Diliana Pecheva on Muck Rack

Diliana Pecheva

As seen in: Frontiers, BioRxiv
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Articles

FEMA-Long: Modeling unstructured covariances for discovery of time-dependent effects in large-scale longitudinal datasets

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By Pravesh Parekh, Nadine Staples Parker, Diliana Pecheva, Evgeniia Frei
| BioRxiv
Abstract Linear mixed-effects (LME) models are commonly used for analyzing longitudinal data. However, most applications of LME models rely on random intercepts or simple, e.g., stationary, covariance. Here, we extend the Fast and Efficient Mixed-Effects Algorithm (FEMA) and present FEMA-Long, a computationally tractable approach to flexibly modeling longitudinal covariance suitable for high-dimensional data.
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Reduced neurite density index in the prefrontal cortex of adults with autism assessed using neurite orientation dispersion and density imaging

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By Mario Torso, Markus Nilsson, Diliana Pecheva
| Frontiers
1. Introduction Autism-spectrum disorder (ASD) is a childhood-onset, lifelong neurodevelopmental disorder characterized by impaired social communication and social interaction and restricted, repetitive patterns of interest and behavior (1). Individuals with ASD are estimated to account for approximately 1% of the population (2).
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