AIMC Topic: Algorithms

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Adaptive learning rate of SpikeProp based on weight convergence analysis.

Neural networks : the official journal of the International Neural Network Society
A Spiking Neural Network (SNN) training using SpikeProp and its variants is usually affected by sudden rise in learning cost called surges. These surges cause diversion in the learning process and often cause it to fail as well. Researches have shown...

A low cost real-time motion tracking approach using webcam technology.

Journal of biomechanics
Physical therapy is an important component of gait recovery for individuals with locomotor dysfunction. There is a growing body of evidence that suggests that incorporating a motor learning task through visual feedback of movement trajectory is a use...

Active-learning strategies in computer-assisted drug discovery.

Drug discovery today
High-throughput compound screening is time and resource consuming, and considerable effort is invested into screening compound libraries, profiling, and selecting the most promising candidates for further testing. Active-learning methods assist the s...

A vector reconstruction based clustering algorithm particularly for large-scale text collection.

Neural networks : the official journal of the International Neural Network Society
Along with the fast evolvement of internet technology, internet users have to face the large amount of textual data every day. Apparently, organizing texts into categories can help users dig the useful information from large-scale text collection. Cl...

Stable feature selection for clinical prediction: exploiting ICD tree structure using Tree-Lasso.

Journal of biomedical informatics
Modern healthcare is getting reshaped by growing Electronic Medical Records (EMR). Recently, these records have been shown of great value towards building clinical prediction models. In EMR data, patients' diseases and hospital interventions are capt...

Prediction of revascularization after myocardial perfusion SPECT by machine learning in a large population.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
OBJECTIVE: We aimed to investigate if early revascularization in patients with suspected coronary artery disease can be effectively predicted by integrating clinical data and quantitative image features derived from perfusion SPECT (MPS) by machine l...

flowCL: ontology-based cell population labelling in flow cytometry.

Bioinformatics (Oxford, England)
MOTIVATION: Finding one or more cell populations of interest, such as those correlating to a specific disease, is critical when analysing flow cytometry data. However, labelling of cell populations is not well defined, making it difficult to integrat...

Recognizing lexical and semantic change patterns in evolving life science ontologies to inform mapping adaptation.

Artificial intelligence in medicine
BACKGROUND: Mappings established between life science ontologies require significant efforts to maintain them up to date due to the size and frequent evolution of these ontologies. In consequence, automatic methods for applying modifications on mappi...

odNEAT: An Algorithm for Decentralised Online Evolution of Robotic Controllers.

Evolutionary computation
Online evolution gives robots the capacity to learn new tasks and to adapt to changing environmental conditions during task execution. Previous approaches to online evolution of neural controllers are typically limited to the optimisation of weights ...

Colored Traveling Salesman Problem.

IEEE transactions on cybernetics
The multiple traveling salesman problem (MTSP) is an important combinatorial optimization problem. It has been widely and successfully applied to the practical cases in which multiple traveling individuals (salesmen) share the common workspace (city ...