AIMC Topic: Algorithms

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Quantitative EEG Evaluation During Robot-Assisted Foot Movement.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Passiveand imagined limbmovements induce changes in cerebral oscillatory activity. Central modulatory effects play a role in plastic changes, and are of uttermost importance in rehabilitation. This has extensively been studied for upper limb, but les...

Dissipativity and stability analysis of fractional-order complex-valued neural networks with time delay.

Neural networks : the official journal of the International Neural Network Society
As we know, the notion of dissipativity is an important dynamical property of neural networks. Thus, the analysis of dissipativity of neural networks with time delay is becoming more and more important in the research field. In this paper, the author...

DeepCut: Object Segmentation From Bounding Box Annotations Using Convolutional Neural Networks.

IEEE transactions on medical imaging
In this paper, we propose DeepCut, a method to obtain pixelwise object segmentations given an image dataset labelled weak annotations, in our case bounding boxes. It extends the approach of the well-known GrabCut [1] method to include machine learnin...

Robust learning in SpikeProp.

Neural networks : the official journal of the International Neural Network Society
Training a Spiking Neural Network using SpikeProp and its derivatives faces stability issues. Surges, marked by a sudden rise in learning cost, are a common occurrence during the learning process. They disrupt the learning process and often destabili...

Random synaptic feedback weights support error backpropagation for deep learning.

Nature communications
The brain processes information through multiple layers of neurons. This deep architecture is representationally powerful, but complicates learning because it is difficult to identify the responsible neurons when a mistake is made. In machine learnin...

Assessing Hospital Performance After Percutaneous Coronary Intervention Using Big Data.

Circulation. Cardiovascular quality and outcomes
BACKGROUND: Although risk adjustment remains a cornerstone for comparing outcomes across hospitals, optimal strategies continue to evolve in the presence of many confounders. We compared conventional regression-based model to approaches particularly ...

Analysis of Machine Learning Techniques for Heart Failure Readmissions.

Circulation. Cardiovascular quality and outcomes
BACKGROUND: The current ability to predict readmissions in patients with heart failure is modest at best. It is unclear whether machine learning techniques that address higher dimensional, nonlinear relationships among variables would enhance predict...

Automatic detection and classification of leukocytes using convolutional neural networks.

Medical & biological engineering & computing
The detection and classification of white blood cells (WBCs, also known as Leukocytes) is a hot issue because of its important applications in disease diagnosis. Nowadays the morphological analysis of blood cells is operated manually by skilled opera...

PLAT: An Automated Fault and Behavioural Anomaly Detection Tool for PLC Controlled Manufacturing Systems.

Computational intelligence and neuroscience
Operational faults and behavioural anomalies associated with PLC control processes take place often in a manufacturing system. Real time identification of these operational faults and behavioural anomalies is necessary in the manufacturing industry. ...

An algorithm for direct causal learning of influences on patient outcomes.

Artificial intelligence in medicine
OBJECTIVE: This study aims at developing and introducing a new algorithm, called direct causal learner (DCL), for learning the direct causal influences of a single target. We applied it to both simulated and real clinical and genome wide association ...