AIMC Topic: Machine Learning

Clear Filters Showing 33951 to 33960 of 34417 articles

An integrative machine learning strategy for improved prediction of essential genes in Escherichia coli metabolism using flux-coupled features.

Molecular bioSystems
Prediction of essential genes helps to identify a minimal set of genes that are absolutely required for the appropriate functioning and survival of a cell. The available machine learning techniques for essential gene prediction have inherent problems...

Epileptic seizure detection based on the kernel extreme learning machine.

Technology and health care : official journal of the European Society for Engineering and Medicine
This paper presents a pattern recognition model using multiple features and the kernel extreme learning machine (ELM), improving the accuracy of automatic epilepsy diagnosis. After simple preprocessing, temporal- and wavelet-based features are extrac...

Machine learning for predicting lifespan-extending chemical compounds.

Aging
Increasing age is a risk factor for many diseases; therefore developing pharmacological interventions that slow down ageing and consequently postpone the onset of many age-related diseases is highly desirable. In this work we analyse data from the Dr...

Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features.

Oncotarget
Current machine learning techniques provide the opportunity to develop noninvasive and automated glioma grading tools, by utilizing quantitative parameters derived from multi-modal magnetic resonance imaging (MRI) data. However, the efficacies of dif...

When loss-of-function is loss of function: assessing mutational signatures and impact of loss-of-function genetic variants.

Bioinformatics (Oxford, England)
MOTIVATION: Loss-of-function genetic variants are frequently associated with severe clinical phenotypes, yet many are present in the genomes of healthy individuals. The available methods to assess the impact of these variants rely primarily upon evol...

TITER: predicting translation initiation sites by deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Translation initiation is a key step in the regulation of gene expression. In addition to the annotated translation initiation sites (TISs), the translation process may also start at multiple alternative TISs (including both AUG and non-A...

Deep learning-based subdivision approach for large scale macromolecules structure recovery from electron cryo tomograms.

Bioinformatics (Oxford, England)
MOTIVATION: Cellular Electron CryoTomography (CECT) enables 3D visualization of cellular organization at near-native state and in sub-molecular resolution, making it a powerful tool for analyzing structures of macromolecular complexes and their spati...

Deep learning with word embeddings improves biomedical named entity recognition.

Bioinformatics (Oxford, England)
MOTIVATION: Text mining has become an important tool for biomedical research. The most fundamental text-mining task is the recognition of biomedical named entities (NER), such as genes, chemicals and diseases. Current NER methods rely on pre-defined ...

Label-free detection of aggregated platelets in blood by machine-learning-aided optofluidic time-stretch microscopy.

Lab on a chip
According to WHO, about 10 million new cases of thrombotic disorders are diagnosed worldwide every year. Thrombotic disorders, including atherothrombosis (the leading cause of death in the US and Europe), are induced by occlusion of blood vessels, du...