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Periodontitis is periodontal inflammation in response to plaque bacterial antigens, causing damage to periodontal ligament and alveolar bone resorption. Bone graft material combination i.e. demineralized freeze-dried bon...

Abstract The growing importance of machine learning in geological data computing, as well as in the broader geoscience and energy sectors, makes it essential to evaluate the impact of data augmentation on model performan...

Today still there remains some questions about renal transplantation to the ones who had bladder augmentation due to improper bladder dynamics. From a lot of centers the reports with small numbers and short follow up per...

Insufficient width of the alveolar ridge often prevents ideal implant placement. Guided bone regeneration, bone grafting, alveolar ridge splitting and combinations of these techniques are used for the lateral augmentatio...

ABSTRACT Graph contrastive learning (GCL) has emerged as a dominant paradigm for self‐supervised representation learning for attributed graph data. However, existing GCL methods heavily rely on empirical graph data aug...

Abstract Background There have been emerging clinical trials investigating the efficacy of synthetic-graft-augmented autografts in anterior cruciate ligament reconstruction (ACLR) in recent years. Hamstring tendon and Li...

Reliable trajectory similarity estimation underpins applications such as map matching, mobility anomaly detection, and travel behavior analysis. However, traditional distance-based methods are computationally expensive a...

One such serious problem in machine learning (ML) is imbalanced datasets. Minority class samples are usually sparse but hold significant meaning. The model can become biased toward the majority class due to unbalanced cl...

Abstract Air pollution, particularly Nitrogen Dioxide ( $$\text {NO}_2$$ ) and ground-level ozone ( $$\text {O}_3$$ ), poses major risks to human health and the environment, making accurate forecasting essential for effe...

Learners face numerous hurdles while acquiring a second language. The use of mobile applications and digital technologies in language learning enhances the language proficiency of the learners. The objective of the study...

Botnet communications often rely on Domain Generation Algorithms (DGAs) to establish channels among attack orchestrators and compromised hosts (bots). Our approach leverages on Artificial Intelligence (AI) to differentia...

OBJECTIVE: The aim of this study was to assess central hemodynamics and parameters of arterial stiffness of cases with nocturnal blood pressure rise. MATERIAL and METHODS: In this retrospective study, ambulatory blood ...

Tumors are a deadly condition often triggered by a range of abnormal modifications and genetic abnormalities. Early tumor diagnosis is essential due to the highly concerned nature of the disease. Early detection and trea...

OBJECTIVE: The metabolic syndrome (MetS) is an endocrinopathy that increases the risk of cardiovascular disease. Arterial stiffness is commonly used to evaluate the risk of cardiovascular disease, which is quantified by ...

This paper addresses the challenge of packet-based information routing in large-scale communication networks. The problem is framed as a constrained statistical learning task, where each network node operates using only ...

Abstract The co-frequency vibration fault is one of the common faults in the operation of rotating equipment, and realizing the real-time diagnosis of the co-frequency vibration fault is of great significance for monitor...

This study aimed to evaluate the performance of deep learning models for segmenting the augmented bone following transalveolar sinus floor elevation (TSFE). Cone-beam computed tomography (CBCT) data from 103 patients und...

Abstract The inherently low thermal conductivity of phase change materials (PCMs) stills a major limitation for their use in latent heat thermal energy storage (LHTES) units, as it significantly reduces the charging proc...

The current Intraperitoneal Underlay Mesh (IPUM), previously referred to as IPOM (onlay), initially faced several challenges due to design and methodological shortcomings, particularly with the use of a bridging techniqu...

Medical image prediction plays a very significant role in clinical decision-making and early detection and diagnosis of different diseases. However, the quality of medical images has a huge impact on the predictive model...

We tackle the challenging problem of single-source domain generalization (DG) for medical image segmentation, where we train a network on one domain (e.g., CT) and directly apply it to a different domain (e.g., MR) witho...

In the face of socioeconomic challenges, this paper develops and empirically demonstrates the Gondauri Index (GI) as a reproducible, diagnostics-first composite framework for benchmarking macro-financial resilience acros...

The effect of imbalanced data on the optical character recognition of Braille text is investigated by applying two techniques to a set of convolutional neural network image classification models. A multilabel classificat...