Journal article Open Access

Cervical Cancer: Machine Learning Techniques for Detection, Risk Factors and Prevention Measures

Elmer Diaz; Andres Ccopa; Lenis Wong

Rights holder(s)
Blue Eyes Intelligence Engineering and Sciences Publication(BEIESP)

Cervical Cancer is considered the fourth most common female malignancy worldwide and represents a major global health challenge. As a result, in recent years, various proposals and researches have been conducted. This study aims to analyze the data presented in current researches regarding cervical cancer and contribute to future research, all through the framework of literature review, based on 3 research questions: Q1: What are the risk factors that cause cervical cancer? Q2: What preventive measures are currently established for cervical cancer? and, Q3: What are the techniques to detect cervical cancer? Findings show that detection techniques are complementary since they are categorized under machine learning. Therefore, we recommend that further study be promoted in these techniques as they are helpful in the detection process. In addition, risk factors can be considered for a greater scope in detection, such as HPV infection, since it is the most relevant factor for the development of cervical cancer. Finally, we suggest to conduct further research on preventive measures for cervical cancer.

Files (322.5 kB)
Name Size
322.5 kB Download
Views 22
Downloads 14
Data volume 4.5 MB
Unique views 14
Unique downloads 14


Cite as