P-glycoprotein (P-gp) is a transmembrane protein that actively transports a wide variety of chemically diverse compounds out of the cell. It is highly associated with the ADMET (absorption, distribution, metabolism, excretion and toxicity) properties...
In the current Information Age, it is usual to access our personal and professional information, such as bank account data or private documents, in a telematic manner. To ensure the privacy of this information, user authentication systems should be a...
The phonocardiogram (PCG) can be used as an affordable way to monitor heart conditions. This study proposes the training and testing of several classifiers based on SVMs (support vector machines), k-NN (k-Nearest Neighbor), and NNs (neural networks)...
Currently, the use of machine learning models for developing intrusion detection systems is a technology trend which improvement has been proven. These intelligent systems are trained with labeled datasets, including different types of attacks and th...
In this day and age, surrounded by innumerable forms of technology, the use of various autonomous systems to recognize various ailments has tremendously benefited the medical industry. An important medical practice is the visual evaluation and counti...
The imbalance and concept drift problems in data streams become more complex in multi-class environment, and extreme imbalance and variation in class ratio may also exist. To tackle the above problems, Hybrid Sampling and Dynamic Weighted-based class...
The Internet of Medical Things (IoMT) interconnects medical devices, software applications, and healthcare services through the internet to enable the transmission and analysis of health data. IoMT facilitates seamless patient care and supports real-...
In industrial applications based on texture classification, efficient and fast classifiers are extremely useful for quality control of industrial processes. The classifier of texture images has to satisfy two requirements: It must be efficient and fa...
The design of multiple human activity recognition applications in areas such as healthcare, sports and safety relies on wearable sensor technologies. However, when making decisions based on the data acquired by such sensors in practical situations, s...
Statistical classification is a critical component of utilizing metabolomics data for examining the molecular determinants of phenotypes. Despite this, a comprehensive and rigorous evaluation of the accuracy of classification techniques for phenotype...
The determination of a reasonable spatial analysis unit is an essential step in urban functional zone (UFZ) division, which significantly affects the results. However, most studies on the division of functional zones are based on excessively large sp...
In this paper, an RGB image with
Background/Objectives: The accurate identification of insect bites from images of skin is daunting due to the fine gradations among diverse bite types, variability in human skin response, and inconsistencies in image quality. Methods: For this work,...
Computed tomography (CT) scans, or radiographic images, were used to aid in the early diagnosis of patients and detect normal and abnormal lung function in the human chest. However, the diagnosis of lungs infected with coronavirus disease 2019 (COVID...
Pest damage is a major factor in reducing crop yield and has negative impacts on the economy. However, the complex background, diversity of pests, and individual differences pose challenges for classification algorithms. In this study, we propose a p...
In this contribution, a novel methodology for multi-class classification in the field of Parkinson’s disease is proposed. The methodology is structured in two phases. In a first phase, the most relevant volumes of interest (VOI) of the brain ar...
The impact of communication through social media is currently considered a significant social issue. This issue can lead to inappropriate behavior using social media, which is referred to as cyberbullying. Automated systems are capable of efficiently...
Currently, high-level synthesis (HLS) methods and tools are a highly relevant area in the strategy of several leading companies in the field of system-on-chips (SoCs) and field programmable gate arrays (FPGAs). HLS facilitates the work of system deve...
Binarized convolutional neural networks (bCNNs) are favored for the design of low-storage, low-power cardiac arrhythmia classifiers owing to their high weight compression rate. However, multi-class classification of ECG signals based on bCNNs is chal...
Nanomaterial-based aptasensors are useful devices capable of detecting small biological species. Determining suitable signal processing methods can improve the identification and quantification of target analytes detected by the biosensor and consequ...
The assignment of secondary structure elements in protein conformations is necessary to interpret a protein model that has been established by computational methods. The process essentially involves labeling the amino acid residues with H (Helix), E...
Skin cancer is a widespread disease associated with eight diagnostic classes. The diagnosis of multiple types of skin cancer is a challenging task for dermatologists due to the similarity of skin cancer classes in phenotype. The average accuracy of m...
This paper proposes the transformation
Essential oils are valuable in various industries, but their easy adulteration can cause adverse health effects. Electronic nasal sensors offer a solution for adulteration detection. This article proposes a new system for characterising essential oil...
Despite their significant environmental benefits, solar photovoltaic (PV) systems are susceptible to malfunctions and performance degradation. This paper addresses detecting and diagnosing faults from a dataset representing a 250 kW PV power plant wi...
Fruit-tree crops generate food and income for local households and contribute to South Africa’s gross domestic product. Timely and accurate phenotyping of fruit-tree crops is essential for innovating and achieving precision agriculture in the h...
