Interpretable machine learning for dermatological disease detection: Bridging the gap between accuracy and explainability-Reference-Cited by-同舟云学术

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Interpretable machine learning for dermatological disease detection: Bridging the gap between accuracy and explainability

Published:2024-09 Issue: Volume:179 Page:108919
ISSN:0010-4825
Container-title:Computers in Biology and Medicine
language:en
Short-container-title:Computers in Biology and Medicine

Author:

Nasir Yusra^ORCID,Kadian Karuna^ORCID,Sharma Arun^ORCID,Dwivedi Vimal^ORCID

Publisher

Elsevier BV

Reference26 articles.

1. Skin cancer classification using explainable artificial intelligence on pre-extracted image features;Khater;Intell. Syst. Appl.,2023

2. An explainable AI approach for the rapid diagnosis of COVID-19 using ensemble learning algorithms;Houwu;Front. Public Health,2022

3. Application of explainable artificial intelligence in the identification of Squamous Cell Carcinoma biomarkers;Meena;Comput. Biol. Med.,2022

4. Dermatologist-level classification of skin cancer with deep neural networks;Esteva;Nature,2017

5. A systematic review of Explainable Artificial Intelligence models and applications: Recent developments and future trends;Saranya;Decis. Anal. J.,2023

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