AIMC Topic: Regression Analysis

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Oropharyngeal squamous cell carcinoma: radiomic machine-learning classifiers from multiparametric MR images for determination of HPV infection status.

Scientific reports Oct 16, 2020
We investigated the ability of machine-learning classifiers on radiomics from pre-treatment multiparametric magnetic resonance imaging (MRI) to accurately predict human papillomavirus (HPV) status in patients with oropharyngeal squamous cell carcinom...
Humans Aged, 80 and over Adult Male Middle Aged Machine Learning Retrospective Studies Female Aged Papillomaviridae Oropharyngeal Neoplasms Multiparametric Magnetic Resonance Imaging Squamous Cell Carcinoma of Head and Neck ROC Curve Head and Neck Neoplasms Computational Biology Regression Analysis Papillomavirus Infections Area Under Curve
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Machine learning-based QSAR models to predict sodium ion channel (Na 1.5) blockers.

Future medicinal chemistry Oct 9, 2020
Conventional experimental approaches used for the evaluation of the proarrhythmic potential of compounds in the drug discovery process are expensive and time consuming but an integral element in the safety profile required for a new drug to be appro...
Humans Machine Learning Models, Statistical Regression Analysis Quantitative Structure-Activity Relationship Small Molecule Libraries NAV1.5 Voltage-Gated Sodium Channel Sodium Channel Blockers
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Long-term PM exposure and the clinical application of machine learning for predicting incident atrial fibrillation.

Scientific reports Oct 1, 2020
Clinical impact of fine particulate matter (PM) air pollution on incident atrial fibrillation (AF) had not been well studied. We used integrated machine learning (ML) to build several incident AF prediction models that include average hourly measurem...
Machine Learning Republic of Korea Female Risk Factors Humans Particle Size Particulate Matter Atrial Fibrillation Inhalation Exposure Aged Male Incidence Regression Analysis
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Advancing predictive modeling in archaeology: An evaluation of regression and machine learning methods on the Grand Staircase-Escalante National Monument.

PloS one Oct 1, 2020
Predictive models are central to both archaeological research and cultural resource management. Yet, archaeological applications of predictive models are often insufficient due to small training data sets, inadequate statistical techniques, and a lac...
Archaeology Machine Learning Models, Statistical Regression Analysis Area Under Curve
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Identification of Potential Type II Diabetes in a Large-Scale Chinese Population Using a Systematic Machine Learning Framework.

Journal of diabetes research Sep 24, 2020
BACKGROUND: An estimated 425 million people globally have diabetes, accounting for 12% of the world's health expenditures, and the number continues to grow, placing a huge burden on the healthcare system, especially in those remote, underserved areas...
Smoking Odds Ratio Alcohol Drinking Male Diabetes Mellitus, Type 2 Decision Trees Female Medically Underserved Area Logistic Models Humans Area Under Curve Risk Factors Decision Making Machine Learning Aged Asian People Regression Analysis Middle Aged Adult Algorithms Waist Circumference China Surveys and Questionnaires
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Machine learning at the interface of structural health monitoring and non-destructive evaluation.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences Sep 14, 2020
While both non-destructive evaluation (NDE) and structural health monitoring (SHM) share the objective of damage detection and identification in structures, they are distinct in many respects. This paper will discuss the differences and commonalities...
Data Compression Engineering Manufacturing and Industrial Facilities Robotics Bayes Theorem Signal Processing, Computer-Assisted Ultrasonics Humans Machine Learning Algorithms Regression Analysis
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Machine learning-based mortality rate prediction using optimized hyper-parameter.

Computer methods and programs in biomedicine Aug 18, 2020
OBJECTIVE AND BACKGROUND: The current scenario of the Pandemic of COVID-19 demands multi-channel investigations and predictions. A variety of prediction models are available in the literature. The majority of these models are based on extrapolating b...
Humans Machine Learning Normal Distribution Pandemics Regression Analysis COVID-19 Models, Biological Sweden Nonlinear Dynamics Computational Biology Statistics, Nonparametric Models, Statistical
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An Automatic Epilepsy Detection Method Based on Improved Inductive Transfer Learning.

Computational and mathematical methods in medicine Aug 3, 2020
Epilepsy is a chronic disease caused by sudden abnormal discharge of brain neurons, causing transient brain dysfunction. The seizures of epilepsy have the characteristics of being sudden and repetitive, which has seriously endangered patients' health...
Signal Processing, Computer-Assisted Nonlinear Dynamics Mathematical Concepts Least-Squares Analysis Discriminant Analysis Epilepsy Seizures Diagnosis, Computer-Assisted Humans Computational Biology Machine Learning Regression Analysis Algorithms
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Development of prognostic model for patients at CKD stage 3a and 3b in South Central China using computational intelligence.

Clinical and experimental nephrology Aug 1, 2020
BACKGROUND: Chronic kidney disease (CKD) stage 3 was divided into two subgroups by eGFR (45 mL/ min 1.73 m). There is difference in prevalence of CKD, racial differences, economic development, genetic, and environmental backgrounds between China and ...
Follow-Up Studies Models, Statistical Humans Regression Analysis Neural Networks, Computer China Prognosis Renal Insufficiency, Chronic Male Retrospective Studies Glomerular Filtration Rate Middle Aged Female Kidney Failure, Chronic Support Vector Machine Disease Progression Risk Factors Adult
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Fast Deep Stacked Networks based on Extreme Learning Machine applied to regression problems.

Neural networks : the official journal of the International Neural Network Society Jul 19, 2020
Deep learning techniques are commonly used to process large amounts of data, and good results are obtained in many applications. Those methods, however, can lead to long training times. An alternative to simultaneously tune all parameters of a large ...
Machine Learning Regression Analysis
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