Deep Neural Networks (DNNs) have achieved remarkable accuracy for numerous applications, yet their complexity often renders the explanation of predictions a challenging task. This complexity contrasts ...

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common liver disease in the world, with a global prevalence of 25%. MASLD has an estimated prevalence of 34% in the United ...

Please provide your email address to receive an email when new articles are posted on . Explainable machine learning can offer accurate diagnoses and identify causes of chronic kidney disease in early ...

On the 31st of May 2024, M.Sc. Anton Björklund defends his PhD thesis on Interpretable and explainable machine learning for natural sciences. The thesis is related to research done in the Department ...

The hydrologic system is subjected unprecedented stresses and increasing demands driven by climate variabilities, landuse changes, groundwater ...

Company Adds 39 New Global Patents to Enrich New Product Innovation and Deepen Leadership in Explainable AI ...

The terrestrial water cycle is a fundamental component of Earth's climate system, governing the exchange of water between land surfaces and the atmosphere.

In todays fast evolving financial landscape, artificial intelligence and machine learning are changin how credit decisions get made. But the traditional “black box” models cause worry 'cause nobody ...

This course explores the field of Explainable AI (XAI), focusing on techniques to make complex machine learning models more transparent and interpretable. Students will learn about the need for XAI, ...