5 天前 - … In recent years, machine learning, a subset of artificial intelligence (AI), has shown
… [10] to achieve model interpretability—a breakthrough in Explainable AI (XAI). SHAP is an …

5 天前 - … to assess Explainable Artificial Intelligence (XAI) for predicting intubation necessity
in methanol-poisoned patients, comparing deep learning and machine learning models. …

5 天前 - … It then proceeds to define research objectives, specifically concentrating on the
use of Federated Learning (FL) and Explainable Artificial Intelligence (XAI) techniques to …

5 天前 - … an explainable graph representation. This is achieved by employing Explainable
Artificial In… His areas of expertise include machine learning, artificial intelligence, graph neural …

5 天前 - … This approach has the added benefit of affording explainability to an analyst user.
By … We also illustrate how our approach allows for explainability of the anomalous portions …

5 天前 - … To address the limitations of current explainability techniques in … Explainable
Adversarial Machine Learning (EAML). The core idea behind EAML is to integrate explainability …

5 天前 - With the advancement of Artificial Intelligence (AI) techniques, intelligent healthcare
applications, such as early disease diagnosis, treatment of rare diseases, diagnosis using …

5 天前 - … Therefore, Healthcare 5.0 requires the integration of Explainable Artificial Intelligence
(XAI) with intelligent healthcare and machines that enable robust, precise prediction and …

5 天前 - … The lack of interpretability in artificial intelligence models further hinders their
adoption in healthcare. This chapter proposes an explainable DNN model for improved CRC …

5 天前 - … sciences, there’s an appetite for “explainable” methods for deep learning. The most
significant and explainable artificial intelligence concepts are laid out in this chapter, which …