AIMC Topic: Mutation

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Radiomic Detection of EGFR Mutations in NSCLC.

Cancer research Nov 4, 2020
Radiomics is defined as the use of automated or semi-automated post-processing and analysis of multiple features derived from imaging exams. Extracted features might generate models able to predict the molecular profile of solid tumors. The aim of th...
Machine Learning Algorithms Tomography, X-Ray Computed Female Humans Adenocarcinoma Carcinoma, Non-Small-Cell Lung Area Under Curve Mutation ErbB Receptors Reproducibility of Results Male ROC Curve Lung Neoplasms
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Machine learning-based prediction of microsatellite instability and high tumor mutation burden from contrast-enhanced computed tomography in endometrial cancers.

Scientific reports Oct 20, 2020
To evaluate whether radiomic features from contrast-enhanced computed tomography (CE-CT) can identify DNA mismatch repair deficient (MMR-D) and/or tumor mutational burden-high (TMB-H) endometrial cancers (ECs). Patients who underwent targeted massive...
Poly-ADP-Ribose Binding Proteins Tumor Suppressor Protein p53 Endometrial Neoplasms Carcinoma, Endometrioid DNA Polymerase II Neoplasm Staging Microsatellite Instability DNA Mismatch Repair Mutation Machine Learning Computer Simulation Prognosis Middle Aged Tomography, X-Ray Computed Humans Cohort Studies Female Uterus Aged
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Non-invasive decision support for NSCLC treatment using PET/CT radiomics.

Nature communications Oct 16, 2020
Two major treatment strategies employed in non-small cell lung cancer, NSCLC, are tyrosine kinase inhibitors, TKIs, and immune checkpoint inhibitors, ICIs. The choice of strategy is based on heterogeneous biomarkers that can dynamically change during...
Protein Kinase Inhibitors Positron Emission Tomography Computed Tomography Mutation Progression-Free Survival ErbB Receptors Humans Female Aged Deep Learning Lung Neoplasms Carcinoma, Non-Small-Cell Lung Male Middle Aged
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A machine learning analysis of a "normal-like" IDH-WT diffuse glioma transcriptomic subgroup associated with prolonged survival reveals novel immune and neurotransmitter-related actionable targets.

BMC medicine Oct 16, 2020
BACKGROUND: Classification of primary central nervous system tumors according to the World Health Organization guidelines follows the integration of histologic interpretation with molecular information and aims at providing the most precise prognosis...
Humans Machine Learning Prognosis Adult Brain Neoplasms Male Middle Aged Transcriptome Female Aged Aged, 80 and over Young Adult Glioma Mutation Survival Analysis Isocitrate Dehydrogenase
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Machine learning discriminates a movement disorder in a zebrafish model of Parkinson's disease.

Disease models & mechanisms Oct 16, 2020
Animal models of human disease provide an system that can reveal molecular mechanisms by which mutations cause pathology, and, moreover, have the potential to provide a valuable tool for drug development. Here, we have developed a zebrafish model of...
Movement Disorders Gene Targeting Gene Expression Profiling Protein Deglycase DJ-1 Machine Learning Disease Models, Animal Algorithms Parkinson Disease Brain Alleles Mutation Animals Base Sequence Zebrafish Movement Dopaminergic Neurons
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Understanding and predicting ciprofloxacin minimum inhibitory concentration in Escherichia coli with machine learning.

Scientific reports Sep 14, 2020
It is important that antibiotics prescriptions are based on antimicrobial susceptibility data to ensure effective treatment outcomes. The increasing availability of next-generation sequencing, bacterial whole genome sequencing (WGS) can facilitate a ...
Toxicity Tests Ciprofloxacin Drug Resistance, Bacterial DNA Gyrase Inhibitory Concentration 50 Machine Learning Intracellular Signaling Peptides and Proteins Genes, Bacterial Anti-Bacterial Agents Escherichia coli Proteins Escherichia coli Mutation
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Machine learning method using position-specific mutation based classification outperforms one hot coding for disease severity prediction in haemophilia 'A'.

Genomics Sep 11, 2020
Haemophilia is an X-linked genetic disorder in which A and B types are the most common that occur due to absence or lack of protein factors VIII and IX, respectively. Severity of the disease depends on mutation. Available Machine Learning (ML) method...
Humans Machine Learning Severity of Illness Index Mutation Hemophilia A
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A Deep Learning Framework Identifies Pathogenic Noncoding Somatic Mutations from Personal Prostate Cancer Genomes.

Cancer research Sep 9, 2020
Our understanding of noncoding mutations in cancer genomes has been derived primarily from mutational recurrence analysis by aggregating clinical samples on a large scale. These cohort-based approaches cannot directly identify individual pathogenic n...
Humans Mutation Male DNA Mutational Analysis Deep Learning Genome Carcinogenesis Prostatic Neoplasms
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Computer versus cardiologist: Is a machine learning algorithm able to outperform an expert in diagnosing a phospholamban p.Arg14del mutation on the electrocardiogram?

Heart rhythm Sep 8, 2020
BACKGROUND: Phospholamban (PLN) p.Arg14del mutation carriers are known to develop dilated and/or arrhythmogenic cardiomyopathy, and typical electrocardiographic (ECG) features have been identified for diagnosis. Machine learning is a powerful tool us...
Adolescent Humans Machine Learning Algorithms Computers Adult Arrhythmogenic Right Ventricular Dysplasia DNA Mutational Analysis Phenotype Male Cardiologists Electrocardiography Calcium-Binding Proteins Middle Aged Retrospective Studies DNA Clinical Competence Female Mutation Reproducibility of Results Young Adult
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MosaicBase: A Knowledgebase of Postzygotic Mosaic Variants in Noncancer Disease-related and Healthy Human Individuals.

Genomics, proteomics & bioinformatics Sep 8, 2020
Mosaic variants resulting from postzygotic mutations are prevalent in the human genome and play important roles in human diseases. However, except for cancer-related variants, there is no collection of postzygotic mosaic variants in noncancer disease...
Zygote Databases, Genetic Disease Humans Mutation Software Knowledge Bases Health Phenotype Genome, Human Mosaicism User-Computer Interface
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