AIMC Topic: Tumor Suppressor Proteins

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Prediction of molecular subclasses of uveal melanoma by deep learning using routine haematoxylin-eosin-stained tissue slides.

Histopathology Jul 1, 2024
AIMS: Uveal melanoma has a high propensity to metastasize. Prognosis is associated with specific driver mutations and copy number variations, and these can only be obtained after genetic testing. In this study we evaluated the efficacy of patient out...
Melanoma Aged Aged, 80 and over Adult Male Middle Aged Humans Prognosis Retrospective Studies Female Hematoxylin RNA Splicing Factors Deep Learning Uveal Neoplasms Staining and Labeling Ubiquitin Thiolesterase Mutation Uveal Melanoma Phosphoproteins Eukaryotic Initiation Factor-1 Tumor Suppressor Proteins Eosine Yellowish-(YS)
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MGMT promoter methylation status prediction using MRI scans? An extensive experimental evaluation of deep learning models.

Medical image analysis Oct 6, 2023
The number of studies on deep learning for medical diagnosis is expanding, and these systems are often claimed to outperform clinicians. However, only a few systems have shown medical efficacy. From this perspective, we examine a wide range of deep l...
Methylation Humans Reproducibility of Results Aged Brain Neoplasms Deep Learning Magnetic Resonance Imaging Glioblastoma DNA Modification Methylases DNA Repair Enzymes Tumor Suppressor Proteins
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A Comparison of Three Different Deep Learning-Based Models to Predict the MGMT Promoter Methylation Status in Glioblastoma Using Brain MRI.

Journal of digital imaging Jan 5, 2023
Glioblastoma (GBM) is the most common primary malignant brain tumor in adults. The standard treatment for GBM consists of surgical resection followed by concurrent chemoradiotherapy and adjuvant temozolomide. O-6-methylguanine-DNA methyltransferase (...
Humans O(6)-Methylguanine-DNA Methyltransferase DNA Methylation Brain Glioblastoma Adult DNA Modification Methylases Brain Neoplasms DNA Repair Enzymes Deep Learning Tumor Suppressor Proteins Magnetic Resonance Imaging Temozolomide
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Predicting glioblastoma molecular subtypes and prognosis with a multimodal model integrating convolutional neural network, radiomics, and semantics.

Journal of neurosurgery Dec 2, 2022
OBJECTIVE: The aim of this study was to build a convolutional neural network (CNN)-based prediction model of glioblastoma (GBM) molecular subtype diagnosis and prognosis with multimodal features.
Aged Adult Radiomics Brain Neoplasms Male Middle Aged Humans Neural Networks, Computer Prognosis Female DNA Repair Enzymes Tumor Suppressor Proteins Semantics Isocitrate Dehydrogenase X-linked Nuclear Protein Deep Learning Magnetic Resonance Imaging Glioblastoma Mutation DNA Modification Methylases
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The role of deep learning-based survival model in improving survival prediction of patients with glioblastoma.

Cancer medicine Aug 28, 2021
This retrospective study has been conducted to validate the performance of deep learning-based survival models in glioblastoma (GBM) patients alongside the Cox proportional hazards model (CoxPH) and the random survival forest (RSF). Furthermore, the ...
Karnofsky Performance Status Glioblastoma Bayes Theorem Sex Factors Survival Analysis DNA Modification Methylases DNA Repair Enzymes Tumor Suppressor Proteins Proportional Hazards Models Chemoradiotherapy Brain Neoplasms Radiotherapy Isocitrate Dehydrogenase Male Middle Aged Humans Deep Learning Retrospective Studies Age Factors Female Predictive Value of Tests Aged Adult
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MRI-Based Deep-Learning Method for Determining Glioma Promoter Methylation Status.

AJNR. American journal of neuroradiology Mar 4, 2021
BACKGROUND AND PURPOSE: () promoter methylation confers an improved prognosis and treatment response in gliomas. We developed a deep learning network for determining promoter methylation status using T2 weighted Images (T2WI) only.
Male Middle Aged Deep Learning Glioma Neural Networks, Computer Humans DNA Methylation Magnetic Resonance Imaging Reproducibility of Results Area Under Curve Aged DNA Modification Methylases Adult DNA Repair Enzymes Sensitivity and Specificity Tumor Suppressor Proteins Brain Neoplasms Promoter Regions, Genetic
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Machine learning-based radiomic, clinical and semantic feature analysis for predicting overall survival and MGMT promoter methylation status in patients with glioblastoma.

Magnetic resonance imaging Sep 25, 2020
INTRODUCTION: Survival varies in patients with glioblastoma due to intratumoral heterogeneity and radiomics/imaging biomarkers have potential to demonstrate heterogeneity. The objective was to combine radiomic, semantic and clinical features to impro...
DNA Repair Enzymes Tumor Suppressor Proteins Semantics Promoter Regions, Genetic Image Processing, Computer-Assisted Magnetic Resonance Imaging Humans DNA Methylation Machine Learning Glioblastoma Retrospective Studies Survival Analysis Female DNA Modification Methylases Aged Adult Brain Neoplasms Male Middle Aged
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Automatic Prediction of MGMT Status in Glioblastoma via Deep Learning-Based MR Image Analysis.

BioMed research international Sep 23, 2020
Methylation of the O-methylguanine methyltransferase (MGMT) gene promoter is correlated with the effectiveness of the current standard of care in glioblastoma patients. In this study, a deep learning pipeline is designed for automatic prediction of M...
Magnetic Resonance Imaging Tumor Suppressor Proteins Humans DNA Methylation Promoter Regions, Genetic Brain Glioblastoma Imaging Genomics Brain Neoplasms Image Interpretation, Computer-Assisted Deep Learning DNA Modification Methylases ROC Curve DNA Repair Enzymes
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Piloting a Deep Learning Model for Predicting Nuclear BAP1 Immunohistochemical Expression of Uveal Melanoma from Hematoxylin-and-Eosin Sections.

Translational vision science & technology Sep 1, 2020
BACKGROUND: Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. Monosomy 3 and mutation are strong prognostic factors predicting metastatic risk in UM. Nuclear BAP1 (nBAP1) expression is a close immunohistochemical surro...
Humans Artificial Intelligence Melanoma Adult Deep Learning Tumor Suppressor Proteins Eosine Yellowish-(YS) Hematoxylin Uveal Neoplasms Ubiquitin Thiolesterase Uveal Melanoma
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Applications of radiomics and machine learning for radiotherapy of malignant brain tumors.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] May 11, 2020
BACKGROUND: Magnetic resonance imaging (MRI) and amino acid positron-emission tomography (PET) of the brain contain a vast amount of structural and functional information that can be analyzed by machine learning algorithms and radiomics for the use o...
Isocitrate Dehydrogenase Neoplasm Grading Humans DNA Repair Enzymes Imaging Genomics Neoplasm Recurrence, Local Sensitivity and Specificity Brain Neoplasms DNA Methylation Tumor Suppressor Proteins Progression-Free Survival Deep Learning Diagnosis, Differential Neuroimaging Positron-Emission Tomography Image Processing, Computer-Assisted Neoplasm Proteins Radiosurgery Radiotherapy Planning, Computer-Assisted Computational Biology Glioblastoma Promoter Regions, Genetic Glioma DNA Modification Methylases Radiation Oncology Magnetic Resonance Imaging
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