AIMC Topic:
Models, Statistical

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Probabilistic machine learning and artificial intelligence.

Nature
How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from da...

The entropic basis of collective behaviour.

Journal of the Royal Society, Interface
We identify a unique viewpoint on the collective behaviour of intelligent agents. We first develop a highly general abstract model for the possible future lives these agents may encounter as a result of their decisions. In the context of these possib...

Multistep prediction of physiological tremor based on machine learning for robotics assisted microsurgery.

IEEE transactions on cybernetics
For effective tremor compensation in robotics assisted hand-held device, accurate filtering of tremulous motion is necessary. The time-varying unknown phase delay that arises due to both software (filtering) and hardware (sensors) in these robotics i...

Statically vs dynamically balanced gait: Analysis of a robotic exoskeleton compared with a human.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In recent years exoskeletons able to replicate human gait have begun to attract growing popularity for both assistive and rehabilitative purposes. Although wearable robots often need the use of external support in order to maintain stability, the REX...

Predicting Protein-Protein Interaction Sites with a Novel Membership Based Fuzzy SVM Classifier.

IEEE/ACM transactions on computational biology and bioinformatics
Predicting residues that participate in protein-protein interactions (PPI) helps to identify, which amino acids are located at the interface. In this paper, we show that the performance of the classical support vector machine (SVM) algorithm can furt...

Fuzzy Logic as a Computational Tool for Quantitative Modelling of Biological Systems with Uncertain Kinetic Data.

IEEE/ACM transactions on computational biology and bioinformatics
Quantitative modelling of biological systems has become an indispensable computational approach in the design of novel and analysis of existing biological systems. However, kinetic data that describe the system's dynamics need to be known in order to...

Fuzzy linguistic prediction model for sinoatrial node field potential analysis in acute hyperglycemia environment.

Bio-medical materials and engineering
The objective of this study is to build a fuzzy linguistic prediction model (FLPM) for analyzing the actuation duration of acute hyperglycemia to sinoatrial node field potential. The field potential was recorded using microelectrode arrays (MEA). The...

Application of multi-output support vector regression on EMGs to decode hand continuous movement trajectory.

Bio-medical materials and engineering
Applications of neural machine interfaces have received increased attention during the last decades. It is crucial to realize the continuous control of prosthetic devices based on biological signals. In order to deal with the highly nonlinear relatio...

A hybrid ensemble method based on double disturbance for classifying microarray data.

Bio-medical materials and engineering
Microarray data has small samples and high dimension, and it contains a significant amount of irrelevant and redundant genes. This paper proposes a hybrid ensemble method based on double disturbance to improve classification performance. Firstly, ori...

An effective fuzzy kernel clustering analysis approach for gene expression data.

Bio-medical materials and engineering
Fuzzy clustering is an important tool for analyzing microarray data. A major problem in applying fuzzy clustering method to microarray gene expression data is the choice of parameters with cluster number and centers. This paper proposes a new approac...