Exploring the Use of Vision Transformer in the Classification of Anal and Cervical Lesions: A Systematic Review

• Ingrid Bromerschenckel UFOP
• Andrea Gomes Campos UFOP

DOI: https://doi.org/10.5753/sbcas.2025.7874

Abstract

Although anal canal cancer (ACC) has a low incidence among gastrointestinal tract tumors, a significant increase in the number of cases has been observed, making it an emerging public health concern. This paper presents a systematic review of the use of the Vision Transformer architecture in classifying cervical and anal cells, evaluating its performance compared with other machine learning architectures. Cervical cells were included in the study due to their histological similarity to anais cells and the widespread use of the Pap test. The objective is to identify the state of the art in the diagnosis of cervical cancer through conventional cytology and to explore the feasibility of using transfer learning for application in anal cancer.

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