AIMC Topic: Machine Learning

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Correlation of magnetic resonance imaging with digital histopathology in prostate.

International journal of computer assisted radiology and surgery
PURPOSE: We propose a systematic approach to correlate MRI and digital histopathology in prostate.

Machine Learning of DTI Structural Brain Connectomes for Lateralization of Temporal Lobe Epilepsy.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
BACKGROUND AND PURPOSE: We analyzed the ability of a machine learning approach that uses diffusion tensor imaging (DTI) structural connectomes to determine lateralization of epileptogenicity in temporal lobe epilepsy (TLE).

Budget constrained non-monotonic feature selection.

Neural networks : the official journal of the International Neural Network Society
Feature selection is an important problem in machine learning and data mining. We consider the problem of selecting features under the budget constraint on the feature subset size. Traditional feature selection methods suffer from the "monotonic" pro...

Seq-ing improved gene expression estimates from microarrays using machine learning.

BMC bioinformatics
BACKGROUND: Quantifying gene expression by RNA-Seq has several advantages over microarrays, including greater dynamic range and gene expression estimates on an absolute, rather than a relative scale. Nevertheless, microarrays remain in widespread use...

Emergence of Leadership in a Group of Autonomous Robots.

PloS one
In this paper we examine the factors contributing to the emergence of leadership in a group, and we explore the relationship between the role of the leader and the behavioural capabilities of other individuals. We use a simulation technique where a g...

Networks that learn the precise timing of event sequences.

Journal of computational neuroscience
Neuronal circuits can learn and replay firing patterns evoked by sequences of sensory stimuli. After training, a brief cue can trigger a spatiotemporal pattern of neural activity similar to that evoked by a learned stimulus sequence. Network models s...

Slithering towards autonomy: a self-contained soft robotic snake platform with integrated curvature sensing.

Bioinspiration & biomimetics
Soft robotic snakes promise significant advantages in achieving traveling curvature waves with a reduced number of active segments as well as allowing for safe and adaptive interaction with the environment and human users. However, current soft robot...

Predicting protein function and other biomedical characteristics with heterogeneous ensembles.

Methods (San Diego, Calif.)
Prediction problems in biomedical sciences, including protein function prediction (PFP), are generally quite difficult. This is due in part to incomplete knowledge of the cellular phenomenon of interest, the appropriateness and data quality of the va...

Machine-learning to characterise neonatal functional connectivity in the preterm brain.

NeuroImage
Brain development is adversely affected by preterm birth. Magnetic resonance image analysis has revealed a complex fusion of structural alterations across all tissue compartments that are apparent by term-equivalent age, persistent into adolescence a...

Discriminating preictal and interictal brain states in intracranial EEG by sample entropy and extreme learning machine.

Journal of neuroscience methods
BACKGROUND: Epilepsy is one of the most common neurological disorders approximately one in every 100 people worldwide are suffering from it. Uncontrolled epilepsy poses a significant burden to society due to associated healthcare cost to treat and co...