AIMC Topic: Algorithms

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Deep learning based prediction of species-specific protein S-glutathionylation sites.

Biochimica et biophysica acta. Proteins and proteomics
As a widespread and reversible post-translational modification of proteins, S-glutathionylation specifically generates the mixed disulfides between cysteine residues and glutathione, which regulates various biological processes including oxidative st...

EEG based Classification of Long-term Stress Using Psychological Labeling.

Sensors (Basel, Switzerland)
Stress research is a rapidly emerging area in the field of electroencephalography (EEG) signal processing. The use of EEG as an objective measure for cost effective and personalized stress management becomes important in situations like the nonavaila...

Brain MRI analysis using a deep learning based evolutionary approach.

Neural networks : the official journal of the International Neural Network Society
Convolutional neural network (CNN) models have recently demonstrated impressive performance in medical image analysis. However, there is no clear understanding of why they perform so well, or what they have learned. In this paper, a three-dimensional...

Grid-Based Mobile Robot Path Planning Using Aging-Based Ant Colony Optimization Algorithm in Static and Dynamic Environments.

Sensors (Basel, Switzerland)
Planning an optimal path for a mobile robot is a complicated problem as it allows the mobile robots to navigate autonomously by following the safest and shortest path between starting and goal points. The present work deals with the design of intelli...

HMMPred: Accurate Prediction of DNA-Binding Proteins Based on HMM Profiles and XGBoost Feature Selection.

Computational and mathematical methods in medicine
Prediction of DNA-binding proteins (DBPs) has become a popular research topic in protein science due to its crucial role in all aspects of biological activities. Even though considerable efforts have been devoted to developing powerful computational ...

Segmentation of prostate and prostate zones using deep learning : A multi-MRI vendor analysis.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
PURPOSE: Develop a deep-learning-based segmentation algorithm for prostate and its peripheral zone (PZ) that is reliable across multiple MRI vendors.

Environmental Noise Classification Using Convolutional Neural Networks with Input Transform for Hearing Aids.

International journal of environmental research and public health
Hearing aids are essential for people with hearing loss, and noise estimation and classification are some of the most important technologies used in devices. This paper presents an environmental noise classification algorithm for hearing aids that us...

A Smartphone Lightweight Method for Human Activity Recognition Based on Information Theory.

Sensors (Basel, Switzerland)
Smartphones have emerged as a revolutionary technology for monitoring everyday life, and they have played an important role in Human Activity Recognition (HAR) due to its ubiquity. The sensors embedded in these devices allows recognizing human behavi...

Predicting alcohol dependence treatment outcomes: a prospective comparative study of clinical psychologists versus 'trained' machine learning models.

Addiction (Abingdon, England)
BACKGROUND AND AIMS: Clinical staff are typically poor at predicting alcohol dependence treatment outcomes. Machine learning (ML) offers the potential to model complex clinical data more effectively. This study tested the predictive accuracy of ML al...

New optimization algorithms for neural network training using operator splitting techniques.

Neural networks : the official journal of the International Neural Network Society
In the following paper we present a new type of optimization algorithms adapted for neural network training. These algorithms are based upon sequential operator splitting technique for some associated dynamical systems. Furthermore, we investigate th...