Ervin Sejdic

TL;DR: It is found that single and multi-layer Deep Belief networks perform nearly identically when analyzing only a single vibration signal, however, multi-layered Deep belief networks demonstrated approximately a 5% to 10% greater accuracy and sensitivity when both signals were analyzed concurrently, indicating that higher-order relationships between these vibrations are important for classification and assessment.

TL;DR: More physiologically-monitored hot flashes were associated with more DMN connectivity, particularly networks supporting the hippocampus, which underscores the importance of continued investigation of the central nervous system in efforts to understand this classic menopausal phenomenon.

TL;DR: The results provide the first evidence that motor imagery of gait may be used as a biomarker of MCI in older adults and any association between the TUG delta time and a cognitive status.

TL;DR: Local smoothness, an important parameter of vertex-varying graph signals, is introduced and defined in this paper and basic properties of this parameter are given.

TL;DR: Machine learning network analysis of resting alpha-band neural activity identified several aberrant networks in individuals with first-episode schizophrenia spectrum psychosis, including the left temporal, right inferior frontal, right posterior parietal, and bilateral cingulate cortices.