Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Bone Marrow Sampling and Transplants01:22

Bone Marrow Sampling and Transplants

3.0K
Bone marrow transplant is a potential cure for several diseases, including cancer and specific genetic disorders. Notably, this procedure is applicable for patients suffering from aplastic anemia, certain types of leukemia, severe combined immunodeficiency disease (SCID), Hodgkin's disease, non-Hodgkin's lymphoma, multiple myeloma, thalassemia, sickle-cell disease, and certain cancers.
The transplant begins with high doses of chemotherapy and radiation treatment, which aim to destroy...
3.0K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Ultrasound-driven microbubble motors for targeted myocardial ischemia-reperfusion injury treatment.

Materials today. Bio·2026
Same author

Clinical Characteristics and Prognostic Risk Factors in Breast Cancer With Liver Metastasis.

The breast journal·2026
Same author

Albumin Concentration Associates Linearly with Unfavorable Outcomes at Three Months Post-Acute Ischemic Stroke in Koreans.

Clinical laboratory·2026
Same author

Spatially Strengthened Ion-Dipole Electrolyte Enables High-Temperature Anode-Free Sodium Batteries.

Advanced materials (Deerfield Beach, Fla.)·2026
Same author

Oral health knowledge, attitudes, and practices and associated factors among non-dental healthcare professionals in South China: a cross-sectional study.

Frontiers in public health·2026
Same author

Prediction of venous thromboembolism after spontaneous intracerebral hemorrhage based on machine learning.

Journal of thrombosis and thrombolysis·2026

Related Experiment Video

Updated: May 1, 2026

Comprehensive Protocol to Sample and Process Bone Marrow for Measuring Measurable Residual Disease and Leukemic Stem Cells in Acute Myeloid Leukemia
09:57

Comprehensive Protocol to Sample and Process Bone Marrow for Measuring Measurable Residual Disease and Leukemic Stem Cells in Acute Myeloid Leukemia

Published on: March 5, 2018

29.2K

Artificial intelligence-based quantitative bone marrow pathology analysis for myeloproliferative neoplasms.

Dandan Yu1, Hongju Zhang2, Yanyan Song2

  • 1State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Key Laboratory of Gene Therapy for Blood Diseases, CAMS Key Laboratory of Gene Therapy for Blood Diseases, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China; School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730.

Haematologica
|June 12, 2025
PubMed
Summary

An AI platform quantitatively analyzes bone marrow pathology for diagnosing myeloproliferative neoplasms (MPNs). This objective approach enhances MPN classification accuracy, aiding hematopathologists in diagnosis.

More Related Videos

Database-guided Flow-cytometry for Evaluation of Bone Marrow Myeloid Cell Maturation
12:05

Database-guided Flow-cytometry for Evaluation of Bone Marrow Myeloid Cell Maturation

Published on: November 3, 2018

11.6K
Intracellular Phosphoflow Cytometry of Acute Myeloid Leukemia Patient-Derived Xenotransplants
07:39

Intracellular Phosphoflow Cytometry of Acute Myeloid Leukemia Patient-Derived Xenotransplants

Published on: June 6, 2025

39

Related Experiment Videos

Last Updated: May 1, 2026

Comprehensive Protocol to Sample and Process Bone Marrow for Measuring Measurable Residual Disease and Leukemic Stem Cells in Acute Myeloid Leukemia
09:57

Comprehensive Protocol to Sample and Process Bone Marrow for Measuring Measurable Residual Disease and Leukemic Stem Cells in Acute Myeloid Leukemia

Published on: March 5, 2018

29.2K
Database-guided Flow-cytometry for Evaluation of Bone Marrow Myeloid Cell Maturation
12:05

Database-guided Flow-cytometry for Evaluation of Bone Marrow Myeloid Cell Maturation

Published on: November 3, 2018

11.6K
Intracellular Phosphoflow Cytometry of Acute Myeloid Leukemia Patient-Derived Xenotransplants
07:39

Intracellular Phosphoflow Cytometry of Acute Myeloid Leukemia Patient-Derived Xenotransplants

Published on: June 6, 2025

39

Area of Science:

  • Hematology
  • Computational Pathology
  • Artificial Intelligence in Medicine

Background:

  • Accurate diagnosis and classification of myeloproliferative neoplasms (MPNs) rely on bone marrow pathology evaluation.
  • Morphological assessment of bone marrow trephine (BMT) sections is subjective, necessitating objective diagnostic systems.

Purpose of the Study:

  • To develop an automated quantitative analysis platform for BMT sections to improve MPN diagnosis and classification.
  • To enhance diagnostic accuracy by objectively analyzing bone marrow metrics.

Main Methods:

  • Developed an automated quantitative analysis platform using U2-Net, UNeXt, and ResNet for BMT sections.
  • Quantitatively analyzed bone marrow metrics: cellularity, M:E ratio, megakaryocyte features, and marrow fibrosis (MF) with ~0.9 accuracy and ~0.8 IoU.
  • Employed random forest classifiers to build bone marrow, clinical, and comprehensive classification models.

Main Results:

  • The automated platform achieved high accuracy in segmenting and identifying cells and tissues.
  • Bone marrow and comprehensive classification models demonstrated a macro-average AUC of 0.96 for differentiating MPN subtypes and nonneoplastic cases.
  • The clinical classification model achieved a macro-average AUC of 0.92.

Conclusions:

  • The developed platform provides highly accurate quantitative analysis of bone marrow pathology for MPN classification.
  • This AI-driven tool can serve as a valuable auxiliary diagnostic aid for hematopathologists in suspected MPN cases.