AIMC Topic: Algorithms

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Anti-cancer Peptide Recognition Based on Grouped Sequence and Spatial Dimension Integrated Networks.

Interdisciplinary sciences, computational life sciences
The diversification of the characteristic sequences of anti-cancer peptides has imposed difficulties on research. To effectively predict new anti-cancer peptides, this paper proposes a more suitable feature grouping sequence and spatial dimension-int...

Machine learning principles applied to CT radiomics to predict mucinous pancreatic cysts.

Abdominal radiology (New York)
PURPOSE: Current diagnostic and treatment modalities for pancreatic cysts (PCs) are invasive and are associated with patient morbidity. The purpose of this study is to develop and evaluate machine learning algorithms to delineate mucinous from non-mu...

Obstacle Avoidance of Multi-Sensor Intelligent Robot Based on Road Sign Detection.

Sensors (Basel, Switzerland)
The existing ultrasonic obstacle avoidance robot only uses an ultrasonic sensor in the process of obstacle avoidance, which can only be avoided according to the fixed obstacle avoidance route. Obstacle avoidance cannot follow additional information. ...

FoldHSphere: deep hyperspherical embeddings for protein fold recognition.

BMC bioinformatics
BACKGROUND: Current state-of-the-art deep learning approaches for protein fold recognition learn protein embeddings that improve prediction performance at the fold level. However, there still exists aperformance gap at the fold level and the (relativ...

A Driving Performance Forecasting System Based on Brain Dynamic State Analysis Using 4-D Convolutional Neural Networks.

IEEE transactions on cybernetics
Vehicle accidents are the primary cause of fatalities worldwide. Most often, experiencing fatigue on the road leads to operator errors and behavioral lapses. Thus, there is a need to predict the cognitive state of drivers, particularly their fatigue ...

A Master-Slave Binary Grey Wolf Optimizer for Optimal Feature Selection in Biomedical Data Classification.

BioMed research international
A new master-slave binary grey wolf optimizer (MSBGWO) is introduced. A master-slave learning scheme is introduced to the grey wolf optimizer (GWO) to improve its ability to explore and get better solutions in a search space. Five high-dimensional bi...

Early Prediction of Sepsis Based on Machine Learning Algorithm.

Computational intelligence and neuroscience
Sepsis is an organ failure disease caused by an infection resulting in extremely high mortality. Machine learning algorithms XGBoost and LightGBM are applied to construct two processing methods: mean processing method and feature generation method, a...

COVID-19 Diagnosis from CT Images with Convolutional Neural Network Optimized by Marine Predator Optimization Algorithm.

BioMed research international
In recent years, almost every country in the world has struggled against the spread of Coronavirus Disease 2019. If governments and public health systems do not take action against the spread of the disease, it will have a severe impact on human life...

A method of parameter estimation for cardiovascular hemodynamics based on deep learning and its application to personalize a reduced-order model.

International journal for numerical methods in biomedical engineering
Precise model personalization is a key step towards the application of cardiovascular physical models. In this manuscript, we propose to use deep learning (DL) to solve the parameter estimation problem in cardiovascular hemodynamics. Based on the con...

Digital Twins of the Water Cooling System in a Power Plant Based on Fuzzy Logic.

Sensors (Basel, Switzerland)
In the search for increased productivity and efficiency in the industrial sector, a new industrial revolution, called Industry 4.0, was promoted. In the electric sector, power plants seek to adapt these new concepts to optimize electric power generat...