Application and performance of artificial intelligence technology in cytopathology

Area of Science:

• Pathology
• Cytopathology
• Artificial Intelligence
• Medical Imaging

Background:

• Artificial intelligence (AI) and deep learning are advancing image analysis capabilities.
• Early AI in pathology focused on computer-assisted Pap test screening.
• Recent AI research extends to whole-slide imaging in gynaecological and non-gynaecological histopathology.

Purpose of the Study:

• To provide a literature overview of AI in cytopathology.
• To emphasize AI algorithm applications in gynaecological and non-gynaecologic cytology.

Main Methods:

• Literature search conducted in PubMed, Web of Science, Scopus, Embase, and Google Scholar.
• Search focused on artificial intelligence in cytopathology from January 2000 to December 2021.
• Inclusion criteria: full-text online-accessible papers.

Main Results:

• AI is increasingly applied to whole-slide imaging for histopathology.
• Significant research exists on AI for gynaecological and non-gynaecologic cytology.
• The review synthesizes findings on AI's role in cytopathology interpretation.

Conclusions:

• AI demonstrates significant potential in cytopathology, particularly with whole-slide imaging.
• Further research and application of AI algorithms are relevant for both gynaecological and non-gynaecologic cytology.
• AI integration in cytopathology is a growing area with clinical implications.