We have recently developed a computational approach for hierarchical, genome-based classification of viruses of a family (DEmARC). In DEmARC, virus clusters are delimited objectively by devising a universal family-wide threshold on intra-cluster gene...
Grasslands are one of the most important terrestrial ecosystems on the planet and have significant economic and ecological value. Accurate and rapid discrimination of grassland communities is critical to the conservation and utilization of grassland...
Image recognition and classification have been widely used for research in computer vision systems. This paper aims to implement a new strategy called Wiener-Granger Causality theory for classifying natural scenery images. This strategy is based on s...
This paper proposes an object-based segmentation/classification scheme for remotely sensed images, based on a novel variant of the recently proposed Genetic Sequential Image Segmentation (GeneSIS) algorithm. GeneSIS segments the image in an iterative...
Modern 5G network slicing centers on the precise design of virtual, independent networks operating over a shared physical infrastructure, each configured to meet specific service requirements. This approach plays a vital role in enabling highly custo...
The analysis of ambient sounds can be very useful when developing sound base intelligent systems. Acoustic scene classification (ASC) is defined as identifying the area of a recorded sound or clip among some predefined scenes. ASC has huge potential...
Machine predictive maintenance plays a critical role in reducing unplanned downtime, lowering maintenance costs, and improving operational reliability by enabling the early detection and classification of potential failures. Artificial intelligence (...
Anguillid eels are widely acknowledged for their ecological and socio-economic value in many countries. Yet, knowledge regarding their biodiversity, distribution and abundance remains superficial—particularly in tropical countries such as Indonesia,...
The continuous increase in Android malware applications (apps) represents a significant danger to the privacy and security of users’ information. Therefore, effective and efficient Android malware app-classification techniques are needed. This...
The classification and recognition of radar clutter is helpful to improve the efficiency of radar signal processing and target detection. In order to realize the effective classification of uniform circular array (UCA) radar clutter data, a classific...
Researchers have proposed many models for the identification of malicious URLs in network security, but they have not achieved good results. In order to improve this defect, the current popular machine learning algorithm is combined to train the mode...
The global concern about the gap between food production and consumption has intensified the research on the genetics, ecophysiology, and breeding of cereal crops. In this sense, several genetic studies have been conducted to assess the effectiveness...
Recently, gene selection has played an important role in cancer diagnosis and classification. In this study, it was studied to select high descriptive genes for use in cancer diagnosis in order to develop a classification analysis for cancer diagnosi...
Objectives: Lung cancer is one of the most prevalent cancers worldwide. Accurately determining lung cancer subtypes and identifying high-risk patients are helpful for individualized treatment and follow-up. Our study aimed to establish an effective m...
Accurately classifying degraded images is a challenging task that relies on domain expertise to devise effective image processing techniques for various levels of degradation. Genetic Programming (GP) has been proven to be an excellent approach for s...
Nearest-neighbor classifiers are accurate and easy to deploy, but their memory footprint and inference time grow with the size of the reference set. This paper studies an evolutionary prototype selection strategy for k-nearest neighbor (K-NN) classif...
In this paper we present a new fuzzy reasoning method in which the Choquet integral is used as aggregation function. In this manner, we can take into account the interaction among the rules of the system. For this reason, we consider several fuzzy me...
In the growing field of Natural Language Processing (NLP), transformers have become excessively large, pushing the boundaries of both training and inference compute. Given the size and widespread use of these models, there is now a strong emphasis on...
Picobirnaviruses (PBVs) are small, double stranded RNA viruses with an ability to infect a myriad of hosts and possessing a high degree of genetic diversity. PBVs are currently classified into two genogroups based upon classification of a 200 nt sequ...
Background: The rapid global spread of the monkeypox virus has led to serious issues for public health professionals. According to related studies, monkeypox and other types of skin conditions can spread through direct contact with infected animals,...
The majority of digital images are stored in compressed form. Generally, image classification using convolution neural network (CNN) is done in uncompressed form rather than compressed one. Training the CNN in the compressed domain eliminates the req...
An improved computer-aided diagnosis (CAD) system is proposed for the early diagnosis of Alzheimer’s disease (AD) based on the fusion of anatomical (magnetic resonance imaging (MRI)) and functional (8F-fluorodeoxyglucose positron emission tomog...
Background: Plasma biomarkers are promoted as scalable tools for the staging of Alzheimer’s disease (AD), yet head-to-head comparisons against the clinical scales used to define diagnostic labels remain scarce. Reported gains from machine learn...
Classification of cattle breeds contributes to our understanding of the history of cattle and is essential for an effective conservation of genetic diversity. Here we review the various classifications over the last two centuries and compare the most...
Introduction: Classification of haematological malignancies has evolved over centuries from multiple morphology-based classifications to a single consensus classification, the World Health Organisation (WHO) classification of tumours in 2001, which i...
