AIMC Topic: Reproducibility of Results

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Prediction of brain maturity in infants using machine-learning algorithms.

NeuroImage
Recent resting-state functional MRI investigations have demonstrated that much of the large-scale functional network architecture supporting motor, sensory and cognitive functions in older pediatric and adult populations is present in term- and prema...

Evaluating clustering methods within the Artificial Ecosystem Algorithm and their application to bike redistribution in London.

Bio Systems
This paper proposes and evaluates a solution to the truck redistribution problem prominent in London's Santander Cycle scheme. Due to the complexity of this NP-hard combinatorial optimisation problem, no efficient optimisation techniques are known to...

Classification of amyloid status using machine learning with histograms of oriented 3D gradients.

NeuroImage. Clinical
Brain amyloid burden may be quantitatively assessed from positron emission tomography imaging using standardised uptake value ratios. Using these ratios as an adjunct to visual image assessment has been shown to improve inter-reader reliability, howe...

Liver vessel segmentation based on extreme learning machine.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Liver-vessel segmentation plays an important role in vessel structure analysis for liver surgical planning. This paper presents a liver-vessel segmentation method based on extreme learning machine (ELM). Firstly, an anisotropic filter is used to remo...

Cascaded Adaptation Framework for Fast Calibration of Myoelectric Control.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In spite of several decades of intensive research and development, the existing algorithms of myoelectric pattern recognition (MPR) are yet to make significant clinical and commercial impact. This study focuses on the one of the limiting factors of c...

A framework for the automatic detection and characterization of brain malformations: Validation on the corpus callosum.

Medical image analysis
In this paper, we extend the one-class Support Vector Machine (SVM) and the regularized discriminative direction analysis to the Multiple Kernel (MK) framework, providing an effective analysis pipeline for the detection and characterization of brain ...

A hierarchical model for integrating unsupervised generative embedding and empirical Bayes.

Journal of neuroscience methods
BACKGROUND: Generative models of neuroimaging data, such as dynamic causal models (DCMs), are commonly used for inferring effective connectivity from individual subject data. Recently introduced "generative embedding" approaches have used DCM-based c...

A Natural Language Processing Tool for Large-Scale Data Extraction from Echocardiography Reports.

PloS one
Large volumes of data are continuously generated from clinical notes and diagnostic studies catalogued in electronic health records (EHRs). Echocardiography is one of the most commonly ordered diagnostic tests in cardiology. This study sought to expl...

Metastatic liver tumour segmentation with a neural network-guided 3D deformable model.

Medical & biological engineering & computing
The segmentation of liver tumours in CT images is useful for the diagnosis and treatment of liver cancer. Furthermore, an accurate assessment of tumour volume aids in the diagnosis and evaluation of treatment response. Currently, segmentation is perf...