{Reference Type}: Journal Article
{Title}: Artificial Intelligence Applications in Cytopathology: Current State of the Art.
{Author}: Vaickus LJ;Kerr DA;Velez Torres JM;Levy J;
{Journal}: Surg Pathol Clin
{Volume}: 17
{Issue}: 3
{Year}: 2024 Sep
暂无{DOI}: 10.1016/j.path.2024.04.011
{Abstract}: The practice of cytopathology has been significantly refined in recent years, largely through the creation of consensus rule sets for the diagnosis of particular specimens (Bethesda, Milan, Paris, and so forth). In general, these diagnostic systems have focused on reducing intraobserver variance, removing nebulous/redundant categories, reducing the use of "atypical" diagnoses, and promoting the use of quantitative scoring systems while providing a uniform language to communicate these results. Computational pathology is a natural offshoot of this process in that it promises 100% reproducible diagnoses rendered by quantitative processes that are free from many of the biases of human practitioners.