AIMC Topic: Bone Marrow Examination

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A deep-learning algorithm (AIFORIA) for classification of hematopoietic cells in bone marrow aspirate smears based on nine cell classes-a feasible approach for routine screening?

Journal of hematopathology
Bone marrow cytology plays a key role for the diagnosis and classification of hematological disease and is often the first step in the acute setting of unclear cytopenia. AI applications represent a powerful tool in digital image analysis and can imp...

Performance Evaluation of a Novel Artificial Intelligence-Assisted Digital Microscopy System for the Routine Analysis of Bone Marrow Aspirates.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Bone marrow aspiration (BMA) smear analysis is essential for diagnosis, treatment, and monitoring of a variety of benign and neoplastic hematological conditions. Currently, this analysis is performed by manual microscopy. We conducted a multicenter s...

Deep learning identifies Acute Promyelocytic Leukemia in bone marrow smears.

BMC cancer
BACKGROUND: Acute promyelocytic leukemia (APL) is considered a hematologic emergency due to high risk of bleeding and fatal hemorrhages being a major cause of death. Despite lower death rates reported from clinical trials, patient registry data sugge...

A Machine Learning Tool Using Digital Microscopy (Morphogo) for the Identification of Abnormal Lymphocytes in the Bone Marrow.

Acta cytologica
Morphological analysis of the bone marrow is an essential step in the diagnosis of hematological disease. The conventional analysis of bone marrow smears is performed under a manual microscope, which is labor-intensive and subject to interobserver va...

[Establishment of New Zealand rabbit models of aplastic anemia].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVE: To screen for the optimal dose of benzene and cyclophosphamide using an orthogonal design for establishment of New Zealand rabbit models of aplastic anemia.