As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...

When machine learning is used to suggest new potential scientific insights or directions, algorithms sometimes offer ...

The study departs from conventional mean-based economic forecasting by focusing on quantile prediction, a technique that ...

This predictive model built on readily acquired clinical data provides encouraging results for the detection of residual disease. External validation and prospective studies implementing the model in ...

Advanced metering infrastructure, Internet of Things devices, and machine learning algorithms can improve communication ...

The severity of symptoms in posttraumatic stress disorder (PTSD) varies greatly across individuals in the first year after trauma and it remains difficult to predict whether someone might worsen, ...

A machine learning model may be a valid method of determining the risk for recurrence of MS among individuals who discontinue ...

Development and Validation of an Ipsilateral Breast Tumor Recurrence Risk Estimation Tool Incorporating Real-World Data and Evidence From Meta-Analyses: A Retrospective Multicenter Cohort Study Data ...