Classification of Cervical Cancer using Deep Learning: A CNN approach
P. Namitha, Surapaneni Ravi Kishan, G Jahnavi, K. J N L V S Medhini · 2024
Cervical cancer, globally at position four and common in women, is majorly confined to less-developed nations. The cervical cancer remains an important global health concern, especially in areas with low screening and healthcare resources. Deep learning approaches provide extremely promising solutions to improve cervical cancer classification accuracy and accessibility. This paper presents a framework for cervical cancer classification using deep learning techniques. The proposed framework will thus contain the following steps: data collection, augmentation, preprocessing, training, and model evaluation. Convolutional Neural Networks are engaged in tasks since they work well with image classification as a base model architecture. Dimensions in ethics related to patient privacy, bias mitigation, and regulatory compliance are addressed. Our model goes well with an accuracy of 95%.