Breast Cancer Prediction

Keywords: Breast, Cancer

Background

Breast cancer is a significant health concern worldwide, and early detection plays a significant role in improving treatment outcomes and patient survival rates. Artificial Neural Networks (ANNs) have shown promising results in various medical applications, including cancer prediction. Breast cancer prediction having several challenges, including the availability and quality of data, the complexity of the disease, the heterogeneity of breast cancer subtypes, the need for interpretability of predictions, and the potential for overfitting due to the high dimensionality of input features. Additionally, challenges related to feature selection, model generalization, and integration of diverse data sources further complicate the accurate prediction of breast cancer using artificial neural networks. Neural networks play a crucial role in predicting models within the health domain sector.

Aim & Objectives

Aim
To Predict the Breast Cancer Data Using DL Technique
Objective

Develop DL model to forecast breast cancer occurrence.
Train model with medical data for accurate classification.
Validate model's efficacy in predicting breast cancer through DL techniques.

Research Methodology

ANN Technique used

Software & Tools

Jupyter, Google Collab

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