TY - JOUR
T1 - Digital cytology part 2
T2 - artificial intelligence in cytology: a concept paper with review and recommendations from the American Society of Cytopathology Digital Cytology Task Force
AU - Kim, David
AU - Sundling, Kaitlin E.
AU - Virk, Renu
AU - Thrall, Michael J.
AU - Alperstein, Susan
AU - Bui, Marilyn M.
AU - Chen-Yost, Heather
AU - Donnelly, Amber D.
AU - Lin, Oscar
AU - Liu, Xiaoying
AU - Madrigal, Emilio
AU - Michelow, Pamela
AU - Schmitt, Fernando C.
AU - Vielh, Philippe R.
AU - Zakowski, Maureen F.
AU - Parwani, Anil V.
AU - Jenkins, Elizabeth
AU - Siddiqui, Momin T.
AU - Pantanowitz, Liron
AU - Li, Zaibo
N1 - Publisher Copyright:
© 2023 American Society of Cytopathology
PY - 2024/3
Y1 - 2024/3
N2 - Digital cytology and artificial intelligence (AI) are gaining greater adoption in the cytology laboratory. However, peer-reviewed real-world data and literature are lacking in regard to the current clinical landscape. The American Society of Cytopathology in conjunction with the International Academy of Cytology and the Digital Pathology Association established a special task force comprising 20 members with expertise and/or interest in digital cytology. The aim of the group was to investigate the feasibility of incorporating digital cytology, specifically cytology whole slide scanning and AI applications, into the workflow of the laboratory. In turn, the impact on cytopathologists, cytologists (cytotechnologists), and cytology departments were also assessed. The task force reviewed existing literature on digital cytology, conducted a worldwide survey, and held a virtual roundtable discussion on digital cytology and AI with multiple industry corporate representatives. This white paper, presented in 2 parts, summarizes the current state of digital cytology and AI practice in global cytology practice. Part 1 of the white paper is presented as a separate paper which details a review and best practice recommendations for incorporating digital cytology into practice. Part 2 of the white paper presented here provides a comprehensive review of AI in cytology practice along with best practice recommendations and legal considerations. Additionally, the cytology global survey results highlighting current AI practices by various laboratories, as well as current attitudes, are reported.
AB - Digital cytology and artificial intelligence (AI) are gaining greater adoption in the cytology laboratory. However, peer-reviewed real-world data and literature are lacking in regard to the current clinical landscape. The American Society of Cytopathology in conjunction with the International Academy of Cytology and the Digital Pathology Association established a special task force comprising 20 members with expertise and/or interest in digital cytology. The aim of the group was to investigate the feasibility of incorporating digital cytology, specifically cytology whole slide scanning and AI applications, into the workflow of the laboratory. In turn, the impact on cytopathologists, cytologists (cytotechnologists), and cytology departments were also assessed. The task force reviewed existing literature on digital cytology, conducted a worldwide survey, and held a virtual roundtable discussion on digital cytology and AI with multiple industry corporate representatives. This white paper, presented in 2 parts, summarizes the current state of digital cytology and AI practice in global cytology practice. Part 1 of the white paper is presented as a separate paper which details a review and best practice recommendations for incorporating digital cytology into practice. Part 2 of the white paper presented here provides a comprehensive review of AI in cytology practice along with best practice recommendations and legal considerations. Additionally, the cytology global survey results highlighting current AI practices by various laboratories, as well as current attitudes, are reported.
KW - Artificial intelligence
KW - Cytopathology
KW - Digital cytology
KW - Recommendation
KW - Validation
KW - Whole slide image
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U2 - 10.1016/j.jasc.2023.11.005
DO - 10.1016/j.jasc.2023.11.005
M3 - Review article
C2 - 38158317
AN - SCOPUS:85181133787
SN - 2213-2945
VL - 13
SP - 97
EP - 110
JO - Journal of the American Society of Cytopathology
JF - Journal of the American Society of Cytopathology
IS - 2
ER -