AIMC Topic: Algorithms

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Computer-aided lung nodule recognition by SVM classifier based on combination of random undersampling and SMOTE.

Computational and mathematical methods in medicine
In lung cancer computer-aided detection/diagnosis (CAD) systems, classification of regions of interest (ROI) is often used to detect/diagnose lung nodule accurately. However, problems of unbalanced datasets often have detrimental effects on the perfo...

Remediating radium contaminated legacy sites: Advances made through machine learning in routine monitoring of "hot" particles.

The Science of the total environment
The extensive use of radium during the 20th century for industrial, military and pharmaceutical purposes has led to a large number of contaminated legacy sites across Europe and North America. Sites that pose a high risk to the general public can pre...

Relative Attribute SVM+ Learning for Age Estimation.

IEEE transactions on cybernetics
When estimating age, human experts can provide privileged information that encodes the facial attributes of aging, such as smoothness, face shape, face acne, wrinkles, and bags under-eyes. In automatic age estimation, privileged information is unavai...

Accurate in silico identification of protein succinylation sites using an iterative semi-supervised learning technique.

Journal of theoretical biology
As a widespread type of protein post-translational modifications (PTMs), succinylation plays an important role in regulating protein conformation, function and physicochemical properties. Compared with the labor-intensive and time-consuming experimen...

Supervised dictionary learning for inferring concurrent brain networks.

IEEE transactions on medical imaging
Task-based fMRI (tfMRI) has been widely used to explore functional brain networks via predefined stimulus paradigm in the fMRI scan. Traditionally, the general linear model (GLM) has been a dominant approach to detect task-evoked networks. However, G...

Screening Internet forum participants for depression symptoms by assembling and enhancing multiple NLP methods.

Computer methods and programs in biomedicine
Depression is a disease that can dramatically lower quality of life. Symptoms of depression can range from temporary sadness to suicide. Embarrassment, shyness, and the stigma of depression are some of the factors preventing people from getting help ...

Multi-scale compositionality: identifying the compositional structures of social dynamics using deep learning.

PloS one
OBJECTIVE: Social media exhibit rich yet distinct temporal dynamics which cover a wide range of different scales. In order to study this complex dynamics, two fundamental questions revolve around (1) the signatures of social dynamics at different tim...

High-Density Electromyography and Motor Skill Learning for Robust Long-Term Control of a 7-DoF Robot Arm.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Myoelectric control offers a direct interface between human intent and various robotic applications through recorded muscle activity. Traditional control schemes realize this interface through direct mapping or pattern recognition techniques. The for...

Timescale separation in recurrent neural networks.

Neural computation
Supervised learning in recurrent neural networks involves two processes: the neuron activity from which gradients are estimated and the process on connection parameters induced by these measurements. A problem such algorithms must address is how to b...

Application of neural networks with back-propagation to genome-enabled prediction of complex traits in Holstein-Friesian and German Fleckvieh cattle.

Genetics, selection, evolution : GSE
BACKGROUND: Recently, artificial neural networks (ANN) have been proposed as promising machines for marker-based genomic predictions of complex traits in animal and plant breeding. ANN are universal approximators of complex functions, that can captur...