Breast Cancer Diagnosis and Prognosis Using Triple Hybrid Deep Learning Approach

Author(s)	Sanitha P S, Jayakrishnan B
Country	India
Abstract	Breast cancer is one of the malignancies that affects women. Breast cancer is a condition that is brought on by abnormal breast cells that multiply and form tumours. If left untreated, tumours have the capacity to grow throughout the body and become fatal. Early initiation and thorough completion of treatment is associated with better outcomes and greater patient tolerance for breast cancer patients. These days, early detection of breast cancer is quite helpful and will help the women who battle the illness. The earliest detection of breast cancer can be successfully achieved with the use of machine learning-based approaches. Breast cancer can be diagnosed with great accuracy using a number of machine learning techniques, including CNN, RF, SVM, NB, KNN, AB, and others. Thus, I am introducing a triple hybrid deep learning method for breast cancer diagnosis and prognosis. This is the CNN, GRU, and LSTM combination.
Keywords	Machine Learning, Triple hybrid deep learning, CNN, GRU, LSTM
Field	Computer
Published In	Volume 6, Issue 3, May-June 2024
Published On	2024-06-01
Cite This	Breast Cancer Diagnosis and Prognosis Using Triple Hybrid Deep Learning Approach - Sanitha P S, Jayakrishnan B - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.21520
DOI	https://doi.org/10.36948/ijfmr.2024.v06i03.21520
Short DOI	https://doi.org/gtxrrz

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International Journal For Multidisciplinary Research