AIMC Topic: Algorithms

Clear Filters Showing 17711 to 17720 of 28713 articles

An Efficient and Robust Deep Learning Method with 1-D Octave Convolution to Extract Fetal Electrocardiogram.

Sensors (Basel, Switzerland)
The invasive method of fetal electrocardiogram (fECG) monitoring is widely used with electrodes directly attached to the fetal scalp. There are potential risks such as infection and, thus, it is usually carried out during labor in rare cases. Recent ...

Prediction of hERG potassium channel blockage using ensemble learning methods and molecular fingerprints.

Toxicology letters
The human ether-a-go-go-related gene (hERG) encodes a tetrameric potassium channel called Kv11.1. This channel can be blocked by certain drugs, which leads to long QT syndrome, causing cardiotoxicity. This is a significant problem during drug develop...

Self-organizing subspace clustering for high-dimensional and multi-view data.

Neural networks : the official journal of the International Neural Network Society
A surge in the availability of data from multiple sources and modalities is correlated with advances in how to obtain, compress, store, transfer, and process large amounts of complex high-dimensional data. The clustering challenge increases with the ...

Hybrid neural network with cost-sensitive support vector machine for class-imbalanced multimodal data.

Neural networks : the official journal of the International Neural Network Society
Although deep learning exhibits advantages in various applications involving multimodal data, it cannot effectively solve the class-imbalance problem. Herein, we propose a hybrid neural network with a cost-sensitive support vector machine (hybrid NN-...

A learning approach with incomplete pixel-level labels for deep neural networks.

Neural networks : the official journal of the International Neural Network Society
Learning with incomplete labels in Neural Networks has been actively investigated these last years. Among different kinds of incomplete labels, we investigate incomplete pixel-level labels which are tackled in many concrete problems. One of the chall...

Suspended sediment load prediction using artificial neural network and ant lion optimization algorithm.

Environmental science and pollution research international
Suspended sediment load (SSL) estimation is a required exercise in water resource management. This article proposes the use of hybrid artificial neural network (ANN) models, for the prediction of SSL, based on previous SSL values. Different input sce...

Morphological traits of drought tolerant horse gram germplasm: classification through machine learning.

Journal of the science of food and agriculture
BACKGROUND: Horse gram (Macrotyloma uniflorum (Lam.) Verdc.) is an underutilized pulse crop with good drought resistance traits. It is a rich source of protein. Conventional breeding methods for high yielding and abiotic stress tolerant germplasm are...

Machine learning of diffraction image patterns for accurate classification of cells modeled with different nuclear sizes.

Journal of biophotonics
Measurement of nuclear-to-cytoplasm (N:C) ratios plays an important role in detection of atypical and tumor cells. Yet, current clinical methods rely heavily on immunofluroescent staining and manual reading. To achieve the goal of rapid and label-fre...

SUSSOL-Using Artificial Intelligence for Greener Solvent Selection and Substitution.

Molecules (Basel, Switzerland)
Solvents come in many shapes and types. Looking for solvents for a specific application can be hard, and looking for green alternatives for currently used nonbenign solvents can be even harder. We describe a new methodology for solvent selection and ...

Constructing an automatic diagnosis and severity-classification model for acromegaly using facial photographs by deep learning.

Journal of hematology & oncology
Due to acromegaly's insidious onset and slow progression, its diagnosis is usually delayed, thus causing severe complications and treatment difficulty. A convenient screening method is imperative. Based on our previous work, we herein developed a new...