Generating Interpretable Patterns for Biomedical Image Classification

Kang, Dong-Woo; Kim, Sunung; Jung, Yoonsik; Ryoo, Hong Seo

doi:10.1109/bibm52615.2021.9669323

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Cited by 2 publications

References 6 publications

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Feature Selection via Nonlinear Set Covering in Logical Analysis of Data

Yan,

Xu,

Zhao

et al. 2023

J CIRCUIT SYST COMP

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In logical analysis of data, the feature selection step only considers selecting minimal number of features after binarization. This paper develops a nonlinear set covering model that explores the interaction between the number of selected original attributes and binarized features. Utilizing the partial derivative of pseudo-Boolean functions, we give a greedy heuristic for the nonlinear set covering problem. The efficacy of the algorithm is demonstrated through experiments on 10 public machine learning datasets from UCI repository.

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Feature Selection via Nonlinear Set Covering in Logical Analysis of Data

Yan,

Xu,

Zhao

et al. 2023

J CIRCUIT SYST COMP

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show abstract

Recognition of Diabetic Retina Patterns using Machine Learning

Chhabra,

Bhatia

2024

The Future of Computing: Ubiquitous Applications and Technologies

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Medical images contain data related to the diseases and it should be interpreted accurately. However, its visual interpretation is quite complex/timeconsuming and only medical experts can examine this data precisely. In case of diabetes, the retina may be damaged and it is quite complex to examine its impact on the retina because there are a lot of vessels inside the human eyes that may be changed due to this disease and manual interpretation of these changes consumes excessive time. In order to overcome this issue, in this paper, a contour-based pattern recognition method (CBPR) is introduced that can recognize multiple patterns in sample retina images. Comparative analysis with the segmentation-based method (SBPR) shows that it outperforms in terms of performance parameters (i.e. Accuracy/Sensitivity/ Specificity etc.).

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Generating Interpretable Patterns for Biomedical Image Classification

Cited by 2 publications

References 6 publications

Feature Selection via Nonlinear Set Covering in Logical Analysis of Data

Feature Selection via Nonlinear Set Covering in Logical Analysis of Data

Recognition of Diabetic Retina Patterns using Machine Learning

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