CADFU for Dermatologists: A Novel Chronic Wounds & Ulcers Diagnosis System with DHuNeT (Dual-Phase Hyperactive UNet) and YOLOv8 Algorithm.

Shah, Syed Muhammad Ahmed Hassan; Rizwan, Atif; Atteia, Ghada; Alabdulhafith, Maali

Shah, Syed Muhammad Ahmed Hassan; Rizwan, Atif; Atteia, Ghada; Alabdulhafith, Maali.

Afiliación

Shah SMAH; Department of Computer Science, COMSATS University Islamabad, Attock Campus, Attock 43600, Pakistan.
Rizwan A; Department of Computer Engineering, Jeju National University, Jejusi 63243, Republic of Korea.
Atteia G; Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.
Alabdulhafith M; Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.

Healthcare (Basel) ; 11(21)2023 Oct 27.

Article en En | MEDLINE | ID: mdl-37957985

Palabras clave

DHuNeT; YOLOv8; artificial intelligence; chronic wounds; deep learning; foot ulcers; medical diagnosis

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Healthcare (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Pakistán Pais de publicación: Suiza

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