The global demand for Explainable AI (XAI) is accelerating as organizations seek greater transparency and accountability in artificial intelligence systems used across critical industries. According ...

This study applied three models—random forest (RF), gradient boosting regression (GBR), and linear regression (LR)—to predict county-level LC mortality rates across the United States. Model ...

Machine learning has seen use cases rise as more and more sectors, from healthcare to insurance, leverage it to increase the speed of operations. Research from Algorithmia found that 76% of ...

Medulloblastoma the most common malignant pediatric brain tumor with a high risk of metastasis and poor survival outcomes. To delineate the metastatic microenvironment,, researchers in China have ...

Krishna, Satyapriya, Tessa Han, Alex Gu, Steven Wu, Shahin Jabbari, and Himabindu Lakkaraju. "The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective." Transactions on ...

A new study published in Genome Research presents an interpretable artificial intelligence framework that improves both the accuracy and transparency of genomic prediction, a key challenge in fields ...

The ability of machine learning models to read great quantities of unstructured data, spot patterns and translate it into actionable information is driving a significant uptake in the technology.