The parameter settings of the RF algorithm after parameter optimization. by Xini Fang (20861990)

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Features selected by optimization algorithms. by Afnan M. Alhassan (18349378)

“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”

MLP vs classification algorithms. by Mohd Mustaqeem (19106494)

“…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”

Hybrid feature selection algorithm of CSCO-ROA. by Afnan M. Alhassan (18349378)

“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”

Parameter optimization results of the RF model improved by FCM clustering. by Xini Fang (20861990)

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Construction process of RF. by Xini Fang (20861990)

Subjects:

The construction process of the FCM clustering algorithm. by Xini Fang (20861990)

Subjects:

The robustness test results of the model. by Xini Fang (20861990)

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Summary of all demographic, epidemiological and clinical data presented in data set used by the primary studies. by Sebastião Rogério da Silva Neto (11944944)

Summary of all non-clinical data (laboratory and others) presented in the data set used by the primary studies. by Sebastião Rogério da Silva Neto (11944944)

Clustering evaluation results of the FCM algorithm. by Xini Fang (20861990)

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Iteration curve of the optimization process. by Meijun Shang (22806461)

Total primary energy demand by fuel in China. by Da Lian (18880882)

Algorithm assessment of temporal drought class using TPM. by Muhammad Asif Khan (7367468)

Principle of the SVM algorithm. by Anfeng Zhu (17817144)

Performance metrics for BrC. by Afnan M. Alhassan (18349378)

“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”

Proposed CVAE model. by Afnan M. Alhassan (18349378)

“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”

Proposed methodology. by Afnan M. Alhassan (18349378)

“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”

Loss vs. Epoch. by Afnan M. Alhassan (18349378)

“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”

Sample images from the BreakHis dataset. by Afnan M. Alhassan (18349378)

“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”