AIMC Topic: Machine Learning

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Classifying Regularized Sensor Covariance Matrices: An Alternative to CSP.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Common spatial patterns (CSP) is a commonly used technique for classifying imagined movement type brain-computer interface (BCI) datasets. It has been very successful with many extensions and improvements on the basic technique. However, a drawback o...

Genome instability model of metastatic neuroblastoma tumorigenesis by a dictionary learning algorithm.

BMC medical genomics
BACKGROUND: Metastatic neuroblastoma (NB) occurs in pediatric patients as stage 4S or stage 4 and it is characterized by heterogeneous clinical behavior associated with diverse genotypes. Tumors of stage 4 contain several structural copy number aberr...

Machine learning classification of mesial temporal sclerosis in epilepsy patients.

Epilepsy research
BACKGROUND AND PURPOSE: Novel approaches applying machine-learning methods to neuroimaging data seek to develop individualized measures that will aid in the diagnosis and treatment of brain-based disorders such as temporal lobe epilepsy (TLE). Using ...

Automated measurement of mouse social behaviors using depth sensing, video tracking, and machine learning.

Proceedings of the National Academy of Sciences of the United States of America
A lack of automated, quantitative, and accurate assessment of social behaviors in mammalian animal models has limited progress toward understanding mechanisms underlying social interactions and their disorders such as autism. Here we present a new in...

Texture recognition and localization in amorphous robotic skin.

Bioinspiration & biomimetics
We present a soft robotic skin that can recognize and localize texture using a distributed set of sensors and computational elements that are inspired by the Pacinian corpuscle, the fast adapting, uniformly spaced mechanoreceptor with a wide receptiv...

Machine learning classification of medication adherence in patients with movement disorders using non-wearable sensors.

Computers in biology and medicine
Medication non-adherence is a major concern in the healthcare industry and has led to increases in health risks and medical costs. For many neurological diseases, adherence to medication regimens can be assessed by observing movement patterns. Howeve...

Learning to decode human emotions with Echo State Networks.

Neural networks : the official journal of the International Neural Network Society
The aim of this paper is to identify the common neural signatures based on which the positive and negative valence of human emotions across multiple subjects can be reliably discriminated. The brain activity is observed via Event Related Potentials (...

Prediction of telephone calls load using Echo State Network with exogenous variables.

Neural networks : the official journal of the International Neural Network Society
We approach the problem of forecasting the load of incoming calls in a cell of a mobile network using Echo State Networks. With respect to previous approaches to the problem, we consider the inclusion of additional telephone records regarding the act...

Going beyond a First Reader: A Machine Learning Methodology for Optimizing Cost and Performance in Breast Ultrasound Diagnosis.

Ultrasound in medicine & biology
The goal of this study was to devise a machine learning methodology as a viable low-cost alternative to a second reader to help augment physicians' interpretations of breast ultrasound images in differentiating benign and malignant masses. Two indepe...

Multi-Objective Particle Swarm Optimization Approach for Cost-Based Feature Selection in Classification.

IEEE/ACM transactions on computational biology and bioinformatics
Feature selection is an important data-preprocessing technique in classification problems such as bioinformatics and signal processing. Generally, there are some situations where a user is interested in not only maximizing the classification performa...