An integrated design of particle swarm optimization (PSO) with fusion of features for detection of brain tumor
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Cites
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
A 75:25 ratio for training and testing provides the best accuracy.
“It has been observed in the literature that the 75:25 ratio for training and testing provides the best accuracy [65].”
From A Comprehensive Analysis of Recent Deep and Federated-Learning-Based Methodologies for Brain Tumor Diagnosis (2022) · cites this paper as [65]
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References 84 · Cited by 206
- Authors
- Sharif, M., Amin, J., Raza, M., Yasmin, M., & Satapathy, S. C.
- Affiliations
- COMSATS University Islamabad (PK)
- KIIT University (IN)
- Corresponding author
- Amin, Javaria
- Venue
- Pattern Recognition Letters
- Publisher
- Elsevier BV
- Published
- 2020-01
- Volume
- 129
- Pages
- 150-157
- ISSN
- 0167-8655 (ISSN-L)
- OpenAlex
- W2988529604
- Cited by
- 206
- References
- 84
- Citations by year
- 2026: 7 · 2025: 25 · 2024: 28 · 2023: 53 · 2022: 49 · 2021: 30 · 2020: 13 · 2019: 1
- FWCI
- 10.26
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Pattern Recognition Letters (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Neurology › Brain Tumor Detection and Classification
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Keywords
- brain tumor detection, brain tumor grading, skull removal, image segmentation, particle swarm optimization, local binary pattern, feature fusion, genetic algorithm feature selection, artificial neural network classification
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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