Intelligent Detection of Skin Diseases Based on The Optimized YOLO V8

In the realm of dermatological diagnostics, the advent of artificial intelligence (AI) has heralded a transformative era, particularly with the application of advanced object detection models like YOLO V8. This study delves into the nuanced capabilities of YOLO V8 in discerning and classifying nine distinct dermatological conditions, a task previously fraught with challenges due to the varied and complex nature of skin diseases. Our research harnesses the robust architecture of YOLO V8, meticulously trained on a diverse dataset comprising both public and private sources, augmented through sophisticated image processing techniques. The model's performance was rigorously evaluated, demonstrating remarkable accuracy and efficiency in real-time detection scenarios. This not only underscores the potential of AI in enhancing diagnostic precision but also paves the way for more accessible and timely dermatological care. As we stand on the precipice of a new horizon in medical technology, the implications of such advancements are both profound and promising, potentially revolutionizing the landscape of dermatological treatment and patient care.

Authors

Institutions

Publication Details

Published
2024-12-06
DOI
https://doi.org/10.1109/iciba62489.2024.10868331
Primary Topic
E-commerce and Technology Innovations
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Intelligent Detection of Skin Diseases Based on The Optimized YOLO V8

Wenqing Ren, Jian Huang, Lina Ru
E-commerce and Technology Innovations
article

Intelligent Detection of Skin Diseases Based on The Optimized YOLO V8

Wenqing Ren, Jian Huang, Lina Ru
article en

Abstract

In the realm of dermatological diagnostics, the advent of artificial intelligence (AI) has heralded a transformative era, particularly with the application of advanced object detection models like YOLO V8. This study delves into the nuanced capabilities of YOLO V8 in discerning and classifying nine distinct dermatological conditions, a task previously fraught with challenges due to the varied and complex nature of skin diseases. Our research harnesses the robust architecture of YOLO V8, meticulously trained on a diverse dataset comprising both public and private sources, augmented through sophisticated image processing techniques. The model's performance was rigorously evaluated, demonstrating remarkable accuracy and efficiency in real-time detection scenarios. This not only underscores the potential of AI in enhancing diagnostic precision but also paves the way for more accessible and timely dermatological care. As we stand on the precipice of a new horizon in medical technology, the implications of such advancements are both profound and promising, potentially revolutionizing the landscape of dermatological treatment and patient care.

Wuhan University (CN), Affiliated Hospital of Youjiang Medical University for Nationalities (CN), Wuhan University of Engineering Science
Guangxi University
Openalex Percentile: Top 50%
E-commerce and Technology Innovations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.