AIMC Topic: Neural Networks, Computer

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LSTM Networks to Improve the Prediction of Harmful Algal Blooms in the West Coast of Sabah.

International journal of environmental research and public health
Harmful algal bloom (HAB) events have alarmed authorities of human health that have caused severe illness and fatalities, death of marine organisms, and massive fish killings. This work aimed to perform the long short-term memory (LSTM) method and co...

Performance Comparisons of AlexNet and GoogLeNet in Cell Growth Inhibition IC50 Prediction.

International journal of molecular sciences
Drug responses in cancer are diverse due to heterogenous genomic profiles. Drug responsiveness prediction is important in clinical response to specific cancer treatments. Recently, multi-class drug responsiveness models based on deep learning (DL) mo...

Evaluation of Mechanical Properties of Materials Based on Genetic Algorithm Optimizing BP Neural Network.

Computational intelligence and neuroscience
In the 21 century, with the increasingly urgent requirements for lightweight in the fields of aviation, aerospace, and electronics, especially automobiles, many properties of magnesium alloy materials, especially the low-density performance character...

An interaction-modeling mechanism for context-dependent Text-to-SQL translation based on heterogeneous graph aggregation.

Neural networks : the official journal of the International Neural Network Society
For the context-dependent Text-to-SQL task, the generation of SQL query is placed in a multi-turn interaction scenario. Each turn of Text-to-SQL must take historical interactive information and database schema into account. Accordingly, how to encode...

Pixel-wise body composition prediction with a multi-task conditional generative adversarial network.

Journal of biomedical informatics
The analysis of human body composition plays a critical role in health management and disease prevention. However, current medical technologies to accurately assess body composition such as dual energy X-ray absorptiometry, computed tomography, and m...

A Hybrid Deep Learning-Driven SDN Enabled Mechanism for Secure Communication in Internet of Things (IoT).

Sensors (Basel, Switzerland)
The Internet of Things (IoT) has emerged as a new technological world connecting billions of devices. Despite providing several benefits, the heterogeneous nature and the extensive connectivity of the devices make it a target of different cyberattack...

Development of Machine Learning Models for Prediction of Osteoporosis from Clinical Health Examination Data.

International journal of environmental research and public health
Osteoporosis is treatable but often overlooked in clinical practice. We aimed to construct prediction models with machine learning algorithms to serve as screening tools for osteoporosis in adults over fifty years old. Additionally, we also compared ...

Investigation of spectrophotometric simultaneous absorption of Salmeterol and Fluticasone in Seroflo spray by continuous wavelet transform and radial basis function neural network methods.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
In this research, the simultaneous absorption of Salmeterol (SAL) and Fluticasone (FLU) in Seroflo spray was investigated using a spectrophotometric device via employing continuous wavelet transform (CWT) and radial basis function neural network (RBF...

BrcaSeg: A Deep Learning Approach for Tissue Quantification and Genomic Correlations of Histopathological Images.

Genomics, proteomics & bioinformatics
Epithelial and stromal tissues are components of the tumor microenvironment and play a major role in tumor initiation and progression. Distinguishing stroma from epithelial tissues is critically important for spatial characterization of the tumor mic...