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AI-based leukemia detection in routine diagnostic blood smear data

CORDIS · observation · Publication date unknown

7% in coming years. Yet, so far, the proof of concept that AI can be effectively employed for leukemia detection in routine diagnostics is missing. I will leverage the methodological advancements in deep learning and explainable AI, the skills of my ERC CoG funded research group, and the expertise and data of the Munich Leukemia Laboratory (MLL), the largest leukemia laboratory in Europe and my long standing industry partner. Together, we will develop and implement LeukoScreen, an AI-based software to automatically identify and flag up acute leukemia cases from MLL’s routine laboratory input. This will decrease the diagnosis to treatment time of critical leukemia cases at reduced costs and staffing. Specifically, we will (i) deploy a real-world dataset from the routine input of the MLL, (ii) train and evaluate our algorithm for transparent decision making on routine diagnostic blood smears, (iii) quantify the gain in sensitivity, specificity, and speed by comparing LeukoScreen with the currently used manual workflow at MLL, and (iv) jointly develop a commercialization strategy for

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recordType

award

status

SIGNED

region

EU

value

150000

unit

EUR