AIMC Topic: Mutation

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Deep Learning for Noninvasive Assessment of H3 K27M Mutation Status in Diffuse Midline Gliomas Using MR Imaging.

Journal of magnetic resonance imaging : JMRI Jan 24, 2023
BACKGROUND: Determination of H3 K27M mutation in diffuse midline glioma (DMG) is key for prognostic assessment and stratifying patient subgroups for clinical trials. MRI can noninvasively depict morphological and metabolic characteristics of H3 K27M ...
Glioma Magnetic Resonance Imaging Mutation Histones Spinal Cord Neoplasms Brain Neoplasms Male Deep Learning Prospective Studies Retrospective Studies Humans
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Editorial for "Deep Learning for Noninvasive Assessment of H3 K27M Mutation Status in Diffuse Midline Gliomas Using MR Imaging".

Journal of magnetic resonance imaging : JMRI Jan 20, 2023
Humans Brain Neoplasms Glioma Deep Learning Magnetic Resonance Imaging Mutation
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A radiomics-based deep learning approach to predict progression free-survival after tyrosine kinase inhibitor therapy in non-small cell lung cancer.

Cancer imaging : the official publication of the International Cancer Imaging Society Jan 20, 2023
BACKGROUND: The epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) are a first-line therapy for non-small cell lung cancer (NSCLC) with EGFR mutations. Approximately half of the patients with EGFR-mutated NSCLC are treated with...
Lung Neoplasms Carcinoma, Non-Small-Cell Lung Mutation Humans Deep Learning Protein Kinase Inhibitors Tyrosine Kinase Inhibitors Progression-Free Survival Disease-Free Survival ErbB Receptors
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Energy consumption prediction using the GRU-MMattention-LightGBM model with features of Prophet decomposition.

PloS one Jan 17, 2023
The prediction of energy consumption is of great significance to the stability of the regional energy supply. In previous research on energy consumption forecasting, researchers have constantly proposed improved neural network prediction models or im...
Neural Networks, Computer Machine Learning Mutation Physical Phenomena
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Predicting prime editing efficiency and product purity by deep learning.

Nature biotechnology Jan 16, 2023
Prime editing is a versatile genome editing tool but requires experimental optimization of the prime editing guide RNA (pegRNA) to achieve high editing efficiency. Here we conducted a high-throughput screen to analyze prime editing outcomes of 92,423...
CRISPR-Cas Systems Mutation Hepatocytes Neural Networks, Computer Deep Learning Humans Gene Editing
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Using machine learning to predict the effects and consequences of mutations in proteins.

Current opinion in structural biology Jan 3, 2023
Machine and deep learning approaches can leverage the increasingly available massive datasets of protein sequences, structures, and mutational effects to predict variants with improved fitness. Many different approaches are being developed, but syste...
Algorithms Mutation Amino Acid Sequence Neural Networks, Computer Machine Learning
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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.
Adult Radiomics Brain Neoplasms Male Middle Aged Prognosis Female Aged Humans DNA Repair Enzymes Neural Networks, Computer Isocitrate Dehydrogenase Tumor Suppressor Proteins Glioblastoma Deep Learning X-linked Nuclear Protein Semantics Mutation Magnetic Resonance Imaging DNA Modification Methylases
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Deep learning and multi-omics approach to predict drug responses in cancer.

BMC bioinformatics Nov 28, 2022
BACKGROUND: Cancers are genetically heterogeneous, so anticancer drugs show varying degrees of effectiveness on patients due to their differing genetic profiles. Knowing patient's responses to numerous cancer drugs are needed for personalized treatme...
Mutation Deep Learning Genomics DNA Copy Number Variations Humans Neoplasms
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Optimization of deep learning models for the prediction of gene mutations using unsupervised clustering.

The journal of pathology. Clinical research Nov 14, 2022
Deep learning models are increasingly being used to interpret whole-slide images (WSIs) in digital pathology and to predict genetic mutations. Currently, it is commonly assumed that tumor regions have most of the predictive power. However, it is reas...
Cluster Analysis Mutation Humans Algorithms Tumor Microenvironment Deep Learning
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Shuffle-ResNet: Deep learning for predicting LGG IDH1 mutation from multicenter anatomical MRI sequences.

Biomedical physics & engineering express Nov 11, 2022
The world health organization recommended to incorporate gene information such as isocitrate dehydrogenase 1 (IDH1) mutation status to improve prognosis, diagnosis, and treatment of the central nervous system tumors. We proposed our Shuffle Residual ...
Humans Retrospective Studies Brain Neoplasms Magnetic Resonance Imaging Mutation Isocitrate Dehydrogenase Disease Progression Deep Learning Glioma
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