AIMC Topic: Algorithms

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Classifying major depression patients and healthy controls using EEG, eye tracking and galvanic skin response data.

Journal of affective disorders
OBJECTIVE: Major depression disorder (MDD) is one of the most prevalent mental disorders worldwide. Diagnosing depression in the early stage is crucial to treatment process. However, due to depression's comorbid nature and the subjectivity in diagnos...

Membrane potential resonance in non-oscillatory neurons interacts with synaptic connectivity to produce network oscillations.

Journal of computational neuroscience
Several neuron types have been shown to exhibit (subthreshold) membrane potential resonance (MPR), defined as the occurrence of a peak in their voltage amplitude response to oscillatory input currents at a preferred (resonant) frequency. MPR has been...

Minimalistic Approach to Coreference Resolution in Lithuanian Medical Records.

Computational and mathematical methods in medicine
Coreference resolution is a challenging part of natural language processing (NLP) with applications in machine translation, semantic search and other information retrieval, and decision support systems. Coreference resolution requires linguistic prep...

Varifocal-Net: A Chromosome Classification Approach Using Deep Convolutional Networks.

IEEE transactions on medical imaging
Chromosome classification is critical for karyotyping in abnormality diagnosis. To expedite the diagnosis, we present a novel method named Varifocal-Net for simultaneous classification of chromosome's type and polarity using deep convolutional networ...

Multilayer one-class extreme learning machine.

Neural networks : the official journal of the International Neural Network Society
One-class classification has been found attractive in many applications for its effectiveness in anomaly or outlier detection. Representative one-class classification algorithms include the one-class support vector machine (SVM), Naive Parzen density...

Machine learning in medicine: a practical introduction.

BMC medical research methodology
BACKGROUND: Following visible successes on a wide range of predictive tasks, machine learning techniques are attracting substantial interest from medical researchers and clinicians. We address the need for capacity development in this area by providi...

Blood Cell Classification Based on Hyperspectral Imaging With Modulated Gabor and CNN.

IEEE journal of biomedical and health informatics
Cell classification, especially that of white blood cells, plays a very important role in the field of diagnosis and control of major diseases. Compared to traditional optical microscopic imaging, hyperspectral imagery, combined with both spatial and...

Scalable Digital Neuromorphic Architecture for Large-Scale Biophysically Meaningful Neural Network With Multi-Compartment Neurons.

IEEE transactions on neural networks and learning systems
Multicompartment emulation is an essential step to enhance the biological realism of neuromorphic systems and to further understand the computational power of neurons. In this paper, we present a hardware efficient, scalable, and real-time computing ...

Augmenting Recurrent Neural Networks Resilience by Dropout.

IEEE transactions on neural networks and learning systems
This brief discusses the simple idea that dropout regularization can be used to efficiently induce resiliency to missing inputs at prediction time in a generic neural network. We show how the approach can be effective on tasks where imputation strate...