This case study of an initiative at Penn Medicine describes a process that included a 4-week trial period, followed ...
A seven-year study found that distinct EEG brain-wave patterns emerging at age 9 can predict vulnerability to anxiety or ...
A longitudinal study tracking children over a period of seven years identified distinct brain-wave patterns emerging from age ...
Abstract: This paper presents a novel approach to practical nonlinear model predictive control (PNMPC) using Kolmogorov–Arnold networks (KANs) as prediction models. KANs are based on the ...
A longitudinal study tracking children over a period of seven years has identified distinct brain-wave patterns emerging from ...
A longitudinal study tracking children over a period of seven years identified distinct brain-wave patterns emerging from age ...
Community detection provides a principled lens on mesoscale organization in functional brain networks, yet many widely used methods presume assortative structure and depend on arbitrary thresholding, ...
Connectome-based predictive modeling harnesses comprehensive maps of neural connections to forecast aspects of cognition in individuals. By integrating structural and functional connectivity data ...
kDepartment of Medicine (Biomedical Informatics), Stanford University, Stanford, CA, USA lDepartment of Biomedical Data Science, Stanford University, Stanford, CA, USA ...
Temporary teams can build new systems, but permanent ones can both develop them and manage them after launch. by Ryan Nelson and Thomas H. Davenport In 2011, The New York Times was facing declines in ...
Abstract: This paper develops a personalized federated learning-based distributed model predictive control (PFL-DMPC) method with predictive error compensation (PEC ...
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