AN IMPROVED BREAST CANCER DETECTION MODEL BASED ONCONVULUTIONAL NEURAL NETWORK

Lukuman Ibrahim; Samuel  Isah Odoh; Agushaka  Jeffery O.

doi:10.62050/fjst2026.v10.n2.664

المؤلفون

Lukuman Ibrahim
lukumanibrahim50@hotmail.com

Federal University of Lafia, Nigeria
Samuel Isah Odoh
Federal University of Lafia, Nigeria
Agushaka Jeffery O.
Federal University of Lafia, Nigeria

الكلمات المفتاحية:

Array

الملخص

Cancer is one of the diseases that causes deaths eventually to women worldwide, that need urgent need for more reliable diagnostic method for early detection to reduce the rate of mortality, many researchers have explode some technologies like machine learning and others techniques for classification of cancer but still several gap has remained, this articles investigate the potential of deep learning especially CNNs techniques for classification of malignant and benign which outperform the traditional classification method like traditional neural network and SVM, mammography, ultrasound and magnetic resonance image. The study identify that all the traditional method of classification of cancer are plague with several limitation which hinder their effectiveness, but using technique like CNN The study have achieve a remarkable success with high performance with accuracy of 98.5%, recall of 98.2 precision of 97.6, and F1-score of 98.0, the study gives an insight overview of deep learning offer crucial information to researchers medical professional of how to improved cancer classifications using CNN technique.

السير الشخصية للمؤلفين

Lukuman Ibrahim

Department of Computer Science

Samuel Isah Odoh

Department of Computer Science

Agushaka Jeffery O.

Dean Faculty of Computing

Dimensions

REFERENCES

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