AIMC Topic: Isocitrate Dehydrogenase
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Insight into deep learning for glioma IDH medical image analysis: A systematic review.
Medicine
Feb 16, 2024
BACKGROUND: Deep learning techniques explain the enormous potential of medical image analysis, particularly in digital pathology. Concurrently, molecular markers have gained increasing significance over the past decade in the context of glioma patien...
Medical Statistics Unlock the Gateway to Further Research: Using Deep Learning to Predict CDKN2A/B Homozygous Deletion in Isocitrate Dehydrogenase-Mutant Astrocytoma.
Korean journal of radiology
Dec 1, 2023
Response to "Medical Statistics Unlock the Gateway to Further Research: Using Deep Learning to Predict CDKN2A/B Homozygous Deletion in Isocitrate Dehydrogenase-Mutant Astrocytoma".
Korean journal of radiology
Dec 1, 2023
[A Dual-Aware deep learning framework for identification of glioma isocitrate dehydrogenase genotype using magnetic resonance amide proton transfer modalities].
Nan fang yi ke da xue xue bao = Journal of Southern Medical University
Aug 20, 2023
OBJECTIVE: To propose a Dual-Aware deep learning framework for genotyping of isocitrate dehydrogenase (IDH) in gliomas based on magnetic resonance amide proton transfer (APT) modality data as a means to assist non-invasive diagnosis of gliomas.
Code-free machine learning for classification of central nervous system histopathology images.
Journal of neuropathology and experimental neurology
Feb 21, 2023
Machine learning (ML), an application of artificial intelligence, is currently transforming the analysis of biomedical data and specifically of biomedical images including histopathology. The promises of this technology contrast, however, with its cu...
Combined molecular subtyping, grading, and segmentation of glioma using multi-task deep learning.
Neuro-oncology
Feb 14, 2023
BACKGROUND: Accurate characterization of glioma is crucial for clinical decision making. A delineation of the tumor is also desirable in the initial decision stages but is time-consuming. Previously, deep learning methods have been developed that can...
Improving the noninvasive classification of glioma genetic subtype with deep learning and diffusion-weighted imaging.
Neuro-oncology
Apr 1, 2022
BACKGROUND: Diagnostic classification of diffuse gliomas now requires an assessment of molecular features, often including IDH-mutation and 1p19q-codeletion status. Because genetic testing requires an invasive process, an alternative noninvasive appr...
Fully automated hybrid approach to predict the IDH mutation status of gliomas via deep learning and radiomics.
Neuro-oncology
Feb 25, 2021
BACKGROUND: Glioma prognosis depends on isocitrate dehydrogenase (IDH) mutation status. We aimed to predict the IDH status of gliomas from preoperative MR images using a fully automated hybrid approach with convolutional neural networks (CNNs) and ra...
A novel fully automated MRI-based deep-learning method for classification of IDH mutation status in brain gliomas.
Neuro-oncology
Mar 5, 2020
BACKGROUND: Isocitrate dehydrogenase (IDH) mutation status has emerged as an important prognostic marker in gliomas. Currently, reliable IDH mutation determination requires invasive surgical procedures. The purpose of this study was to develop a high...
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