AIMC Topic: Likelihood Functions

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Estimating the Causal Impact of Proximity to Gold and Copper Mines on Respiratory Diseases in Chilean Children: An Application of Targeted Maximum Likelihood Estimation.

International journal of environmental research and public health
In a town located in a desert area of Northern Chile, gold and copper open-pit mining is carried out involving explosive processes. These processes are associated with increased dust exposure, which might affect children's respiratory health. Therefo...

Collaborative targeted learning using regression shrinkage.

Statistics in medicine
Causal inference practitioners are routinely presented with the challenge of model selection and, in particular, reducing the size of the covariate set with the goal of improving estimation efficiency. Collaborative targeted minimum loss-based estima...

Deep neural networks for texture classification-A theoretical analysis.

Neural networks : the official journal of the International Neural Network Society
We investigate the use of Deep Neural Networks for the classification of image datasets where texture features are important for generating class-conditional discriminative representations. To this end, we first derive the size of the feature space f...

Phylogeny analysis from gene-order data with massive duplications.

BMC genomics
BACKGROUND: Gene order changes, under rearrangements, insertions, deletions and duplications, have been used as a new type of data source for phylogenetic reconstruction. Because these changes are rare compared to sequence mutations, they allow the i...

A machine learning approach for predicting methionine oxidation sites.

BMC bioinformatics
BACKGROUND: The oxidation of protein-bound methionine to form methionine sulfoxide, has traditionally been regarded as an oxidative damage. However, recent evidences support the view of this reversible reaction as a regulatory post-translational modi...

Vascular tree tracking and bifurcation points detection in retinal images using a hierarchical probabilistic model.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Retinal vascular tree extraction plays an important role in computer-aided diagnosis and surgical operations. Junction point detection and classification provide useful information about the structure of the vascular network...

An Evaluation of Artificial Neural Networks in Predicting Pancreatic Cancer Survival.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
OBJECTIVE: This study aims to evaluate the development of an artificial neural network (ANN) method for predicting the survival likelihood of pancreatic adenocarcinoma patients. The ANN predictive model should produce results with a 90% sensitivity.

Maximum likelihood optimal and robust Support Vector Regression with lncosh loss function.

Neural networks : the official journal of the International Neural Network Society
In this paper, a novel and continuously differentiable convex loss function based on natural logarithm of hyperbolic cosine function, namely lncosh loss, is introduced to obtain Support Vector Regression (SVR) models which are optimal in the maximum ...

Graph-based composite local Bregman divergences on discrete sample spaces.

Neural networks : the official journal of the International Neural Network Society
This paper develops a general framework of statistical inference on discrete sample spaces, on which a neighborhood system is defined by an undirected graph. The scoring rule is a measure of the goodness of fit for the model to observed samples, and ...

Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion.

PloS one
Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. However, EEG is an important technique, especially for brain-computer interface applications. In this study, a novel algorithm ...