The research on explainable deep learning can enhance the capabilities for AI-assisted diagnosis by integrating with large-scale medical systems, providing an effective and interactive way to promote medical intelligence. Different from common explainable deep learning methods, the deep learning explanation ...
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When artificial intelligence (AI) is used to make high-stakes decisions, some worry that this will create a morally troubling responsibility gap—that
Without explanations behind an AI model’s internal functionalities and the decisions it makes, there is a risk that the model would not be considered trustworthy or legitimate. XAI provides the needed understandability and transparency to enable greater trust toward AI- based solutions. Thus, XAI ...
Dear Colleagues, Cancer is one of the major causes of death in the world. Recently, AI has widely been used in artificial intelligence (AI). In the past, AI has shown itself as a complex tool and a solution assisting medical professionals in the diagnosis/prognosis of different cancers in ...
Fujitsu and Tokai National Higher Education and Research System leverage explainable AI to enhance space weather prediction in collaboration with JAXA
XAI is the method of making AI decision-making processes understandable and accessible to human users.
We will also share recommendations on XAI governance, and how it connects to AI governance more broadly, and functions such as model risk management. This road map can serve as a guide for senior managers, risk and compliance executives, heads of AI research and business unit leaders that are...
A library for graph deep learning research deep-learninggraph-generationexplainable-mlself-supervised-learning3d-graphgraph-neural-network UpdatedJul 15, 2024 Python Trusted-AI/AIX360 Star1.7k Code Issues Pull requests Interpretability and explainability of data and machine learning models ...
This Special Issue will present a collection of cutting-edge research and recent real-world applications in causal inference/discovery and interpretable/explainable AI, with the aim of making complex or black-box AI/ML models understandable and supporting reliable, trustable and responsible decision maki...