AIMC Topic: Bone Marrow
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DeepHeme, a high-performance, generalizable deep ensemble for bone marrow morphometry and hematologic diagnosis.
Science translational medicine
Jun 11, 2025
Cytomorphological analysis of the bone marrow aspirate (BMA) is pivotal for the diagnostic workup of a broad range of hematological disorders. However, this skill is error prone, highly complex, and time consuming. Deep learning-based models for the ...
Using artificial intelligence-based software for an unbiased discrimination of immune cell subtypes in the fracture hematoma and bone marrow of non-osteoporotic and osteoporotic mice.
PloS one
Apr 29, 2025
It is well established that the early inflammatory response following fracture is essential for initiating subsequent bone regeneration. An imbalance in inflammation, whether within the innate or adaptive immune response, can result in impaired fract...
Multimodal representations of transfer learning with snake optimization algorithm on bone marrow cell classification using biomedical histopathological images.
Scientific reports
Apr 24, 2025
Bone marrow (BM) plays a crucial role in the hematopoietic process, producing all of the body's blood cells and maintaining the overall immune and health system. Red and yellow BM are the two various kinds of BM. A comprehensive identification of the...
Development and validation of a nomogram for predicting bone marrow involvement in lymphoma patients based on F-FDG PET radiomics and clinical factors.
Annals of nuclear medicine
Mar 29, 2025
OBJECTIVE: This study aimed to develop and validate a nomogram combining F-FDG PET radiomics and clinical factors to non-invasively predict bone marrow involvement (BMI) in patients with lymphoma.
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
Mar 29, 2025
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...
Improved MRI detection of inflammation-induced changes in bone marrow microstructure in mice: a machine learning-enhanced T2 distribution analysis.
European radiology experimental
Mar 26, 2025
BACKGROUND: We investigated inflammation-induced changes in femoral hematopoietic bone marrow using advanced magnetic resonance imaging (MRI) techniques, including T2-weighted imaging, scalar T2 mapping, and machine learning-enhanced T2 distribution ...
Deep learning and genome-wide association meta-analyses of bone marrow adiposity in the UK Biobank.
Nature communications
Jan 2, 2025
Bone marrow adipose tissue is a distinct adipose subtype comprising more than 10% of fat mass in healthy humans. However, the functions and pathophysiological correlates of this tissue are unclear, and its genetic determinants remain unknown. Here, w...
Development and validation of a deep learning model for morphological assessment of myeloproliferative neoplasms using clinical data and digital pathology.
British journal of haematology
Dec 10, 2024
The subjectivity of morphological assessment and the overlapping pathological features of different subtypes of myeloproliferative neoplasms (MPNs) make accurate diagnosis challenging. To improve the pathological assessment of MPNs, we developed a di...
Machine learning based on multiplatform tests assists in subtype classification of mature B-cell neoplasms.
British journal of haematology
Dec 3, 2024
Mature B-cell neoplasms (MBNs) are clonal proliferative diseases encompassing over 40 subtypes. The WHO classification (morphology, immunology, cytogenetics and molecular biology) provides comprehensive diagnostic understandings. However, MBN subtypi...
Lymphoma, Mantle-Cell
Leukemia, Hairy Cell
Waldenstrom Macroglobulinemia
Lymphoma, B-Cell
Neprilysin
Lymphoma, Follicular
CD5 Antigens
Bone Marrow
Leukemia, Lymphocytic, Chronic, B-Cell
High-Throughput Nucleotide Sequencing
Humans
East Asian People
Immunohistochemistry
Machine Learning
Mutation
Retrospective Studies
Flow Cytometry
Automatic segmentation and visualization of cortical and marrow bone in mandibular condyle on CBCT: a preliminary exploration of clinical application.
Oral radiology
Nov 9, 2024
OBJECTIVES: To develop a deep learning-based automatic segmentation method for cortex and marrow in mandibular condyle on cone-beam computed tomography (CBCT) images and explore its clinical application.
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