Sep 26, 2023 · This research aims to propose a robust explainable HCI model using SHAPley additive explanation, local interpretable model-agnostic explanations, and DL ...
Dec 27, 2022 · The proposed tests are focused on the evaluation of memory loss related to common objects, recent conversations and events; the diagnosis of ...
May 5, 2022 · The outcomes of the proposed model depict higher prediction accuracy bringing eicient computer interface in decision making, and suggests a high ...
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Oct 22, 2024 · The outcomes of the proposed model depict higher prediction accuracy bringing efficient computer interface in decision making, and suggests a ...
This research aims to propose a robust explainable HCI model using shapley additive explanation (SHAP), local interpretable model-agnostic explanations (LIME) ...
This article provides a systematic review of the application of LIME and SHAP in interpreting the detection of Alzheimer's disease (AD).
Oct 7, 2024 · Explanation-Driven HCI Model to Examine the Mini-Mental State for Alzheimer's Disease. ACM Trans. Multim. Comput. Commun. Appl. 20(2): 41:1 ...
Explainable Artificial Intelligence in Alzheimer's Disease Classification
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Nov 13, 2023 · This work presents a systematic review of the literature reporting Alzheimer's disease (AD) detection using XAI that were communicated during the last decade.
Gaur, M. Masud, and N. Jhanjhi, 'Explanation-driven HCI Model to Examine the Mini-Mental State for Alzheimer's Disease', Dec. 2022 ...
Feb 5, 2024 · In this study, we propose an explainable AI (XAI)-based approach for the diagnosis of Alzheimer's disease, leveraging the power of deep transfer learning and ...