An introduction with medical applications to functional data analysis
Functional data are data that can be represented by suitable functions, such as curves
(potentially multi‐dimensional) or surfaces. This paper gives an introduction to some basic …
(potentially multi‐dimensional) or surfaces. This paper gives an introduction to some basic …
K-mean alignment for curve clustering
The problem of curve clustering when curves are misaligned is considered. A novel
algorithm is described, which jointly clusters and aligns curves. The proposed procedure …
algorithm is described, which jointly clusters and aligns curves. The proposed procedure …
A rational approach to defining principal axes of multidirectional wall shear stress in realistic vascular geometries, with application to the study of the influence of …
The distribution of arterial lesions is attributed by the prevalent mechanistic theory to the
proatherogenic role played by low and oscillatory wall shear stress (WSS). However …
proatherogenic role played by low and oscillatory wall shear stress (WSS). However …
A case study in exploratory functional data analysis: geometrical features of the internal carotid artery
This pilot study is a product of the AneuRisk Project, a scientific program that aims at
evaluating the role of vascular geometry and hemodynamics in the pathogenesis of cerebral …
evaluating the role of vascular geometry and hemodynamics in the pathogenesis of cerebral …
Complex geometries in additive manufacturing: A new solution for lattice structure modeling and monitoring
The production of novel types of complex shapes is nowadays enabled by new
manufacturing paradigms such as additive manufacturing, also known as 3D printing. The …
manufacturing paradigms such as additive manufacturing, also known as 3D printing. The …
Local polynomial regression for symmetric positive definite matrices
Local polynomial regression has received extensive attention for the non-parametric
estimation of regression functions when both the response and the covariate are in …
estimation of regression functions when both the response and the covariate are in …
Classification of EEG signals: An interpretable approach using functional data analysis
Electroencephalography (EEG) is a noninvasive method to record electrical activity of the
brain. The EEG data is continuous flow of voltages, in this paper, we consider them as …
brain. The EEG data is continuous flow of voltages, in this paper, we consider them as …
An insight into the mechanistic role of the common carotid artery on the hemodynamics at the carotid bifurcation
The rationale for this study lies in the well-known predilection for vascular disease of the
carotid bifurcation, attributed to an altered shear stress distribution at the luminal surface and …
carotid bifurcation, attributed to an altered shear stress distribution at the luminal surface and …
Shape analysis of Euclidean curves under frenet-serret framework
Geometric frameworks for analyzing curves are common in applications as they focus on
invariant features and provide visually satisfying solutions to standard problems such as …
invariant features and provide visually satisfying solutions to standard problems such as …
Spatial regression models over two-dimensional manifolds
We propose a regression model for data spatially distributed over general two-dimensional
Riemannian manifolds. This is a generalized additive model with a roughness penalty term …
Riemannian manifolds. This is a generalized additive model with a roughness penalty term …