacea, Seborrheic Dermatitis and Hidradenitis Suppurativa Research Laboratory, Seoul National University Hospital, Seoul, South Korea.
Cho SI; Biomedical Research Institute, Seoul National University Hospital, Seoul, South Korea.
Kong HJ; Department of Dermatology, Seoul National University College of Medicine, Seoul, South Korea.
Lee JW; Department of Transdisciplinary Medicine, Seoul National University Hospital, Seoul, South Korea.
Lee JH; Department of Medicine, Seoul National University College of Medicine, Seoul, South Korea.
Suh DH; Department of Dermatology, Seoul National University College of Medicine, Seoul, South Korea.

Am J Clin Dermatol ; 24(4): 649-659, 2023 Jul.

Article en En | MEDLINE | ID: mdl-37160644

Asunto(s)

Acné Vulgar; Dermatólogos; Humanos; Acné Vulgar/patología; Algoritmos; Fotograbar; Vesícula

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Acné Vulgar / Dermatólogos Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Am J Clin Dermatol Asunto de la revista: DERMATOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Corea del Sur Pais de publicación: Nueva Zelanda

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google