Classification of Parkinsonian Syndromes from FDG-PET Brain Data Using Decision Trees with SSM/PCA Features Article Swipe
Deborah Mudali
,
Laura K. Teune
,
Remco J. Renken
,
Klaus L. Leenders
,
Jos B. T. M. Roerdink
·
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.1155/2015/136921
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.1155/2015/136921
Medical imaging techniques like fluorodeoxyglucose positron emission tomography (FDG-PET) have been used to aid in the differential diagnosis of neurodegenerative brain diseases. In this study, the objective is to classify FDG-PET brain scans of subjects with Parkinsonian syndromes (Parkinson’s disease, multiple system atrophy, and progressive supranuclear palsy) compared to healthy controls. The scaled subprofile model/principal component analysis (SSM/PCA) method was applied to FDG-PET brain image data to obtain covariance patterns and corresponding subject scores. The latter were used as features for supervised classification by the C4.5 decision tree method. Leave-one-out cross validation was applied to determine classifier performance. We carried out a comparison with other types of classifiers. The big advantage of decision tree classification is that the results are easy to understand by humans. A visual representation of decision trees strongly supports the interpretation process, which is very important in the context of medical diagnosis. Further improvements are suggested based on enlarging the number of the training data, enhancing the decision tree method by bagging, and adding additional features based on (f)MRI data.
Related Topics
Concepts
Decision tree
Artificial intelligence
Pattern recognition (psychology)
Progressive supranuclear palsy
Principal component analysis
Positron emission tomography
Context (archaeology)
Decision tree learning
Computer science
Classifier (UML)
Machine learning
Medicine
Pathology
Atrophy
Nuclear medicine
Biology
Paleontology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1155/2015/136921
- https://downloads.hindawi.com/journals/cmmm/2015/136921.pdf
- OA Status
- hybrid
- Cited By
- 59
- References
- 31
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2057374433
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2057374433Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1155/2015/136921Digital Object Identifier
- Title
-
Classification of Parkinsonian Syndromes from FDG-PET Brain Data Using Decision Trees with SSM/PCA FeaturesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2015Year of publication
- Publication date
-
2015-01-01Full publication date if available
- Authors
-
Deborah Mudali, Laura K. Teune, Remco J. Renken, Klaus L. Leenders, Jos B. T. M. RoerdinkList of authors in order
- Landing page
-
https://doi.org/10.1155/2015/136921Publisher landing page
- PDF URL
-
https://downloads.hindawi.com/journals/cmmm/2015/136921.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://downloads.hindawi.com/journals/cmmm/2015/136921.pdfDirect OA link when available
- Concepts
-
Decision tree, Artificial intelligence, Pattern recognition (psychology), Progressive supranuclear palsy, Principal component analysis, Positron emission tomography, Context (archaeology), Decision tree learning, Computer science, Classifier (UML), Machine learning, Medicine, Pathology, Atrophy, Nuclear medicine, Biology, PaleontologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
59Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 5, 2024: 7, 2023: 7, 2022: 5, 2021: 3Per-year citation counts (last 5 years)
- References (count)
-
31Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| corresponding_author_ids | https://openalex.org/A5073784823 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| corresponding_institution_ids | https://openalex.org/I1334415907, https://openalex.org/I169381384 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/16 |
| sustainable_development_goals[0].score | 0.7300000190734863 |
| sustainable_development_goals[0].display_name | Peace, Justice and strong institutions |
| citation_normalized_percentile.value | 0.94266416 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |