AIMC Topic: Multivariate Analysis

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Next-Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Algorithms.

Molecular imaging and biology Aug 1, 2020
PURPOSE: Considerable progress has been made in the assessment and management of non-small cell lung cancer (NSCLC) patients based on mutation status in the epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene (KRAS). At the...
Female Aged Male Lung Neoplasms Genomics Humans Machine Learning Algorithms Positron-Emission Tomography High-Throughput Nucleotide Sequencing Multivariate Analysis ErbB Receptors Proto-Oncogene Proteins p21(ras) Carcinoma, Non-Small-Cell Lung Multimodal Imaging Area Under Curve Mutation
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Modeling and measurement of signaling outcomes affecting decision making in noisy intracellular networks using machine learning methods.

Integrative biology : quantitative biosciences from nano to macro May 21, 2020
Characterization of decision-making in cells in response to received signals is of importance for understanding how cell fate is determined. The problem becomes multi-faceted and complex when we consider cellular heterogeneity and dynamics of biochem...
PTEN Phosphohydrolase Signal Transduction Humans Probability Decision Making Tumor Suppressor Protein p53 Machine Learning DNA Damage Multivariate Analysis Algorithms Outcome Assessment, Health Care Genes, p53 Reproducibility of Results Normal Distribution ROC Curve
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Multivariate Data Analysis and Machine Learning for Prediction of MCI-to-AD Conversion.

Advances in experimental medicine and biology Jan 1, 2020
There has always been a need for discovering efficient and dependable Alzheimer's disease (AD) diagnostic biomarkers. Like the majority of diseases, the earlier the diagnosis, the most effective the treatment. (Semi)-automated structural magnetic res...
Case-Control Studies Diagnosis, Computer-Assisted Cognitive Dysfunction Support Vector Machine Magnetic Resonance Imaging Humans Machine Learning Brain Bayes Theorem Alzheimer Disease Multivariate Analysis Diagnostic Techniques, Neurological
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Multi-omics integration-a comparison of unsupervised clustering methodologies.

Briefings in bioinformatics Jul 19, 2019
With the recent developments in the field of multi-omics integration, the interest in factors such as data preprocessing, choice of the integration method and the number of different omics considered had increased. In this work, the impact of these f...
Metabolomics Unsupervised Machine Learning Factor Analysis, Statistical Models, Biological Multivariate Analysis Computational Biology Systems Biology Proteomics Cluster Analysis Systems Integration Humans Algorithms Databases, Factual Computer Simulation Animals Mice Genomics
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Decision tree (DT), generalized regression neural network (GR) and multivariate adaptive regression splines (MARS) models for sediment transport in sewer pipes.

Water science and technology : a journal of the International Association on Water Pollution Research Mar 1, 2019
Sediment deposition in sewers and urban drainage systems has great effect on the hydraulic capacity of the channel. In this respect, the self-cleansing concept has been widely used for sewers and urban drainage systems design. This study investigates...
Geologic Sediments Waste Disposal, Fluid Drainage, Sanitary Models, Statistical Neural Networks, Computer Decision Trees Water Pollution Multivariate Analysis
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A Cancer Paradox: Machine-Learning Backed Propensity-Score Analysis of Coronary Angiography Findings in Cardio-Oncology.

The Journal of invasive cardiology Jan 1, 2019
OBJECTIVES: Cancer has been proposed as a cardiovascular risk factor. We aimed to assess the cardiovascular risk profile and coronary angiography (CA) findings of cancer patients and compare them to those of patients without cancer.
Humans Multivariate Analysis Machine Learning Coronary Angiography Retrospective Studies Propensity Score Coronary Artery Disease Female Texas Reference Values Prevalence Aged Cancer Care Facilities Sex Factors Case-Control Studies Aged, 80 and over Academic Medical Centers Logistic Models Male Age Factors Risk Assessment Neoplasms
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The Decision Decoding ToolBOX (DDTBOX) - A Multivariate Pattern Analysis Toolbox for Event-Related Potentials.

Neuroinformatics Jan 1, 2019
In recent years, neuroimaging research in cognitive neuroscience has increasingly used multivariate pattern analysis (MVPA) to investigate higher cognitive functions. Here we present DDTBOX, an open-source MVPA toolbox for electroencephalography (EEG...
Humans Neuroimaging Brain Multivariate Analysis Support Vector Machine Evoked Potentials Electroencephalography Signal Processing, Computer-Assisted
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Combined multivariate analysis and machine learning reveals a predictive module of metabolic stress response in Arabidopsis thaliana.

Molecular omics Dec 3, 2018
Abiotic stress exposure of plants induces metabolic reprogramming which is tightly regulated by signalling cascades connecting transcriptional with translational and metabolic regulation. Complexity of such interconnected metabolic networks impedes t...
Multivariate Analysis Analysis of Variance Chlorophyll Arabidopsis Phosphoglucomutase Cell Line Machine Learning Mutation Computational Biology Sucrose Metabolomics Stress, Physiological
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Predicting the Ability of Wounds to Heal Given Any Burn Size and Fluid Volume: An Analytical Approach.

Journal of burn care & research : official publication of the American Burn Association Aug 17, 2018
The intrinsic relationship between fluid volume and open wound size (%) has not been previously examined. Therefore, we conducted this study to investigate whether open wound size can be predicted from fluid volume plus other significant factors over...
Hospitalization Adult Male Multivariate Analysis Humans Middle Aged Wound Healing Crystalloid Solutions Machine Learning Age Factors Predictive Value of Tests Retrospective Studies Fluid Therapy Female Burns Reproducibility of Results
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Incidence and location of positive surgical margin among open, laparoscopic and robot-assisted radical prostatectomy in prostate cancer patients: a single institutional analysis.

Japanese journal of clinical oncology Aug 1, 2018
OBJECTIVE: To evaluate the positive surgical margin rates and locations in radical prostatectomy among three surgical approaches, including open radical prostatectomy, laparoscopic radical prostatectomy and robot-assisted radical prostatectomy.
Male Propensity Score Prostatic Neoplasms Humans Middle Aged Prostate-Specific Antigen Retrospective Studies Incidence Prostatectomy Laparoscopy Risk Factors Logistic Models Multivariate Analysis Preoperative Care Aged Robotics Margins of Excision
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