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

You might also read

Related Articles

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

Sort by
Same author

SIGNAL: A Scalable, Real-World Model for Rapid Intraoperative Molecular Classification of Gliomas Using Stimulated Raman Histology.

medRxiv : the preprint server for health sciences·2026
Same author

Anatomic Predilection of Isocitrate Dehydrogenase-Mutant Gliomas: A Multi-Institutional Spatial Analysis.

Neurosurgery·2026
Same author

Natural Language Processing Methods Automate Molecular Marker Extraction From Glioma Pathology Reports.

Neurosurgery·2026
Same author

Minimizing the risks of stereotactic brain biopsy in suspected central nervous system lymphoma: a retrospective database study.

Journal of cancer research and clinical oncology·2026
Same author

AI-driven label-free Raman spectromics for intraoperative spinal tumor assessment.

NPJ digital medicine·2026
Same author

The Intraoperative Utility of Raman Spectroscopy for Neurosurgical Oncology.

Cancers·2025
Same journal

Spatially defined microenvironmental niches are associated with clinical outcome and tumor ecosystem diversity in head and neck cancer.

Med (New York, N.Y.)·2026
Same journal

AI-driven therapeutic antisense oligonucleotide for processing-deficient progeroid laminopathies.

Med (New York, N.Y.)·2026
Same journal

Advanced cholangiocarcinoma in 2025: Therapeutic sequencing and global implementation.

Med (New York, N.Y.)·2026
Same journal

Atlas of human brain imaging-derived phenotypes and disease risk.

Med (New York, N.Y.)·2026
Same journal

Withdrawal effects following treatment discontinuation: A blind spot in evidence-based medicine.

Med (New York, N.Y.)·2026
Same journal

Rethinking parenteral nutrition as supportive therapy for neonatal sepsis.

Med (New York, N.Y.)·2026
See all related articles

Related Experiment Video

Updated: Jul 19, 2025

Laser Capture Microdissection of Glioma Subregions for Spatial and Molecular Characterization of Intratumoral Heterogeneity, Oncostreams, and Invasion
09:09

Laser Capture Microdissection of Glioma Subregions for Spatial and Molecular Characterization of Intratumoral Heterogeneity, Oncostreams, and Invasion

Published on: April 12, 2020

6.9K

Unlocking glioma genetics with deep learning.

Daniel A Orringer1, Todd C Hollon2

  • 1Departments of Neurosurgery and Pathology, Perlmutter Cancer Center, NYU Langone Health, New York, NY, USA.

Med (New York, N.Y.)
|August 12, 2023
PubMed
Summary
This summary is machine-generated.

The CHARM artificial intelligence (AI) algorithm can improve glioma diagnosis and treatment. This AI tool streamlines molecular classification, intraoperative diagnosis, surgical decisions, and clinical trial enrollment for patients.

More Related Videos

Evaluation of Biomarkers in Glioma by Immunohistochemistry on Paraffin-Embedded 3D Glioma Neurosphere Cultures
06:32

Evaluation of Biomarkers in Glioma by Immunohistochemistry on Paraffin-Embedded 3D Glioma Neurosphere Cultures

Published on: January 9, 2019

7.9K
Transposon Mediated Integration of Plasmid DNA into the Subventricular Zone of Neonatal Mice to Generate Novel Models of Glioblastoma
10:58

Transposon Mediated Integration of Plasmid DNA into the Subventricular Zone of Neonatal Mice to Generate Novel Models of Glioblastoma

Published on: February 22, 2015

13.0K

Related Experiment Videos

Last Updated: Jul 19, 2025

Laser Capture Microdissection of Glioma Subregions for Spatial and Molecular Characterization of Intratumoral Heterogeneity, Oncostreams, and Invasion
09:09

Laser Capture Microdissection of Glioma Subregions for Spatial and Molecular Characterization of Intratumoral Heterogeneity, Oncostreams, and Invasion

Published on: April 12, 2020

6.9K
Evaluation of Biomarkers in Glioma by Immunohistochemistry on Paraffin-Embedded 3D Glioma Neurosphere Cultures
06:32

Evaluation of Biomarkers in Glioma by Immunohistochemistry on Paraffin-Embedded 3D Glioma Neurosphere Cultures

Published on: January 9, 2019

7.9K
Transposon Mediated Integration of Plasmid DNA into the Subventricular Zone of Neonatal Mice to Generate Novel Models of Glioblastoma
10:58

Transposon Mediated Integration of Plasmid DNA into the Subventricular Zone of Neonatal Mice to Generate Novel Models of Glioblastoma

Published on: February 22, 2015

13.0K

Area of Science:

  • Oncology
  • Medical Artificial Intelligence (AI)
  • Bioinformatics

Background:

  • The integration of artificial intelligence (AI) into medicine offers novel avenues for enhancing disease diagnosis and treatment strategies.
  • Gliomas, a type of brain tumor, present complex diagnostic and treatment challenges that could benefit from advanced computational approaches.

Purpose of the Study:

  • To introduce CHARM, a novel AI algorithm designed to optimize the management of glioma patients.
  • To highlight the potential of CHARM in improving key aspects of glioma care, including classification, diagnosis, surgical planning, and clinical trial participation.

Main Methods:

  • Development and description of the CHARM AI algorithm.
  • Evaluation of CHARM's capabilities in streamlining molecular classification, intraoperative diagnosis, surgical decision-making, and patient enrollment in clinical trials for glioma.

Main Results:

  • CHARM demonstrates potential in enhancing the efficiency and accuracy of molecular classification for gliomas.
  • The algorithm shows promise in improving intraoperative diagnosis and informing surgical decision-making processes.
  • CHARM may facilitate streamlined patient enrollment into relevant clinical trials, accelerating research and treatment advancements.

Conclusions:

  • The CHARM AI algorithm represents a significant advancement in applying artificial intelligence to neuro-oncology.
  • CHARM has the potential to revolutionize glioma patient management by optimizing critical diagnostic and therapeutic decision points.