Low transfer rates are a major bottleneck for brain–computer interfaces based on electroencephalography (EEG). This problem has led to the development of more robust and accurate classifiers. In this study, we investigated the performance of va...
Encephalitis and acute disseminated encephalomyelitis (ADEM) are often caused or triggered by viruses—but the specific pathogen commonly remains unidentified in routine care. We explored the use of viral metagenomic next-generation sequencing (...
1 December 2014
The AO classification system for fractures in the adult craniomaxillofacial (CMF) skeleton is organized in anatomic modules in a 3 precision-level hierarchy with account for an increasing complexity and details. Level-1 is most elementary and identif...
Today, clinicians often do diagnosis and classification of diseases based on information collected from several physiological sensor signals. However, sensor signal could easily be vulnerable to uncertain noises or interferences and due to large indi...
Estimating the completion cost accurately in the early phases of construction projects is critical to their success. However, cost overruns are almost inevitable due to the risks inherent in construction projects. Hence, the completion cost fluctuate...
Choledochal cysts (CCs) are rare occurrences presenting as dilatations of biliary structures, which can present as single or multiple dilatations and can appear as both intra- and extrahepatic anomalies. The most widespread classification of CCs is t...
Software bug report classification is a critical process to understand the nature, implications, and causes of software failures. Furthermore, classification enables a fast and appropriate reaction to software bugs. However, for large-scale projects,...
In recent years, a new generation of power grid system, referred to as the Smart Grid, with an aim of managing electricity demand in a sustainable, reliable, and economical manner has emerged. With greater knowledge of operational characteristics of...
Within the field of computer vision, image segmentation and classification serve as crucial tasks, involving the automatic categorization of images into predefined groups or classes, respectively. In this work, we propose a framework designed for sim...
Jacob’s disease is a rare entity consisting of the formation of a pseudojoint between an abnormal coronoid process of the mandible and the inner surface of the zygomatic bone. First described by Jacob in 1899, its diagnosis and definition have...
27 May 2022
As the process of urbanization in China continues to accelerate, the amount of domestic waste generated correspondingly increases and directly affects the living space of residents. This indirectly implies that to reduce the production of municipal s...
The construction of green roofs (GR) combined with rainwater harvesting systems (RWHSs) in buildings can increase the advantages of each of these technologies, being a very promising solution to combat climate change and increase the sustainability o...
22 June 2010
Anteromedial fracture dislocation of the mandibular condyle is common but a superolateral dislocation of an intact condyle is quite rare. Only ∼19 cases of such dislocation have been reported in the world English literature. This type of dislocation...
Few-shot learning is a deep learning subfield that is the focus of research nowadays. This paper addresses the research question of whether a triplet-trained Siamese network, initially designed for multi-class classification, can effectively handle m...
High-quality, openly accessible clinical datasets remain a significant bottleneck in advancing both research and clinical applications within medical artificial intelligence. Case reports, often rich in multimodal clinical data, represent an underuti...
26 March 2021
Background: This cross-sectional study evaluated the utility of the 2018 European Federation of Periodontology/American Academy of Periodontology (EFP/AAP) classifications of epidemiological studies in terms of periodontitis severity, prevalence and...
Rare genetic syndromes, conditions with a global average prevalence of 40 cases/100,000 people, are associated with anatomical, physiological, and neurological anomalies that may affect different body districts, including the oral district. So far, n...
During the ISNS meeting “Newborn Screening for SCID ‘State of the Art’” on 26 and 27 January 2021, the topic of case definitions and related issues were discussed. There is currently a lack of uniform definitions and therefore a lack of uniform regis...
Plant classification requires the eye of an expert in botanics when the subtle differences in stem or petals differentiate between different species. Hence, an accurate automatic plant classification might be of great assistance to a person who studi...
Imbalanced data are a non-trivial problem in deep learning. The high variability in the number of samples composing each category might force learning procedures to become biased towards classes with major cardinality and disregard classes with low i...
Background/Objectives: Mediastinal tumors, regardless of their location, can grow to significant sizes, causing compression-related symptoms. The term “giant” mediastinal tumor is inconsistently defined in the literature. This study prese...
The proper classification of the origins of food products is a crucial issue all over the world nowadays. In this paper, the authors present a device—a multispectral portable fibre-optic reflectometer and signal processing patch—together...
Background: Industry 4.0 (I4.0) has gained significant attention in recent years, with the term Logistics 4.0 (L4.0) emerging in the logistics industry. However, L4.0 remains vague and lacks a unified definition or classification of related technolog...
Random Forest (RF) is a widely used algorithm for classification of remotely sensed data. Through a case study in peatland classification using LiDAR derivatives, we present an analysis of the effects of input data characteristics on RF classificatio...
