AIMC Topic: Algorithms

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Prediction of RNA-protein sequence and structure binding preferences using deep convolutional and recurrent neural networks.

BMC genomics
BACKGROUND: RNA regulation is significantly dependent on its binding protein partner, known as the RNA-binding proteins (RBPs). Unfortunately, the binding preferences for most RBPs are still not well characterized. Interdependencies between sequence ...

Atrial Fibrillation Beat Identification Using the Combination of Modified Frequency Slice Wavelet Transform and Convolutional Neural Networks.

Journal of healthcare engineering
Atrial fibrillation (AF) is a serious cardiovascular disease with the phenomenon of beating irregularly. It is the major cause of variety of heart diseases, such as myocardial infarction. Automatic AF beat detection is still a challenging task which ...

An end to end Deep Neural Network for iris segmentation in unconstrained scenarios.

Neural networks : the official journal of the International Neural Network Society
With the increasing imaging and processing capabilities of today's mobile devices, user authentication using iris biometrics has become feasible. However, as the acquisition conditions become more unconstrained and as image quality is typically lower...

Assessment of Carotid Artery Plaque Components With Machine Learning Classification Using Homodyned-K Parametric Maps and Elastograms.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Quantitative ultrasound (QUS) imaging methods, including elastography, echogenicity analysis, and speckle statistical modeling, are available from a single ultrasound (US) radio-frequency data acquisition. Since these US imaging methods provide compl...

Early anomaly detection in smart home: A causal association rule-based approach.

Artificial intelligence in medicine
As the world's population grows older, an increasing number of people are facing health issues. For the elderly, living alone can be difficult and dangerous. Consequently, smart homes are becoming increasingly popular. A sensor-rich environment can b...

Protein Secondary Structure Prediction Based on Data Partition and Semi-Random Subspace Method.

Scientific reports
Protein secondary structure prediction is one of the most important and challenging problems in bioinformatics. Machine learning techniques have been applied to solve the problem and have gained substantial success in this research area. However ther...

Exergetic performance prediction of solar air heater using MLP, GRNN and RBF models of artificial neural network technique.

Journal of environmental management
In the present study three different types of neural models: multi-layer perceptron (MLP), generalized regression neural network (GRNN) and radial basis function (RBF) has been used to predict the exergetic efficiency of roughened solar air heater. T...

Spiking networks as efficient distributed controllers.

Biological cybernetics
In the brain, networks of neurons produce activity that is decoded into perceptions and actions. How the dynamics of neural networks support this decoding is a major scientific question. That is, while we understand the basic mechanisms by which neur...

Deep Learning Global Glomerulosclerosis in Transplant Kidney Frozen Sections.

IEEE transactions on medical imaging
Transplantable kidneys are in very limited supply. Accurate viability assessment prior to transplantation could minimize organ discard. Rapid and accurate evaluation of intra-operative donor kidney biopsies is essential for determining which kidneys ...