Teledermatologist: Automated Diagnosis of Skin Diseases with Image Recognition

Nadav Ishai, Dolev Peretz, Natalia Vanetik, Marina Litvak

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Early diagnosis of skin diseases is crucial for effective treatment, preventing spread, minimizing long-Term damage, managing chronic conditions, detecting underlying health issues, and promoting psychological well-being. It is often necessary to do difficult tests in order to obtain a diagnosis, which demands a lot of resources from patients as well as medical personnel. Motivated by this shortage, we introduce a user-friendly and private system for the automatic detection of skin disease from a picture. Our system employs a deep neural model for the accurate classification of a given picture to one of the predefined classes of diseases. We created a large dataset of six skin lesion types and tested different neural models. The best-performing model, which achieved 92% accuracy, was integrated into our system. The application and its web demo can be accessed at https://teledermatologis-Ai.streamlit.app/.

Original languageEnglish
Title of host publication2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Electronic)9798350359855
DOIs
StatePublished - 1 Jan 2023
Externally publishedYes
Event2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023 - Jeju, Korea, Republic of
Duration: 4 Dec 20237 Dec 2023

Publication series

Name2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023

Conference

Conference2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023
Country/TerritoryKorea, Republic of
CityJeju
Period4/12/237/12/23

Keywords

  • Dataset
  • Facial Skin Disease
  • Image Recognition

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Signal Processing
  • Media Technology

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