Background: This study evaluated a custom algorithm that sought to perform a radiogenomic analysis on lung cancer genetic and imaging data, specifically by using machine learning to see whether a custom clustering/classification method could simultan...
Internationally accepted classifications of malignant tumors, developed by the World Health Organization (WHO) and the Union for International Cancer Control (UICC), are based on the histotype, site of origin, morphologic grade, and spread of cancer...
13 December 2024
Based on the single nucleotide polymorphism (SNP) markers developed by whole genome resequencing (WGRS), the relationship and population genetic structure of 53 common apricot (P. armeniaca) varieties were analyzed to provide a theoretical basis for...
In this paper, we propose a crossover operator for genetic algorithms with binary chromosomes populations based on the cellular automata (
Despite the increasing application of machine learning and computational intelligence algorithms in medicine and physiotherapy, accurate classification and prognosis algorithms for postoperative patients in the rehabilitation phase are still lacking....
Electromyography (EMG) processing is a fundamental part of medical research. It offers the possibility of developing new devices and techniques for the diagnosis, treatment, care, and rehabilitation of patients, in most cases non-invasively. However,...
Fatty liver disease is considered a critical illness that should be diagnosed and detected at an early stage. In advanced stages, liver cancer or cirrhosis arise, and to identify this disease, radiologists commonly use ultrasound images. However, bec...
This research introduces a new data-driven methodology for fault detection and isolation in dynamic systems, integrating fuzzy/Bayesian change point detection and decision trees induced by genetic programming for pattern classification. Tracking chan...
The problem of insufficient classification accuracy in fuzzy clustering algorithms for multidimensional data is addressed in this paper. To tackle this issue, an improved genetic algorithm (GA)-based fuzzy controller is proposed, which combines the a...
Congenital spinal deformities (CSDs) are rare but severe conditions caused by abnormalities in vertebral development during embryogenesis. These deformities, including scoliosis, kyphosis, and lordosis, significantly impair patients’ quality of...
The goal of this study was to analyze the genetic and environmental factors of selected meat yield indicators in Fleckvieh cattle in the Czech Republic, through the application of station (S) and field (F) testing methods. Data collected from fattene...
Fruit shape significantly impacts the quality and commercial value of tomatoes (Solanum lycopersicum L.). Precise grading is essential to elucidate the genetic basis of fruit shape in breeding programs, cultivar descriptions, and variety registration...
Any robust classification system depends on its purpose and must refer to accepted standards, its strength relying on predictive values and a careful consideration of known factors that can affect its reliability. In this context, a molecular classif...
Genetic variation between various plant species determines differences in their physio-chemical makeup and ultimately in their hyperspectral emissivity signatures. The hyperspectral emissivity signatures, on the one hand, account for the subtle physi...
Genetic disorders affect over 6% of the global population and pose substantial obstacles to healthcare systems. Early identification of these rare facial genetic disorders is essential for managing related medical complexities and health issues. Many...
The compound classification strategies addressed in this study encounter challenges related to either low efficiency or accuracy. Precise classification of chemical compounds from SMILES symbols holds significant importance in domains such as drug di...
The circadian rhythm plays a crucial role in regulating biological processes, and its disruption is linked to various health issues. Identifying small molecules that influence the circadian period is essential for developing targeted therapies. This...
Studying population structure has made an essential contribution to understanding evolutionary processes and demographic history in forest ecology research. This inference process basically involves the identification of common genetic variants among...
Pancreatic neuroendocrine neoplasms (pNENs) are rare tumors accounting for only 1%–2% of all pancreatic tumors. pNENs are pathologically heterogeneous and are categorized into three groups (neuroendocrine tumor: NET G1, NET G2; and neuroendocrine car...
Multi-sensor systems (MSS) have been increasingly applied in pattern classification while searching for the optimal classification framework is still an open problem. The development of the classifier ensemble seems to provide a promising solution. T...
Astroviruses are a diverse family of viruses that infect a wide range of mammalian and avian hosts. Here we describe the phylogenetic diversity and current classification methodology of astroviruses based on the ORF1b and ORF2 genes, highlighting the...
Worster-Drought syndrome (WDS), also known as congenital suprabulbar paresis, is a rare neurodevelopmental disorder characterized by feeding, swallowing, drooling, and speech disturbances. Currently, it is classified as a subtype of cerebral palsy. H...
The classification of cancer based on gene expression profiles is a central challenge in precision oncology due to the high dimensionality and low sample size inherent in microarray datasets. Effective gene selection is crucial for improving classifi...
The design of efficient electroencephalogram (EEG) classification systems for the detection of mental states is still an open problem. Such systems can be used to provide assistance to humans in tasks where a certain level of alertness is required, l...
Gliomas are the most common primary human brain tumors. They comprise a heterogeneous group of benign and malignant neoplasms that are histologically classified according to the World Health Organization (WHO) classification of tumors of the nervous...
of 26