ArticleFrontiers in oncology2021
Detection of Metastatic Tumor Cells in the Bone Marrow Aspirate Smears by Artificial Intelligence (AI)-Based
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.
- Artificial intelligence in cytopathological applications for cancer: a review of accuracy and analytic validity.European journal of medical research · 2024Pooled it
- Transfer RNA-Derived Small RNA-5'tiRNAGln Drives HNRNPC Phase Separation to Promote Breast Cancer Bone Metastasis by Regulating IGF1R.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Interpretative diagnostic model for neuroblastoma metastases using bone marrow cytology.Journal of translational medicine · 2026Article
- Comprehensive performance assessment of the BMIA-12 a system for bone marrow cell quantification in normal and hematological malignancy samples.Scientific reports · 2026Article
- PredictingiScience · 2025Article
- The utility of automated artificial intelligence-assisted digital cytomorphology for bone marrow analysis in diagnostic haemato-oncology.Clinical and translational medicine · 2025Article
- Real-World Application of Digital Morphology Analyzers: Practical Issues and Challenges in Clinical Laboratories.Diagnostics (Basel, Switzerland) · 2025Review
- Challenges and Clinical Relevance in Diagnosing Metastatic Cells From Non-Hematopoietic Malignancies in Bone Marrow Aspirates.Cancer medicine · 2025Article
- Optimization of diagnosis and treatment of hematological diseases via artificial intelligence.Frontiers in medicine · 2024Review
- Review
- High-accuracy morphological identification of bone marrow cells using deep learning-based Morphogo system.Scientific reports · 2023Article
- Artificial Intelligence-Assisted Diagnostic Cytology and Genomic Testing for Hematologic Disorders.Cells · 2023Review
- Cytomorphological evaluation of non-haematopoietic malignancies metastasizing to the bone marrow.American journal of blood research · 2023Review
- Cytopathology 2.0: How Artificial Intelligence Is Redefining the Future of Cytopathology.Journal of cytologyReview
- Bone marrow metastasis in nonhematological malignancies: A study from tertiary care center.Annals of African medicineArticle
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionMetastatic carcinomas of bone marrow (MCBM) are characterized as tumors of non-hematopoietic origin spreading to the bone marrow through blood or lymphatic circulation. The diagnosis is critical for tumor staging, treatment selection and prognostic risk stratification. However, the identification of metastatic carcinoma cells on bone marrow aspiration smears is technically challenging by conventional microscopic screening.
objectiveThe aim of this study is to develop an automatic recognition system using deep learning algorithms applied to bone marrow cells image analysis. The system takes advantage of an artificial intelligence (AI)-based method in recognizing metastatic atypical cancer clusters and promoting rapid diagnosis.
methodsWe retrospectively reviewed metastatic non-hematopoietic malignancies in bone marrow aspirate smears collected from 60 cases of patients admitted to Zhongshan Hospital. High resolution digital bone marrow aspirate smear images were generated and automatically analyzed by
results
conclusionIn patients with clinical history of cancer, the
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