David P Ng, Paul D Simonson, Attila Tarnok, Fabienne Lucas, Wolfgang Kern, Nina Rolf, Goce Bogdanoski, Cherie Green, Ryan R Brinkman, Kamila Czechowska
Flow cytometry is a key clinical tool in the diagnosis of many hematologic malignancies and traditionally requires close inspection of digital data by hematopathologists with expert domain knowledge. Advances in artificial intelligence (AI) are transferable to flow cytometry and have the potential to improve efficiency and prioritization of cases, reduce errors, and highlight fundamental, previously unrecognized associations with underlying biological processes. As a multidisciplinary group of stakeholders, we review a range of critical considerations for appropriately applying AI to clinical flow cytometry, including use case identification, low and high risk use cases, validation, revalidation, computational considerations, and the present regulatory frameworks surrounding AI in clinical medicine...
February 26, 2024: Cytometry. Part B, Clinical Cytometry