As e-commerce platforms generate ever-longer streams of user-behavior data, machine-learning methods are increasingly examined for their ability to model how customer interests form and shift over ...

Researchers demonstrate how mathematical modeling combined with dynamic biomarkers can be used to characterize metastatic disease and identify appropriate therapeutic approaches to improve patient ...

Implementing Cancer Registry Data With the PCORnet Common Data Model: The Greater Plains Collaborative Experience Current image-based long-term risk prediction models do not fully use previous ...

Repetitive transcranial magnetic stimulation (rTMS) and other targeted, noninvasive neuromodulation approaches offer promise for treating neuropsychiatric conditions. These techniques work by ...

While dynamic modeling is arguably one of the most important technological developments for engineers in the last 50 years, many process control engineers are unable to use it. It requires proper time ...

Researchers from Jordan’s Al al-Bayt University have created comprehensive theoretical dynamic modeling to analyze the performance of building integrated photovoltaic thermal (BIPV/T) systems. The ...

Unfortunately, this book can't be printed from the OpenBook. If you need to print pages from this book, we recommend downloading it as a PDF. Visit NAP.edu/10766 to get more information about this ...

Researchers at the Department of Energy’s Oak Ridge National Laboratory (ORNL) have developed a dynamic modeling method that uses machine learning to provide accurate simulations of grid behavior and ...

Most cancer deaths are due to the metastatic spread and growth of tumor cells at distant sites. Identifying appropriate treatments for patients with metastatic disease is challenging because of ...