AIMC Topic: Neural Networks, Computer

Clear Filters Showing 22091 to 22100 of 31376 articles

Applying Deep Neural Networks and Ensemble Machine Learning Methods to Forecast Airborne Pollen.

International journal of environmental research and public health
Allergies to airborne pollen are a significant issue affecting millions of Americans. Consequently, accurately predicting the daily concentration of airborne pollen is of significant public benefit in providing timely alerts. This study presents a me...

Error Tolerance of Machine Learning Algorithms across Contemporary Biological Targets.

Molecules (Basel, Switzerland)
Machine learning continues to make strident advances in the prediction of desired properties concerning drug development. Problematically, the efficacy of machine learning in these arenas is reliant upon highly accurate and abundant data. These two l...

Hyperspectral Image Features Classification Using Deep Learning Recurrent Neural Networks.

Journal of medical systems
The implementation of Deep learning (DL) techniques, Object detection and classification has achieved remarkable results in remote sensing application. Deep learning with Recurrent Neural Network (RNN) technique on hyper-spectral data has been presen...

Detection of DNA base modifications by deep recurrent neural network on Oxford Nanopore sequencing data.

Nature communications
DNA base modifications, such as C5-methylcytosine (5mC) and N6-methyldeoxyadenosine (6mA), are important types of epigenetic regulations. Short-read bisulfite sequencing and long-read PacBio sequencing have inherent limitations to detect DNA modifica...

Ventricular ectopic beat detection using a wavelet transform and a convolutional neural network.

Physiological measurement
OBJECTIVE: Ventricular contractions in healthy individuals normally follow the contractions of atria to facilitate more efficient pump action and cardiac output. With a ventricular ectopic beat (VEB), volume within the ventricles are pumped to the bo...

Combining deep neural networks and engineered features for cardiac arrhythmia detection from ECG recordings.

Physiological measurement
OBJECTIVE: We aim to combine deep neural networks and engineered features (hand-crafted features based on medical domain knowledge) for cardiac arrhythmia detection from short single-lead ECG recordings.

Deep Neural Architectures for Highly Imbalanced Data in Bioinformatics.

IEEE transactions on neural networks and learning systems
In the postgenome era, many problems in bioinformatics have arisen due to the generation of large amounts of imbalanced data. In particular, the computational classification of precursor microRNA (pre-miRNA) involves a high imbalance in the classes. ...

Electrochemical inhibition bacterial sensor array for detection of water pollutants: artificial neural network (ANN) approach.

Analytical and bioanalytical chemistry
This work reports on further development of an inhibition electrochemical sensor array based on immobilized bacteria for the preliminary detection of a wide range of organic and inorganic pollutants, such as heavy metal salts (HgCl, PbCl, CdCl), pest...

Predicting Inpatient Payments Prior to Lower Extremity Arthroplasty Using Deep Learning: Which Model Architecture Is Best?

The Journal of arthroplasty
BACKGROUND: Recent advances in machine learning have given rise to deep learning, which uses hierarchical layers to build models, offering the ability to advance value-based healthcare by better predicting patient outcomes and costs of a given treatm...

Real-time accident detection: Coping with imbalanced data.

Accident; analysis and prevention
Detecting accidents is of great importance since they often impose significant delay and inconvenience to road users. This study compares the performance of two popular machine learning models, Support Vector Machine (SVM) and Probabilistic Neural Ne...