AIMC Topic: Models, Statistical

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Fall risk probability estimation based on supervised feature learning using public fall datasets.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
Risk of falling is considered among major threats for elderly population and therefore started to play an important role in modern healthcare. With recent development of sensor technology, the number of studies dedicated to reliable fall detection sy...
Humans Models, Statistical Supervised Machine Learning Probability Risk Assessment Accidental Falls Algorithms
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Forecasting nanoparticle toxicity using nonlinear predictive regressor learning systems.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
Nanoparticle (NP) toxicity is determined by a vast number of topological, sterical, physico-chemical as well as biological properties, rendering a priori evaluation of the effect of NP on biological tissue as arduous as it is necessary and urgent. We...
Support Vector Machine Models, Statistical Nonlinear Dynamics Algorithms Nanoparticles
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[Prediction of schistosomiasis infection rates of population based on ARIMA-NARNN model].

Zhongguo xue xi chong bing fang zhi za zhi = Chinese journal of schistosomiasis control Jul 12, 2016
OBJECTIVE: To explore the effect of the autoregressive integrated moving average model-nonlinear auto-regressive neural network (ARIMA-NARNN) model on predicting schistosomiasis infection rates of population.
Models, Statistical Schistosomiasis China Incidence Neural Networks, Computer Forecasting Humans
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A Case Study of the Impact of Data-Adaptive Versus Model-Based Estimation of the Propensity Scores on Causal Inferences from Three Inverse Probability Weighting Estimators.

The international journal of biostatistics May 1, 2016
OBJECTIVE: Consistent estimation of causal effects with inverse probability weighting estimators is known to rely on consistent estimation of propensity scores. To alleviate the bias expected from incorrect model specification for these nuisance para...
Diabetes Mellitus, Type 2 Models, Statistical Propensity Score Outcome Assessment, Health Care Humans Machine Learning Electronic Health Records
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Statistical Inference for Data Adaptive Target Parameters.

The international journal of biostatistics May 1, 2016
Consider one observes n i.i.d. copies of a random variable with a probability distribution that is known to be an element of a particular statistical model. In order to define our statistical target we partition the sample in V equal size sub-samples...
Data Mining Biostatistics Models, Statistical Data Interpretation, Statistical Machine Learning
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Optimal Spatial Prediction Using Ensemble Machine Learning.

The international journal of biostatistics May 1, 2016
Spatial prediction is an important problem in many scientific disciplines. Super Learner is an ensemble prediction approach related to stacked generalization that uses cross-validation to search for the optimal predictor amongst all convex combinatio...
Machine Learning Models, Statistical Spatial Analysis United States Environmental Protection Agency Lakes United States
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Testing the Relative Performance of Data Adaptive Prediction Algorithms: A Generalized Test of Conditional Risk Differences.

The international journal of biostatistics May 1, 2016
Comparing the relative fit of competing models can be used to address many different scientific questions. In classical statistics one can, if appropriate, use likelihood ratio tests and information based criterion, whereas clinical medicine has tend...
Models, Statistical Data Interpretation, Statistical Risk Assessment Polymorphism, Single Nucleotide Genetic Association Studies Humans Machine Learning
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Genetics. Predicting the impact of genomic variation.

Nature methods Mar 1, 2016
Molecular Sequence Data Chromosome Mapping Models, Statistical Unsupervised Machine Learning Base Sequence Genetic Variation Genome, Human Humans Computer Simulation Models, Genetic Sequence Analysis, DNA
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Multicenter Comparison of Machine Learning Methods and Conventional Regression for Predicting Clinical Deterioration on the Wards.

Critical care medicine Feb 1, 2016
OBJECTIVE: Machine learning methods are flexible prediction algorithms that may be more accurate than conventional regression. We compared the accuracy of different techniques for detecting clinical deterioration on the wards in a large, multicenter ...
Age Factors Models, Statistical Vital Signs Heart Arrest Humans Survival Analysis Logistic Models Intensive Care Units Socioeconomic Factors Risk Assessment Diagnostic Techniques and Procedures Support Vector Machine Cohort Studies Time Factors ROC Curve Neural Networks, Computer Machine Learning
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The importance of imagination (or lack thereof) in artificial, human and quantum decision making.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences Jan 13, 2016
Enlarging upon experiments and analysis that I did jointly some years ago, in which artificial (symbolic, neural-net and pattern) learning and generalization were compared with that of humans, I will emphasize the role of imagination (or lack thereof...
Quantum Theory Imagination Humans Decision Making Machine Learning Computer Simulation Models, Statistical Models, Neurological Decision Support Techniques
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