AIMC Topic: Bone Marrow Cells

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Methodologies and Emerging Technologies for the Evaluation of the Hematopoietic System.

Toxicologic pathology
Hematology and bone marrow analysis is central to our understanding of the hematopoietic system and how it responds to insults, and this session presented during the 2022 STP symposium provided a review of current and novel approaches for the evaluat...

Evaluation of two semi-supervised learning methods and their combination for automatic classification of bone marrow cells.

Scientific reports
Differential bone marrow (BM) cell counting is an important test for the diagnosis of various hematological diseases. However, it is difficult to accurately classify BM cells due to non-uniformity and the lack of reproducibility of differential count...

A method to classify bone marrow cells with rejected option.

Biomedizinische Technik. Biomedical engineering
Bone marrow cell morphology has always been an important tool for the diagnosis of blood diseases. Still, it requires years of experience from a suitable person. Furthermore, the outcomes of their recognition are subjective and there is no objective ...

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...

Machine learning assisted real-time deformability cytometry of CD34+ cells allows to identify patients with myelodysplastic syndromes.

Scientific reports
Diagnosis of myelodysplastic syndrome (MDS) mainly relies on a manual assessment of the peripheral blood and bone marrow cell morphology. The WHO guidelines suggest a visual screening of 200 to 500 cells which inevitably turns the assessor blind to r...

Using deep learning for quantification of cellularity and cell lineages in bone marrow biopsies and comparison to normal age-related variation.

Pathology
Cellularity estimation forms an important aspect of the visual examination of bone marrow biopsies. In clinical practice, cellularity is estimated by eye under a microscope, which is rapid, but subjective and subject to inter- and intraobserver varia...

Deep learning for bone marrow cell detection and classification on whole-slide images.

Medical image analysis
Bone marrow (BM) examination is an essential step in both diagnosing and managing numerous hematologic disorders. BM nucleated differential count (NDC) analysis, as part of BM examination, holds the most fundamental and crucial information. However, ...

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...

Evaluation of an open-source machine-learning tool to quantify bone marrow plasma cells.

Journal of clinical pathology
AIMS: The objective of this study was to develop and validate an open-source digital pathology tool, QuPath, to automatically quantify CD138-positive bone marrow plasma cells (BMPCs).

Screening For Bone Marrow Cellularity Changes in Cynomolgus Macaques in Toxicology Safety Studies Using Artificial Intelligence Models.

Toxicologic pathology
Many compounds affect the cellularity of hematolymphoid organs including bone marrow. Toxicologic pathologists are tasked with their evaluation as part of safety studies. An artificial intelligence (AI) tool could provide diagnostic support for the p...