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 ...

Using a real-world, nationwide electronic health record–derived deidentified database of 38,048 patients with advanced NSCLC, we trained binary prediction algorithms to predict likelihood of 12-month ...

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 ...

A machine learning (ML)-based model may aid in-hospital community-acquired pneumonia (CAP) mortality prediction, according to study findings published in Respiratory Medicine. Res ...

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 ...

Found in knee replacements and bone plates, aircraft components, and catalytic converters, the exceptionally strong metals known as multiple principal element alloys (MPEA) are about to get even ...

Image courtesy by QUE.com As we navigate through 2026, the landscape of technology is no longer just shifting; it is being ...