AIMC Topic: Machine Learning

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Optimal Spatial Prediction Using Ensemble Machine Learning.

The international journal of biostatistics
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...

Big Data and Machine Learning in Plastic Surgery: A New Frontier in Surgical Innovation.

Plastic and reconstructive surgery
Medical decision-making is increasingly based on quantifiable data. From the moment patients come into contact with the health care system, their entire medical history is recorded electronically. Whether a patient is in the operating room or on the ...

Cross-View Action Recognition via Transferable Dictionary Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Discriminative appearance features are effective for recognizing actions in a fixed view, but may not generalize well to a new view. In this paper, we present two effective approaches to learn dictionaries for robust action recognition across views. ...

Objective Assessment of Physical Activity: Classifiers for Public Health.

Medicine and science in sports and exercise
PURPOSE: Walking for health is recommended by health agencies, partly based on epidemiological studies of self-reported behaviors. Accelerometers are now replacing survey data, but it is not clear that intensity-based cut points reflect the behaviors...

Addressing Confounding in Predictive Models with an Application to Neuroimaging.

The international journal of biostatistics
Understanding structural changes in the brain that are caused by a particular disease is a major goal of neuroimaging research. Multivariate pattern analysis (MVPA) comprises a collection of tools that can be used to understand complex disease efxcfe...

Testing the Relative Performance of Data Adaptive Prediction Algorithms: A Generalized Test of Conditional Risk Differences.

The international journal of biostatistics
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...

Variable Selection for Confounder Control, Flexible Modeling and Collaborative Targeted Minimum Loss-Based Estimation in Causal Inference.

The international journal of biostatistics
This paper investigates the appropriateness of the integration of flexible propensity score modeling (nonparametric or machine learning approaches) in semiparametric models for the estimation of a causal quantity, such as the mean outcome under treat...

[A Denoising Method for Low-dose Small-animal Computed Tomography Image Based on Globe Dictionary Learning].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Considering the survival rate of small animals and the continuity of the experiments,high-dose X-ray shooting process is not suitable for the small animals in computed tomography(CT)experiments.But the low-dose process results with images might be po...