A new framework to classify the cancerous and non-cancerous pap smear images using filtering techniques to improve accuracy

Cervical cancer is not new to the research at the same time it has more impact on society to motivate to find better solutions to predict at the earlier stage to avoid the severity of the patient. Cervical cancer has various stages of severity and it will be analyzed using various diagnosis methods. Therefore to identify the severity, this research study will use machine learning approaches to analyze the medical diagnosis inputs. In this study, the cancerous pap smear images are given as input on machine learning algorithms and predicted the severity of decease for better treatment. Therefore this research paper proposes a new framework to classify the cancerous and non-cancerous pap smear images using filtering techniques to improve the better accuracy of the existing research studies.