The Augmented Hematologist: Human-AI Feedback Loops to Assist Differential Cell Count during the Analysis of Bone Marrow Aspirates

Bermejo-Peláez, D., Rueda Charro, S., Mousa, A., Alamo, E., Garcia Roa, M., Trelles-Martínez, R., . . . Martinez Lopez, J. (2022). The augmented hematologist: Human-ai feedback loops to assist differential cell count during the analysis of bone marrow aspirates. Blood, 140 (Supplement 1), 10736-10737. doi:10.1182/blood-2022-160005

Every day, thousands of hematologists worldwide analyze bone marrow aspirate (BMA) samples supported by an optical microscope and their own clinical expertise. A crucial part of the BMA analysis, the differential cell count (DCC), is still a time-consuming task that wastes professionals’ energy and time, and its results are subject to interobserver variability (Fuentes-Arderiu 2009). Significant advances have been made to date to assist professionals during the DCC process and to increase their efficiency by leveraging artificial intelligence. However, these tools have not been widely implemented in real clinical environments due to the complexity and high price of the devices that allow the digitization of BMA samples (Chandradevan 2020, Jin 2020).


We aimed to develop and evaluate a simple and integrated digital system (see Figure) to cover the entire process, from sample digitization to DCC facilitated by human-artificial intelligence (AI) interaction, by using a 3D printed microscopy adapter arm, a smartphone, a mobile application, and a web-based telemedicine platform.