Statistical modeling of diabetic neuropathy: Exploring the dynamics of nerve mortality
Artikel i vetenskaplig tidskrift, 2023

Diabetic neuropathy is a disorder characterized by impaired nerve function and reduction of the number of epidermal nerve fibers per epidermal surface. Additionally, as neuropathy related nerve fiber loss and regrowth progresses over time, the two-dimensional spatial arrangement of the nerves becomes more clustered. These observations suggest that with development of neuropathy, the spatial pattern of diminished skin innervation is defined by a thinning process which remains incompletely characterized. We regard samples obtained from healthy controls and subjects suffering from diabetic neuropathy as realisations of planar point processes consisting of nerve entry points and nerve endings, and propose point process models based on spatial thinning to describe the change as neuropathy advances. Initially, the hypothesis that the nerve removal occurs completely at random is tested using independent random thinning of healthy patterns. Then, a dependent parametric thinning model that favors the removal of isolated nerve trees is proposed. Approximate Bayesian computation is used to infer the distribution of the model parameters, and the goodness-of-fit of the models is evaluated using both non-spatial and spatial summary statistics. Our findings suggest that the nerve mortality process changes as neuropathy advances.

Författare

Konstantinos Konstantinou

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Göteborgs universitet

Farnaz Ghorbanpour

Allameh Tabataba'i University

Umberto Picchini

Göteborgs universitet

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Adam Loavenbruck

University of Minnesota

Aila Särkkä

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Göteborgs universitet

Statistics in Medicine

0277-6715 (ISSN) 1097-0258 (eISSN)

Vol. 42 23 4128-4146

Djupinlärning och likelihood-fri Bayesiansk inferens för stokastiska modeller

Chalmers AI-forskningscentrum (CHAIR), 2020-01-01 -- 2024-12-31.

Vetenskapsrådet (VR) (2019-03924), 2020-01-01 -- 2023-12-31.

Ämneskategorier

Endokrinologi och diabetes

Oftalmologi

Sannolikhetsteori och statistik

Neurologi

DOI

10.1002/sim.9851

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Senast uppdaterat

2024-03-07