AIMC Topic: Machine Learning

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Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images.

IEEE transactions on medical imaging
Among brain tumors, gliomas are the most common and aggressive, leading to a very short life expectancy in their highest grade. Thus, treatment planning is a key stage to improve the quality of life of oncological patients. Magnetic resonance imaging...

Hierarchical Clustering Multi-Task Learning for Joint Human Action Grouping and Recognition.

IEEE transactions on pattern analysis and machine intelligence
This paper proposes a hierarchical clustering multi-task learning (HC-MTL) method for joint human action grouping and recognition. Specifically, we formulate the objective function into the group-wise least square loss regularized by low rank and spa...

Least square neural network model of the crude oil blending process.

Neural networks : the official journal of the International Neural Network Society
In this paper, the recursive least square algorithm is designed for the big data learning of a feedforward neural network. The proposed method as the combination of the recursive least square and feedforward neural network obtains four advantages ove...

Sequential detection of learning in cognitive diagnosis.

The British journal of mathematical and statistical psychology
In order to look more closely at the many particular skills examinees utilize to answer items, cognitive diagnosis models have received much attention, and perhaps are preferable to item response models that ordinarily involve just one or a few broad...

Automated discrimination of dicentric and monocentric chromosomes by machine learning-based image processing.

Microscopy research and technique
Dose from radiation exposure can be estimated from dicentric chromosome (DC) frequencies in metaphase cells of peripheral blood lymphocytes. We automated DC detection by extracting features in Giemsa-stained metaphase chromosome images and classifyin...

Predicting Market Impact Costs Using Nonparametric Machine Learning Models.

PloS one
Market impact cost is the most significant portion of implicit transaction costs that can reduce the overall transaction cost, although it cannot be measured directly. In this paper, we employed the state-of-the-art nonparametric machine learning mod...

Multiple classifier systems for automatic sleep scoring in mice.

Journal of neuroscience methods
BACKGROUND: Electroencephalogram (EEG) and electromyogram (EMG) recordings are often used in rodents to study sleep architecture and sleep-associated neural activity. These recordings must be scored to designate what sleep/wake state the animal is in...

Medical Decision Support System for Diagnosis of Heart Arrhythmia using DWT and Random Forests Classifier.

Journal of medical systems
In this study, Random Forests (RF) classifier is proposed for ECG heartbeat signal classification in diagnosis of heart arrhythmia. Discrete wavelet transform (DWT) is used to decompose ECG signals into different successive frequency bands. A set of ...

A Discriminatively Trained Fully Connected Conditional Random Field Model for Blood Vessel Segmentation in Fundus Images.

IEEE transactions on bio-medical engineering
GOAL: In this work, we present an extensive description and evaluation of our method for blood vessel segmentation in fundus images based on a discriminatively trained fully connected conditional random field model.