AIMC Topic: Machine Learning

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Automated Sleep Apnea Detection in Raw Respiratory Signals Using Long Short-Term Memory Neural Networks.

IEEE journal of biomedical and health informatics
Sleep apnea is one of the most common sleep disorders and the consequences of undiagnosed sleep apnea can be very severe, ranging from increased blood pressure to heart failure. However, many people are often unaware of their condition. The gold stan...

A minimal set of physiomarkers in continuous high frequency data streams predict adult sepsis onset earlier.

International journal of medical informatics
PURPOSE: Sepsis is a life-threatening condition with high mortality rates and expensive treatment costs. To improve short- and long-term outcomes, it is critical to detect at-risk sepsis patients at an early stage.

Deep Learning in Cardiology.

IEEE reviews in biomedical engineering
The medical field is creating large amount of data that physicians are unable to decipher and use efficiently. Moreover, rule-based expert systems are inefficient in solving complicated medical tasks or for creating insights using big data. Deep lear...

Multi-trait, Multi-environment Deep Learning Modeling for Genomic-Enabled Prediction of Plant Traits.

G3 (Bethesda, Md.)
Multi-trait and multi-environment data are common in animal and plant breeding programs. However, what is lacking are more powerful statistical models that can exploit the correlation between traits to improve prediction accuracy in the context of ge...

Multi-environment Genomic Prediction of Plant Traits Using Deep Learners With Dense Architecture.

G3 (Bethesda, Md.)
Genomic selection is revolutionizing plant breeding and therefore methods that improve prediction accuracy are useful. For this reason, active research is being conducted to build and test methods from other areas and adapt them to the context of gen...

A Neural Machine Translation Model for Arabic Dialects That Utilises Multitask Learning (MTL).

Computational intelligence and neuroscience
In this research article, we study the problem of employing a neural machine translation model to translate Arabic dialects to modern standard Arabic. The proposed solution of the neural machine translation model is prompted by the recurrent neural n...

Nonnegative/Binary matrix factorization with a D-Wave quantum annealer.

PloS one
D-Wave quantum annealers represent a novel computational architecture and have attracted significant interest. Much of this interest has focused on the quantum behavior of D-Wave machines, and there have been few practical algorithms that use the D-W...

Identifying disease genes using machine learning and gene functional similarities, assessed through Gene Ontology.

PloS one
Identifying disease genes from a vast amount of genetic data is one of the most challenging tasks in the post-genomic era. Also, complex diseases present highly heterogeneous genotype, which difficult biological marker identification. Machine learnin...

Identification of tissue-specific tumor biomarker using different optimization algorithms.

Genes & genomics
BACKGROUND: Identification of differentially expressed genes, i.e., genes whose transcript abundance level differs across different biological or physiological conditions, was indeed a challenging task. However, the inception of transcriptome sequenc...