A big part of his work is figuring out when a statistical method is truly the best choice. Some problems have straightforward ...

Faculty develop methods for structured and unstructured biomedical data that advance statistical inference, machine learning, causal inference, and algorithmic modeling. Their work delivers principled ...

Scientists from Peking University conducts a systematic review of studies on integrating machine learning into statistical methods in disease prediction models. Researchers from Peking University have ...

Recent technological advances have enabled the production of vast amounts of data types that can help health researchers better understand complex diseases, such as cancer, cardiovascular diseases and ...

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...

We obtain a Bernstein-type inequality for sums of Banach-valued random variables satisfying a weak dependence assumption of general type and under certain smoothness assumptions of the underlying ...

Chongzhi Di develops statistical methods for analyzing functional and longitudinal data in epidemiologic studies of physical activity and sedentary behavior, particularly using data from mobile-health ...

Our lab has developed many data analysis workflows adapting and integrating sophisticated statistical methods to evaluate complex molecular datasets that we obtain with MS technologies. We are ...

Machine learning is reshaping the way portfolios are built, monitored, and adjusted. Investors are no longer limited to ...