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A large expert-annotated single-cell peripheral blood dataset for hematological disease diagnostics.
Sci. Data 12:1773 (2025)
Distinguishing cell types in a peripheral blood smear is critical for diagnosing blood diseases, such as leukemia subtypes. Artificial intelligence can assist in automating cell classification. For training robust machine learning algorithms, however, large and well-annotated single-cell datasets are pivotal. Here, we introduce a large, publicly available, annotated peripheral blood dataset comprising >40,000 single-cell images classified into 18 classes by cytomorphology experts from the Munich Leukemia Laboratory, the largest European laboratory for blood disease diagnostics. By making our dataset publicly available, we provide a valuable resource for medical and machine learning researchers and support the development of reliable and clinically relevant diagnostic tools for diagnosing hematological diseases.
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Publication type
Article: Journal article
Document type
Scientific Article
ISSN (print) / ISBN
2052-4463
e-ISSN
2052-4463
Journal
Scientific Data
Quellenangaben
Volume: 12,
Issue: 1,
Article Number: 1773
Publisher
Nature Publishing Group
Publishing Place
London
Reviewing status
Peer reviewed
Institute(s)
Human-Centered AI (HCA)