A Breast Cancer Detection Model using a Tuned SVM Classifier

Ghose, Partho; Uddin, Md. Ashraf; Islam, Mohammad Manzurul; Islam, Manowarul; Acharjee, Uzzal Kumar

doi:10.1109/iccit57492.2022.10055054

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Cited by 3 publications

References 16 publications

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BrainSegNeT: A Lightweight Brain Tumor Segmentation Model Based on U-Net and Progressive Neuron Expansion

Ghose,

Biswas,

Gaur

2023

Lecture Notes in Computer Science

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BrainSegNeT: A Lightweight Brain Tumor Segmentation Model Based on U-Net and Progressive Neuron Expansion

Ghose,

Biswas,

Gaur

2023

Lecture Notes in Computer Science

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Enhancing Breast Cancer Detection: A Machine Learning Approach Using Multielectrode Bioimpedance

Bougandoura,

Achour,

Zaoui

2024

Bioelectricity

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Deep Learning Perspectives for Prediction of Diabetic Foot Ulcers

Sharma,

Kaushal,

Dogra

et al. 2023

Metaverse Applications for Intelligent Healthcare

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A significant complication of diabetes mellitus, diabetic foot ulcers (DFUs), can have devastating repercussions if they are not identified and treated right away. Machine learning algorithms have gained more attention recently for their potential to anticipate DFUs before they manifest, enabling early management and preventing consequences. In this chapter, the authors examine how convolutional neural networks (CNNs) can be used to forecast DFUs. The performance of DenseNet, EfficientNet, and a regular CNN are specifically compared. With labels identifying the presence or absence of a DFU, the authors use a dataset of medical photographs of diabetic feet to train each model. The objective is to assess the effectiveness of these models and look at how each layer affects the precision of the predictions. The authors also hope to provide some light on how the algorithms are able to pinpoint foot regions that are most likely to get DFUs. They also look into how each CNN model's different layers affect prediction accuracy.

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A Breast Cancer Detection Model using a Tuned SVM Classifier

Cited by 3 publications

References 16 publications

BrainSegNeT: A Lightweight Brain Tumor Segmentation Model Based on U-Net and Progressive Neuron Expansion

BrainSegNeT: A Lightweight Brain Tumor Segmentation Model Based on U-Net and Progressive Neuron Expansion

Enhancing Breast Cancer Detection: A Machine Learning Approach Using Multielectrode Bioimpedance

Deep Learning Perspectives for Prediction of Diabetic Foot Ulcers

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