AI And Cervical Cancer Screening: A New Era In Women's Health. Review

Maged Naser, Mohamed M. Nasr, Lamia H. Shehata

Abstract


Among cancers, cervical cancer is unique since it may be prevented and eradicated, primarily by vaccine and proactive screening. Nonetheless, many women in low- and middle-income nations still require cervical cancer screening. There are clear advantages and disadvantages to traditional cervical cancer screening methods in terms of sensitivity, specificity, timeliness, and cost. With an emphasis on machine learning (ML) and deep learning (DL) approaches, artificial intelligence(AI) has become widely used in recent years to assist medical practitioners in conducting comprehensive cervical cancer screenings. AI technology in conjunction with conventional screening techniques has demonstrated early efficacy in cervical cancer screening. However, there are a number of issues that must be addressed, including the lack of resources and technology, the complexities of integrating clinical processes, and the ethical and legal hazards associated with largescale community cervical cancer screening. This review initially discussed how AI improves the triage and diagnosis procedures for colposcopy and human papillomavirus (HPV), streamlines workflows, and helps with cytological segmentation and diagnosis. Next, we compiled the current clinical examples of AI used in widespread cervical cancer screening. Lastly, we talked about the difficulties and constraints of using AI to test for cervical cancer in big populations. By enhancing diagnosis accuracy, promoting early intervention, and boosting the overall effectiveness of cervical cancer screening programs globally, these discoveries may have the potential to revolutionize cervical cancer screening.

Keywords


Artificial intelligence, cervical cancer screening, deep learning, and machine learning.

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References


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DOI: http://dx.doi.org/10.52155/ijpsat.v58.1.8339

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