The rapid growth of household waste not only endangers the environment and people’s health, but also limits social and economic development. The effective sorting and recycling of garbage can control this problem. Adopting a semi-quantitative case st...
Landslide susceptibility maps are widely used in land management and urban planning to delimit potentially problematic areas. In this article we improve their reliability by acting on the frequency ratio method and map classification systems. For the...
One crucial parameter to evaluate the state of the heart after myocardial infarction (MI) is the viability of the myocardial segment, i.e., if the segment recovers its functionality upon revascularization. MRI performed several minutes after the inje...
River deltas boast ecosystem richness, but their efficient conservation and management require consideration of the full spectrum of natural phenomena, including those which are geological. Few specialists have explored the issue of deltaic geologica...
20 May 2021
Chronic lymphocytic leukemia (CLL) is the most common leukemia in adults in Western countries. Its etiology is largely unknown but increasing incidence rates observed worldwide suggest that lifestyle and environmental factors such as diet might play...
Due to the ever-changing business environment, enterprises are facing unprecedented challenges in their new-product development (NPD) processes, while the success and survival of NPD projects have become increasingly challenging in recent years. Thus...
Distinguishing between a dangerous audio event like a gun firing and other non-life-threatening events, such as a plastic bag bursting, can mean the difference between life and death and, therefore, the necessary and unnecessary deployment of public...
Information on crop planting structure serves as a key reference for crop growth monitoring and agricultural structural adjustment. Mapping the spatial distribution of crops through feature-based classification serves as a fundamental component of su...
Multisource data fusion technology integrates the strengths of various data sources, addressing the limitations of relying on a single source. Therefore, it has been widely applied in fields such as lithological classification and mineral exploration...
Modern industries still commonly use traditional methods to visually inspect products, even though automation has many advantages over the skills of human labour. The automation of redundant tasks is one of the greatest successes of Artificial Intell...
Convolutional Neural Networks (CNNs) have garnered significant utilisation within automated image classification systems. CNNs possess the ability to leverage the spatial and temporal correlations inherent in a dataset. This study delves into the use...
To address the challenges of incomplete knowledge representation, independent decision ranges, and insufficient causal decisions in bogie welding decisions, this paper proposes a hybrid decision-making method and develops a corresponding intelligent...
Short-Term Load Forecasting is a very relevant aspect in managing, operating or participating an electric system. From system operators to energy producers and retailers knowing the electric demand in advance with high accuracy is a key feature for t...
Distribution of hydrological parameters is varied under contrasting meteorological conditions. However, how to determine the most suitable parameters on a predefined meteorological condition is challenging. To address this issue, a hydrological predi...
Taxonomy—the classification of species—is an important branch of biology that allows us to systematically understand and study biodiversity. Conventional taxonomy relies heavily on morphological and anatomical structures for classificatio...
Background: Oligodendrogliomas are a molecularly distinct subtype of glioma according to the WHO 2021 tumor classification, defined as isocitrate dehydrogenase (IDH) mutations and 1p/19q co-deletion. This updated classification has changed the approa...
Hyperspectral imagery and advanced classification techniques can significantly enhance remote sensing’s role in forest monitoring. Thanks to recent missions, such as the Italian Space Agency’s PRISMA (PRecursore IperSpettrale della Missio...
Spatial sampling design is important for accurately assessing land use and land cover (LULC) classification results from remote sensing data. Spatial stratification can dramatically improve spatial sampling efficiency by dividing the study area into...
Accurate and timely classification and monitoring of urban functional zones prove to be significant in rapidly developing cities, to better understand the real and varying urban functions of cities to support urban planning and management. Many effor...
Background/Objectives: This work brings to light the importance of forming large training datasets with diverse images generated and proposes an image dataset merging application, namely, the Data Merger App, to streamline the management and synthesi...
In this paper, we investigate the potential of unsupervised feature selection techniques for classification tasks, where only sparse training data are available. This is motivated by the fact that unsupervised feature selection techniques combine the...
The application of Artificial Intelligence to the industrial world and its appliances has recently grown in popularity. Indeed, AI techniques are now becoming the de-facto technology for the resolution of complex tasks concerning computer vision, nat...
New diseases constantly endanger the lives of populations, and, nowadays, they can spread easily and constitute a global threat. The COVID-19 pandemic has shown that the fight against a new disease may be difficult, especially at the initial stage of...
Cultural heritage has numerous developmental prospects that might contribute to the sustainable development and quality of life of communities. However, cultural heritage products have a complex relationship with many sectors. This paper examines Sau...
Mangrove forests are among the world’s most vital coastal ecosystems. Mapping mangrove cover from local to global scales using spectral data and machine learning models is a well-established method. While non-spectral contextual datasets (spati...
Image classification is a very popular machine learning domain in which deep convolutional neural networks have mainly emerged on such applications. These networks manage to achieve remarkable performance in terms of prediction accuracy but they are...
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