Assessing the Interpretability of Machine Learning Models in Early Detection of Alzheimer's Disease-Reference-Cited by-同舟云学术

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Assessing the Interpretability of Machine Learning Models in Early Detection of Alzheimer's Disease

Published:2024-07-08 Issue: Volume:12 Page:1-6
ISSN:
Container-title:2024 16th International Conference on Human System Interaction (HSI)
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Author:

Haddada Karim¹,Khedher Mohamed Ibn²,Jemai Olfa¹,Khedher Sarra Iben³,El-Yacoubi Mounim A.⁴

Affiliation:

1. National Engineering School of Gabes (ENIG), University of Gabes,Research Team in Intelligent Machines (RTIM)

2. IRT - SystemX,Palaiseau,France,91120

3. Universty of Monastir,Faculty of Medicine of Monastir,Monastir,Tunisie,5000

4. Institut Polytechnique de Paris,Samovar, Telecom SudParis,Palaiseau,France,91120

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10613508/10613523/10613551.pdf?arnumber=10613551

Reference36 articles.

1. Deep learning and image processing-based early detection of Alzheimer disease in cognitively normal individuals

2. Comparative study of Deep Learning architectures for Early Alzheimer Detection

3. How does the model make predictions? A systematic literature review on the explainability power of machine learning in healthcare

4. Interpreting artificial intelligence models: a systematic review on the application of LIME and SHAP in Alzheimer’s disease detection

5. Explainable Artificial Intelligence in Alzheimer’s Disease Classification: A Systematic Review

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