AIMC Topic: Tumor Suppressor Proteins

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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.
Prognosis Female Aged Adult Radiomics Brain Neoplasms Humans Neural Networks, Computer DNA Modification Methylases DNA Repair Enzymes Tumor Suppressor Proteins Semantics Isocitrate Dehydrogenase X-linked Nuclear Protein Male Middle Aged Deep Learning Magnetic Resonance Imaging Glioblastoma Mutation
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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 ...
Radiotherapy Isocitrate Dehydrogenase Karnofsky Performance Status Deep Learning Age Factors Predictive Value of Tests Glioblastoma Bayes Theorem Sex Factors Female Survival Analysis Aged DNA Modification Methylases Adult DNA Repair Enzymes Humans Brain Neoplasms Tumor Suppressor Proteins Male Retrospective Studies Proportional Hazards Models Middle Aged Chemoradiotherapy
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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.
Humans Neural Networks, Computer Reproducibility of Results Deep Learning Glioma Magnetic Resonance Imaging DNA Methylation Area Under Curve DNA Modification Methylases Aged Adult Sensitivity and Specificity Brain Neoplasms Male Middle Aged DNA Repair Enzymes Tumor Suppressor Proteins 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 Methylation Glioblastoma Survival Analysis DNA Modification Methylases DNA Repair Enzymes Tumor Suppressor Proteins Semantics Promoter Regions, Genetic Adult Brain Neoplasms Male Middle Aged Humans Image Processing, Computer-Assisted Machine Learning Magnetic Resonance Imaging Retrospective Studies Female 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...
ROC Curve DNA Repair Enzymes Magnetic Resonance Imaging Humans Tumor Suppressor Proteins DNA Methylation Brain Promoter Regions, Genetic Glioblastoma Imaging Genomics Brain Neoplasms Image Interpretation, Computer-Assisted Deep Learning DNA Modification Methylases
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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...
Uveal Neoplasms Ubiquitin Thiolesterase Uveal Melanoma Adult Deep Learning Tumor Suppressor Proteins Eosine Yellowish-(YS) Hematoxylin Humans Artificial Intelligence 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...
Humans Sensitivity and Specificity Brain Neoplasms Neoplasm Recurrence, Local Progression-Free Survival DNA Methylation Tumor Suppressor Proteins Deep Learning Positron-Emission Tomography Diagnosis, Differential Neuroimaging Radiotherapy Planning, Computer-Assisted Image Processing, Computer-Assisted Neoplasm Proteins DNA Modification Methylases Computational Biology Radiosurgery Glioblastoma Glioma Magnetic Resonance Imaging Promoter Regions, Genetic DNA Repair Enzymes Isocitrate Dehydrogenase Radiation Oncology Neoplasm Grading Imaging Genomics
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Analysis of gene expression profiles of lung cancer subtypes with machine learning algorithms.

Biochimica et biophysica acta. Molecular basis of disease Apr 28, 2020
Lung cancer is one of the most common cancer types worldwide and causes more than one million deaths annually. Lung adenocarcinoma (AC) and lung squamous cell cancer (SCC) are two major lung cancer subtypes and have different characteristics in sever...
Cystatin A Adenosine Triphosphatases Terminology as Topic Membrane Transport Proteins Monte Carlo Method Carcinoma, Squamous Cell Serpins Gene Expression Profiling Adenocarcinoma of Lung Transcriptome Transcription Factors Lung Neoplasms Diagnosis, Differential Computational Biology Humans Cadherins Gene Expression Regulation, Neoplastic Machine Learning Datasets as Topic Tumor Suppressor Proteins
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Comprehensive Molecular and Pathologic Evaluation of Transitional Mesothelioma Assisted by Deep Learning Approach: A Multi-Institutional Study of the International Mesothelioma Panel from the MESOPATH Reference Center.

Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer Mar 9, 2020
INTRODUCTION: Histologic subtypes of malignant pleural mesothelioma are a major prognostic indicator and decision denominator for all therapeutic strategies. In an ambiguous case, a rare transitional mesothelioma (TM) pattern may be diagnosed by path...
Humans Deep Learning Lung Neoplasms Mesothelioma Tumor Suppressor Proteins Homozygote Sequence Deletion Ubiquitin Thiolesterase
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A 21‑gene Support Vector Machine classifier and a 10‑gene risk score system constructed for patients with gastric cancer.

Molecular medicine reports Nov 21, 2019
Gastric cancer (GC) ranks fifth in terms of incidence and third in terms of tumor mortality worldwide. The present study was designed to construct a Support Vector Machine (SVM) classifier and risk score system for GC. The GSE62254 (training set) and...
Angiopoietin-Like Protein 1 Gene Expression Regulation, Neoplastic Membrane Proteins Support Vector Machine Databases, Genetic Aged Carrier Proteins Stomach Neoplasms Humans Male Nerve Tissue Proteins Cytokines Middle Aged Neoplasm Recurrence, Local Prognosis Gene Expression Profiling Tumor Suppressor Proteins Female Gene Regulatory Networks Kaplan-Meier Estimate Risk Factors Angiopoietin-like Proteins A Kinase Anchor Proteins
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