AIMC Topic: Glioma

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Deep Learning Glioma Grading with the Tumor Microenvironment Analysis Protocol for Comprehensive Learning, Discovering, and Quantifying Microenvironmental Features.

Journal of imaging informatics in medicine Feb 27, 2024
Gliomas are primary brain tumors that arise from neural stem cells, or glial precursors. Diagnosis of glioma is based on histological evaluation of pathological cell features and molecular markers. Gliomas are infiltrated by myeloid cells that accumu...
Humans Tumor Microenvironment Brain Neoplasms Image Interpretation, Computer-Assisted Deep Learning Glioma Neoplasm Grading
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Quantitative and Visual Analysis of Data Augmentation and Hyperparameter Optimization in Deep Learning-Based Segmentation of Low-Grade Glioma Tumors Using Grad-CAM.

Annals of biomedical engineering Feb 26, 2024
This study executes a quantitative and visual investigation on the effectiveness of data augmentation and hyperparameter optimization on the accuracy of deep learning-based segmentation of LGG tumors. The study employed the MobileNetV2 and ResNet bac...
Humans Brain Neoplasms Deep Learning Image Processing, Computer-Assisted Glioma
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Auto-segmentation of Adult-Type Diffuse Gliomas: Comparison of Transfer Learning-Based Convolutional Neural Network Model vs. Radiologists.

Journal of imaging informatics in medicine Feb 21, 2024
Segmentation of glioma is crucial for quantitative brain tumor assessment, to guide therapeutic research and clinical management, but very time-consuming. Fully automated tools for the segmentation of multi-sequence MRI are needed. We developed and p...
Image Interpretation, Computer-Assisted Brain Neoplasms Male Middle Aged Neural Networks, Computer Humans Magnetic Resonance Imaging Female Deep Learning Radiologists Adult Glioma
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Development and internal validation of machine learning models for personalized survival predictions in spinal cord glioma patients.

The spine journal : official journal of the North American Spine Society Feb 15, 2024
BACKGROUND CONTEXT: Numerous factors have been associated with the survival outcomes in patients with spinal cord gliomas (SCG). Recognizing these specific determinants is crucial, yet it is also vital to establish a reliable and precise prognostic m...
Prognosis Retrospective Studies Female Humans Machine Learning Middle Aged Glioma Survival Analysis Spinal Cord Neoplasms Aged Adult Male
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Added value of dynamic contrast-enhanced MR imaging in deep learning-based prediction of local recurrence in grade 4 adult-type diffuse gliomas patients.

Scientific reports Jan 25, 2024
Local recurrences in patients with grade 4 adult-type diffuse gliomas mostly occur within residual non-enhancing T2 hyperintensity areas after surgical resection. Unfortunately, it is challenging to distinguish non-enhancing tumors from edema in the ...
Magnetic Resonance Imaging Deep Learning Humans Glioblastoma Adult Glioma Brain Neoplasms Contrast Media
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GlioPredictor: a deep learning model for identification of high-risk adult IDH-mutant glioma towards adjuvant treatment planning.

Scientific reports Jan 25, 2024
Identification of isocitrate dehydrogenase (IDH)-mutant glioma patients at high risk of early progression is critical for radiotherapy treatment planning. Currently tools to stratify risk of early progression are lacking. We sought to identify a comb...
Adjuvants, Pharmaceutic ErbB Receptors Isocitrate Dehydrogenase Cyclin-Dependent Kinase Inhibitor Proteins Glioma DNA Copy Number Variations Adjuvants, Immunologic Humans Adult Deep Learning
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Integrating Machine Learning and Mendelian Randomization Determined a Functional Neurotrophin-Related Gene Signature in Patients with Lower-Grade Glioma.

Molecular biotechnology Jan 23, 2024
Recent researches reported that neurotrophins can promote glioma growth/invasion but the relevant model for predicting patients' survival in Lower-Grade Gliomas (LGGs) lacked. In this study, we adopted univariate Cox analysis, LASSO regression, and m...
Nerve Growth Factors Sulfotransferases Neoplasm Grading Proportional Hazards Models Homeodomain Proteins Glioma DNA Copy Number Variations Mendelian Randomization Analysis Machine Learning Prognosis Female Polymorphism, Single Nucleotide Gene Expression Regulation, Neoplastic Brain Neoplasms Male Humans
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Therapy-induced modulation of tumor vasculature and oxygenation in a murine glioblastoma model quantified by deep learning-based feature extraction.

Scientific reports Jan 23, 2024
Glioblastoma presents characteristically with an exuberant, poorly functional vasculature that causes malperfusion, hypoxia and necrosis. Despite limited clinical efficacy, anti-angiogenesis resulting in vascular normalization remains a promising the...
Animals Deep Learning Glioblastoma Hypoxia Mice Immunotherapy Glioma
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Noninvasive Isocitrate Dehydrogenase 1 Status Prediction in Grade II/III Glioma Based on Magnetic Resonance Images: A Transfer Learning Strategy.

Journal of computer assisted tomography Jan 16, 2024
OBJECTIVE: The aim of this study was to evaluate transfer learning combined with various convolutional neural networks (TL-CNNs) in predicting isocitrate dehydrogenase 1 ( IDH1 ) status of grade II/III gliomas.
Male Humans Neural Networks, Computer Middle Aged Machine Learning Glioma Infant Infant, Newborn Magnetic Resonance Imaging Adolescent Young Adult Female Neoplasm Grading Child, Preschool Adult Isocitrate Dehydrogenase Child
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Approaching expert-level accuracy for differentiating ACL tear types on MRI with deep learning.

Scientific reports Jan 10, 2024
Treatment for anterior cruciate ligament (ACL) tears depends on the condition of the ligament. We aimed to identify different tear statuses from preoperative MRI using deep learning-based radiomics with sex and age. We reviewed 862 patients with preo...
Magnetic Resonance Imaging Anterior Cruciate Ligament Injuries Anterior Cruciate Ligament Reconstruction Humans Brain Neoplasms Deep Learning Glioma
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