AIMC Topic: Regression Analysis

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Cross-scanner and cross-protocol multi-shell diffusion MRI data harmonization: Algorithms and results.

NeuroImage Jul 13, 2020
Cross-scanner and cross-protocol variability of diffusion magnetic resonance imaging (dMRI) data are known to be major obstacles in multi-site clinical studies since they limit the ability to aggregate dMRI data and derived measures. Computational al...
Image Processing, Computer-Assisted Regression Analysis Neuroimaging Diffusion Magnetic Resonance Imaging Humans Algorithms Brain Adult Deep Learning
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Machine learning-based prediction of acute severity in infants hospitalized for bronchiolitis: a multicenter prospective study.

Scientific reports Jul 3, 2020
We aimed to develop machine learning models to accurately predict bronchiolitis severity, and to compare their predictive performance with a conventional scoring (reference) model. In a 17-center prospective study of infants (aged < 1 year) hospitali...
Humans Machine Learning Prospective Studies Intensive Care Units Female Regression Analysis Decision Trees Predictive Value of Tests Positive-Pressure Respiration Bronchiolitis Hospitalization Male Infant Severity of Illness Index Cohort Studies
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Solitary solid pulmonary nodules: a CT-based deep learning nomogram helps differentiate tuberculosis granulomas from lung adenocarcinomas.

European radiology Jun 27, 2020
OBJECTIVES: To evaluate the differential diagnostic performance of a computed tomography (CT)-based deep learning nomogram (DLN) in identifying tuberculous granuloma (TBG) and lung adenocarcinoma (LAC) presenting as solitary solid pulmonary nodules (...
Solitary Pulmonary Nodule Regression Analysis Diagnosis, Differential Granuloma Tuberculosis Lung Neoplasms Logistic Models Nomograms Age Factors Adenocarcinoma of Lung Sex Factors Diagnostic Tests, Routine Observer Variation Pattern Recognition, Automated Calibration Tomography, X-Ray Computed Female Adult Male Middle Aged Diagnosis, Computer-Assisted Deep Learning ROC Curve Image Processing, Computer-Assisted Humans Algorithms Retrospective Studies
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Machine learning-based CT texture analysis to predict HPV status in oropharyngeal squamous cell carcinoma: comparison of 2D and 3D segmentation.

European radiology Jun 26, 2020
OBJECTIVE: To compare the CT texture feature reproducibility of 2D and 3D segmentations and their machine learning (ML)-based classifications for predicting human papilloma virus (HPV) status in oropharyngeal squamous cell carcinoma (OPSCC).
Humans Machine Learning Algorithms Retrospective Studies Regression Analysis Diagnosis, Differential Area Under Curve Observer Variation Alphapapillomavirus Imaging, Three-Dimensional Image Processing, Computer-Assisted Papillomavirus Infections Tomography, X-Ray Computed Squamous Cell Carcinoma of Head and Neck Female Head and Neck Neoplasms Reproducibility of Results Male
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Modeling the Spread of COVID-19 Infection Using a Multilayer Perceptron.

Computational and mathematical methods in medicine May 29, 2020
Coronavirus (COVID-19) is a highly infectious disease that has captured the attention of the worldwide public. Modeling of such diseases can be extremely important in the prediction of their impact. While classic, statistical, modeling can provide sa...
Coronavirus Infections Mathematical Concepts Algorithms Pneumonia, Viral Humans Databases, Factual Neural Networks, Computer Computational Biology Pandemics Regression Analysis COVID-19 Models, Biological
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In Silico Prediction of Intestinal Permeability by Hierarchical Support Vector Regression.

International journal of molecular sciences May 19, 2020
The vast majority of marketed drugs are orally administrated. As such, drug absorption is one of the important drug metabolism and pharmacokinetics parameters that should be assessed in the process of drug discovery and development. A nonlinear quant...
Humans Support Vector Machine Computer Simulation Regression Analysis Reproducibility of Results Permeability Animals Intestines Rats
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Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states.

NeuroImage May 18, 2020
Predicting biomedical outcomes from Magnetoencephalography and Electroencephalography (M/EEG) is central to applications like decoding, brain-computer-interfaces (BCI) or biomarker development and is facilitated by supervised machine learning. Yet, m...
Models, Theoretical Regression Analysis Electroencephalography Signal Processing, Computer-Assisted Electromyography Supervised Machine Learning Cerebral Cortex Brain Waves Magnetoencephalography Humans Machine Learning Computer Simulation Adult
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Proprioceptive Estimation of Forces Using Underactuated Fingers for Robot-Initiated pHRI.

Sensors (Basel, Switzerland) May 18, 2020
In physical Human-Robot Interaction (pHRI), forces exerted by humans need to be estimated to accommodate robot commands to human constraints, preferences, and needs. This paper presents a method for the estimation of the interaction forces between a ...
Humans Proprioception Feedback Regression Analysis Robotics Torque Fingers
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Assessment of associations between clinical and immune microenvironmental factors and tumor mutation burden in resected nonsmall cell lung cancer by applying machine learning to whole-slide images.

Cancer medicine May 12, 2020
BACKGROUND: It is unclear whether clinical factors and immune microenvironment (IME) factors are associated with tumor mutation burden (TMB) in patients with nonsmall cell lung cancer (NSCLC).
Ex-Smokers Non-Smokers Carcinoembryonic Antigen Smokers Exome Sequencing Keratin-19 Middle Aged Lung Neoplasms B7-H1 Antigen Antigens, Neoplasm Adenocarcinoma Aged Carcinoma, Non-Small-Cell Lung Humans Aged, 80 and over Lymphocytes, Tumor-Infiltrating Machine Learning Adult Regression Analysis Female Tumor Microenvironment Mutation Carcinoma, Squamous Cell Male Forkhead Transcription Factors
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Key components of mechanical work predict outcomes in robotic stroke therapy.

Journal of neuroengineering and rehabilitation Apr 21, 2020
BACKGROUND: Clinical practice typically emphasizes active involvement during therapy. However, traditional approaches can offer only general guidance on the form of involvement that would be most helpful to recovery. Beyond assisting movement, robots...
Energy Metabolism Humans Movement Treatment Outcome Prognosis Upper Extremity Regression Analysis Female Stroke Rehabilitation Robotics Aged Models, Biological Male Middle Aged
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