Multinomial logistic regression algorithm for the classification of patients with parkinsonisms

Compared to existing algorithms, this approach offers comparable accuracy and reliability in diagnosing PD, MSA, and PSP with no need of healthy control images. It can also distinguish between multiple types of parkinsonisms simultaneously and offers the flexibility to easily accommodate new groups.

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Publication Details

Journal
EJNMMI Research
Published
2025-03-16
DOI
https://doi.org/10.1186/s13550-025-01210-0
Citations
2
Primary Topic
Parkinson's Disease Mechanisms and Treatments
Type
article
Field-Weighted Citation Impact
2.78

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article

Multinomial logistic regression algorithm for the classification of patients with parkinsonisms

Jan Jamšek, Urban Simončič, Tomaž Rus, Eva Štokelj et al.
2 citations
EJNMMI Research
Parkinson's Disease Mechanisms and Treatments
2.78
article

Multinomial logistic regression algorithm for the classification of patients with parkinsonisms

Jan Jamšek, Urban Simončič, Tomaž Rus, Eva Štokelj, Maja Trošt
article en
2 citations

Abstract

Compared to existing algorithms, this approach offers comparable accuracy and reliability in diagnosing PD, MSA, and PSP with no need of healthy control images. It can also distinguish between multiple types of parkinsonisms simultaneously and offers the flexibility to easily accommodate new groups.

EJNMMI ResearchVol. 15(1)
University of Ljubljana (SI), Ljubljana University Medical Centre (SI)
Javna Agencija za Raziskovalno Dejavnost RS
Openalex Percentile: Top 12%
Parkinson's Disease Mechanisms and Treatments
2.78
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