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 ...

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

Using Real-World Data for Machine-Learning Algorithms to Predict the Treatment Response in Advanced Melanoma: A Pilot Study for Personalizing Cancer Care This study aims to investigate the impact of ...

Although the original Phase 3 A4 trial showed no statistically significant overall benefit for solanezumab (a humanized monoclonal antibody designed to treat Alzheimer’s disease by binding to and ...

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 ...

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 ...

The Uncertainty Engine is guiding research in fusion plasma physics. Could similar approaches benefit fission research as ...

A new study explores how artificial intelligence models can support clinical decision-making for sepsis management. Their research, titled “Responsible AI for Sepsis Prediction: Bridging the Gap ...