AIMC Topic: Isocitrate Dehydrogenase
Clear Filters Showing 41 to 50 of 67 articles
A Multiple-Instance Learning-Based Convolutional Neural Network Model to Detect the Mutation in the Histopathology Images of Glioma Tissues.
Journal of computational biology : a journal of computational molecular cell biology
Jan 3, 2020
Prediction of IDH and TERT promoter mutations in low-grade glioma from magnetic resonance images using a convolutional neural network.
Scientific reports
Dec 30, 2019
Identification of genotypes is crucial for treatment of glioma. Here, we developed a method to predict tumor genotypes using a pretrained convolutional neural network (CNN) from magnetic resonance (MR) images and compared the accuracy to that of a di...
Machine learning-based quantitative texture analysis of conventional MRI combined with ADC maps for assessment of IDH1 mutation in high-grade gliomas.
Japanese journal of radiology
Nov 18, 2019
PURPOSE: To assess the performance of texture analysis of conventional magnetic resonance imaging (MRI) and apparent diffusion coefficient (ADC) maps in predicting IDH1 status in high-grade gliomas (HGG).
Predicting the 1p/19q Codeletion Status of Presumed Low-Grade Glioma with an Externally Validated Machine Learning Algorithm.
Clinical cancer research : an official journal of the American Association for Cancer Research
Sep 23, 2019
PURPOSE: Patients with 1p/19q codeleted low-grade glioma (LGG) have longer overall survival and better treatment response than patients with 1p/19q intact tumors. Therefore, it is relevant to know the 1p/19q status. To investigate whether the 1p/19q ...
Prediction of IDH1 Mutation Status in Glioblastoma Using Machine Learning Technique Based on Quantitative Radiomic Data.
World neurosurgery
Feb 5, 2019
OBJECTIVE: Isocitrate dehydrogenase 1 (IDH1) mutation status is an independent favorable prognostic factor for glioblastoma (GBM) and is usually determined by sequencing or immunohistochemistry. An accurate prediction of IDH1 mutation status via noni...
Radiomics-based machine learning methods for isocitrate dehydrogenase genotype prediction of diffuse gliomas.
Journal of cancer research and clinical oncology
Feb 4, 2019
PURPOSE: Reliable and accurate predictive models are necessary to drive the success of radiomics. Our aim was to identify the optimal radiomics-based machine learning method for isocitrate dehydrogenase (IDH) genotype prediction in diffuse gliomas.
Contrast enhancement is a prognostic factor in IDH1/2 mutant, but not in wild-type WHO grade II/III glioma as confirmed by machine learning.
European journal of cancer (Oxford, England : 1990)
Dec 7, 2018
BACKGROUND: Mutation of the isocitrate dehydrogenase (IDH) gene and co-deletion on chromosome 1p/19q is becoming increasingly relevant for the evaluation of clinical outcome in glioma. Among the imaging parameters, contrast enhancement (CE) in WHO II...
Machine learning: a useful radiological adjunct in determination of a newly diagnosed glioma's grade and IDH status.
Journal of neuro-oncology
May 16, 2018
INTRODUCTION: Machine learning methods have been introduced as a computer aided diagnostic tool, with applications to glioma characterisation on MRI. Such an algorithmic approach may provide a useful adjunct for a rapid and accurate diagnosis of a gl...
Deep-Learning Convolutional Neural Networks Accurately Classify Genetic Mutations in Gliomas.
AJNR. American journal of neuroradiology
May 10, 2018
BACKGROUND AND PURPOSE: The World Health Organization has recently placed new emphasis on the integration of genetic information for gliomas. While tissue sampling remains the criterion standard, noninvasive imaging techniques may provide complimenta...
Texture analysis- and support vector machine-assisted diffusional kurtosis imaging may allow in vivo gliomas grading and IDH-mutation status prediction: a preliminary study.
Scientific reports
Apr 17, 2018
We sought to investigate, whether texture analysis of diffusional kurtosis imaging (DKI) enhanced by support vector machine (SVM) analysis may provide biomarkers for gliomas staging and detection of the IDH mutation. First-order statistics and textur...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31984
- Neural Networks, Computer 30211
- Algorithms 27388
- Deep Learning 26888
- Artificial Intelligence 24826
- Robotics 13382
- Image Processing, Computer-Assisted 9732
- Retrospective Studies 9334
- Magnetic Resonance Imaging 6342
- Reproducibility of Results 5670
- Tomography, X-Ray Computed 4864
- Support Vector Machine 4766
- Computational Biology 4331
- Brain 4126
- Computer Simulation 3932
Recent Journals
- Scientific reports 6743
- Sensors (Basel, Switzerland) 4794
- PloS one 4196
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1916
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1378
- IEEE journal of biomedical and health informatics 1170
- Journal of chemical information and modeling 1064
- Nature communications 1039
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 873
- Journal of medical Internet research 860
- Briefings in bioinformatics 853