AIMC Topic: Machine Learning

Clear Filters Showing 25401 to 25410 of 34417 articles

Using human brain activity to guide machine learning.

Scientific reports
Machine learning is a field of computer science that builds algorithms that learn. In many cases, machine learning algorithms are used to recreate a human ability like adding a caption to a photo, driving a car, or playing a game. While the human bra...

Empirical radio propagation model for DTV applied to non-homogeneous paths and different climates using machine learning techniques.

PloS one
The establishment and improvement of transmission systems rely on models that take into account, (among other factors), the geographical features of the region, as these can lead to signal degradation. This is particularly important in Brazil, where ...

Comparison of Natural Language Processing Rules-based and Machine-learning Systems to Identify Lumbar Spine Imaging Findings Related to Low Back Pain.

Academic radiology
RATIONALE AND OBJECTIVES: To evaluate a natural language processing (NLP) system built with open-source tools for identification of lumbar spine imaging findings related to low back pain on magnetic resonance and x-ray radiology reports from four hea...

Relative location prediction in CT scan images using convolutional neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Relative location prediction in computed tomography (CT) scan images is a challenging problem. Many traditional machine learning methods have been applied in attempts to alleviate this problem. However, the accuracy and spee...

Prediction of DNase I hypersensitive sites in plant genome using multiple modes of pseudo components.

Analytical biochemistry
DNase I hypersensitive sites (DHSs) are accessible chromatin zones hypersensitive to DNase I endonucleases in plant genome. DHSs have been used as markers for the presence of transcriptional regulatory elements. It is an important complement to devel...

PON-tstab: Protein Variant Stability Predictor. Importance of Training Data Quality.

International journal of molecular sciences
Several methods have been developed to predict effects of amino acid substitutions on protein stability. Benchmark datasets are essential for method training and testing and have numerous requirements including that the data is representative for the...

A hybrid model based on neural networks for biomedical relation extraction.

Journal of biomedical informatics
Biomedical relation extraction can automatically extract high-quality biomedical relations from biomedical texts, which is a vital step for the mining of biomedical knowledge hidden in the literature. Recurrent neural networks (RNNs) and convolutiona...

Sequential regulatory activity prediction across chromosomes with convolutional neural networks.

Genome research
Models for predicting phenotypic outcomes from genotypes have important applications to understanding genomic function and improving human health. Here, we develop a machine-learning system to predict cell-type-specific epigenetic and transcriptional...

Machine learning approaches for large scale classification of produce.

Scientific reports
The analysis and identification of different attributes of produce such as taxonomy, vendor, and organic nature is vital to verifying product authenticity in a distribution network. Though a variety of analysis techniques have been studied in the pas...

Prediction and early detection of delirium in the intensive care unit by using heart rate variability and machine learning.

Physiological measurement
OBJECTIVE: Delirium is an important syndrome found in patients in the intensive care unit (ICU), however, it is usually under-recognized during treatment. This study was performed to investigate whether delirious patients can be successfully distingu...