Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

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, ...

Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...