Cardiovascular Disease (CVD) is a primary cause of heart problems such as angina and myocardial ischemia. The detection of the stage of CVD is vital for the prevention of medical complications related to the heart, as they can lead to heart muscle de...
In many remote sensing projects on land cover mapping, the interest is often in a sub-set of classes presented in the study area. Conventional multi-class classification may lead to a considerable training effort and to the underestimation of the cla...
Stunting is a condition in which children experience impaired growth and development, caused by malnutrition, repeated infections, and inadequate psychosocial stimulation. It often remains unrecognized due to a lack of awareness in the community. The...
Imbalanced data constitutes a challenge for knowledge management. This problem is even more complex in the presence of hybrid (numeric and categorical data) having missing values and multiple decision classes. Unfortunately, health-related informatio...
Multi-class classification is a fundamental task in Machine Learning. However, complex models can be viewed as black boxes, making it difficult to gain insight into how the model makes its predictions and build trust in its decision-making process. T...
The classification of imbalanced and overlapping data has provided customary insight over the last decade, as most real-world applications comprise multiple classes with an imbalanced distribution of samples. Samples from different classes overlap ne...
Sensor drift is the most challenging problem in gas sensing at present. We propose a novel two-dimensional classifier ensemble strategy to solve the gas discrimination problem, regardless of the gas concentration, with high accuracy over extended per...
The main purpose of this study was to produce landslide susceptibility maps using various ensemble-based machine learning models (i.e., the AdaBoost, LogitBoost, Multiclass Classifier, and Bagging models) for the Sacheon-myeon area of South Korea. A...
For evaluating the classification model of an information system, a proper measure is usually needed to determine if the model is appropriate for dealing with the specific domain task. Though many performance measures have been proposed, few measures...
An intrusion detection system (IDS) identifies whether the network traffic behavior is normal or abnormal or identifies the attack types. Recently, deep learning has emerged as a successful approach in IDSs, having a high accuracy rate with its disti...
The Convolutional Neural Network (CNN) is one of the widely used deep learning models that offers the chance to boost farming productivity through autonomous inference of field conditions. In this paper, CNN is connected to a Support Vector Machine (...
The growth in the number of people suffering from eye diseases determines the relevance of research in the field of diagnosing retinal pathologies. Artificial intelligence models and algorithms based on measurements obtained via electrophysiological...
Motor diagnostics is an important subject for consideration. Electric motors of different types are present in a multitude of object, from consumer goods through everyday use devices to specialized equipment. Diagnostic assessment of motors using aco...
Load distributing band (LDB) mechanical chest compression (CC) devices are used to treat out-of-hospital cardiac arrest (OHCA) patients. Mechanical CCs induce artifacts in the electrocardiogram (ECG) recorded by defibrillators, potentially leading to...
The clinical decision support system provides an automatic diagnosis of human diseases using machine learning techniques to analyze features of patients and classify patients according to different diseases. An analysis of real-world electronic healt...
The aims of this research were to map and analyze the risk of land subsidence in the Seoul Metropolitan Area, South Korea using satellite interferometric synthetic aperture radar (InSAR) time-series data, and three ensemble machine-learning models, B...
Cyberbullying is characterized by deliberate and sustained peer aggression, as well as a power differential between the victim and the perpetrators or abusers. Cyberbullying can have a variety of consequences for victims, including mental health prob...
Multiclass image classification is a complex task that has been thoroughly investigated in the past. Decomposition-based strategies are commonly employed to address it. Typically, these methods divide the original problem into smaller, potentially si...
Multiclass motor imagery classification is essential for brain–computer interface systems such as prosthetic arms. The compressive sensing of EEG helps classify brain signals in real-time, which is necessary for a BCI system. However, compressi...
This work addresses the challenge of classifying multiclass visual EEG signals into 40 classes for brain–computer interface applications using deep learning architectures. The visual multiclass classification approach offers BCI applications a...
Cross-project defect prediction (CPDP) is a practical approach for finding software defects in projects which have incomplete or fewer data. Improvements to the defect prediction accuracy of CPDP—such as the PROMISE repository, the correct clas...
The early detection of melanoma is the most efficient way to reduce its mortality rate. Dermatologists achieve this task with the help of dermoscopy, a non-invasive tool allowing the visualization of patterns of skin lesions. Computer-aided diagnosis...
Malware, short for malicious software, is any software program designed to cause harm to a computer or computer network. Malware can take many forms, such as viruses, worms, Trojan horses, and ransomware. Because malware can cause significant damage...
Recently, digital pathology is an essential application for clinical practice and medical research. Due to the lack of large annotated datasets, the deep transfer learning technique is often used to classify histopathology images. A softmax classifie...
of 18