Project description
Routine leukaemia diagnosis using AI
Peripheral blood smears remain a cornerstone in diagnosing haematologic neoplasms, providing rapid and valuable insights that guide further diagnostic steps. However, since neoplastic transformations typically originate in the bone marrow, they may not appear as detectable abnormalities in peripheral blood, posing a diagnostic challenge. Funded by the European Research Council, the LeukoScreen project develops an explainable transformer-based AI model to classify haematologic malignancies based on peripheral blood cytomorphology. The focus is on real-world patient data, which introduce additional heterogeneity and complexity. The goal is to optimise the model’s calibrated prediction probabilities, reduce the false discovery rate without missing acute leukaemia cases, and thereby minimise unnecessary bone marrow aspirations.
Objective
Acute promyelocytic leukemia is an extremely aggressive blood cancer where immediate diagnosis can determine life or death. The diagnostic state of the art is manual inspection of a patient’s blood smear under the microscope by trained cytologists. It is prone to human error and time consuming - a risk factor in notoriously understaffed laboratories. Supporting clinical decisions with AI will drastically increase diagnostic speed and accuracy, benefit patient survival, and free up valuable expert time. This is particularly important for cytological and histological analysis, whose market size is expected to rise by a compounded annual growth rate of 14.7% 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 the exploitation of results.
This AI approach to support disease detection will save patients’ lives, change the paradigm of cytologic workflows, and create capacities in overburdened diagnostics.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences software
- natural sciences physical sciences optics microscopy
- medical and health sciences clinical medicine oncology leukemia
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC-POC - HORIZON ERC Proof of Concept Grants
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2022-POC2
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85764 Neuherberg
Germany
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