5 citations · 8 across the 11 of their papers we have counts for
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MORPHFED: Federated Learning for Cross-institutional Blood Morphology Analysis
Gabriel Ansah, Eden Ruffell, Delmiro Fernandez-Reyes +1
Automated blood morphology analysis can support hematological diagnostics in low- and middle-income countries (LMICs) but remains sensitive to dataset shifts from staining variabil…
Automated Detection of Acute Promyelocytic Leukemia in Blood Films and Bone Marrow Aspirates with Annotation-free Deep Learning
Petru Manescu, Priya Narayanan, Christopher Bendkowski +7
While optical microscopy inspection of blood films and bone marrow aspirates by a hematologist is a crucial step in establishing diagnosis of acute leukemia, especially in low-reso…
Data-Driven Malaria Prevalence Prediction in Large Densely-Populated Urban Holoendemic sub-Saharan West Africa: Harnessing Machine Learning Approaches and 22-years of Prospectively Collected Data
Biobele J. Brown, Alexander A. Przybylski, Petru Manescu +20
Plasmodium falciparum malaria still poses one of the greatest threats to human life with over 200 million cases globally leading to half-million deaths annually. Of these, 90% of c…