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This study presents a novel machine learning approach to assess human well-being through the analysis of brain wave activities. We developed a Random Forest classifier to categorize brain wave patterns into three states ...

Abstract Background Tuberculous pericardial effusion (TPE) presents significant diagnostic challenges due to its nonspecific clinical presentation and similarities with other types of pericardial effusion. The available ...

Timely access to public healthcare is fundamental human rights and a key measure of social equity. In Thailand, transportation barriers especially in rural and underserved areas continue to restrict equitable access to m...

Abstract Background Identifying factors associated with cardiovascular disease (CVD) is critical for its prevention, but this topic is scarcely investigated in Kashgar prefecture, Xinjiang, northwestern China. We thus...

Introduction: The COVID-19 pandemic has exacerbated mental health challenges, particularly depression among college students. Detecting at-risk students early is crucial but remains challenging, particularly in developin...

Abstract Background Surgical site infections (SSIs) continue to exert a substantial burden on healthcare systems, particularly in resource-limited settings where they contribute to prolonged hospitalizations, escalated c...

Additive manufacturing has become an important tool for fabricating advanced systems and devices for visible nanophotonics. However, the lack of simulation and optimization methods taking into account the essential physi...

Abstract Objective Machine learning-based approaches were applied to explore prognostic risk factors for patients with tuberculous meningitis (TBM) and develop a risk prediction model for their 1-year post-treatment poor...

ObjectiveThis study aimed to identify core inflammatory biomarkers through machine learning approaches and develop an accessible online risk calculator to predict pulmonary consolidation in children with Chlamydia pneumo...

Abstract This study investigates whether machine learning effectively processes high-dimensional data, a challenging task for traditional predictive models, to optimize portfolio strategies. Using daily data from Decembe...

ObjectiveCongenital Hypogonadotropic Hypogonadism (CHH) is a rare disease with an extremely low incidence, and the outcomes of fertility induction therapy in CHH patients exhibit significant interindividual heterogeneity...

Recent developments in artificial intelligence (AI) have made significant improvements in understanding and enhancing pedestrian safety—a vulnerable road user group that receives less attention than motorized road user...

Abstract Background Enchondromas (EC) present cartilaginous tumors that are difficult to differentiate from their intermediate counterpart, atypical cartilaginous tumors (ACT). Histologically, tumor distinction of these ...

Tesis Energía y Ambiente (maestría) - Instituto Tecnológico de Buenos Aires, Buenos Aires - Karlsruher Institut für Technologie, Karlsruhe, 2023 This thesis develops a machine learning framework for the spatial disag...

Photonic device development (PDD) has achieved remarkable success in designing and implementing new devices for controlling light across various wavelengths, scales, and applications, including telecommunications, imagin...

Di-Higgs production at the LHC associated with missing transverse energy is explored in the context of simplified models that generically parameterize a large class of models with heavy scalars and dark matter candidates...

Abstract Occupational Health and Safety (OHS), which holds substantial importance due to its profound human implications and far-reaching economic consequences, requires effective management to minimize workplace acciden...

Abstract This research employs hybrid machine learning techniques to optimize the mechanical properties of 3D-printed polylactic acid (PLA) lattice structures. By integrating random forest (RF) and XGBoost (XGB) algorith...

Abstract Advances in AI have transformed the traditional Internet of Things (IoT) into smarter, more versatile next-generation devices. Enhanced connectivity among sensors, actuators, and appliances boosts data availabil...

Microscopic traffic flow models and simulations are crucial for capturing vehicle interactions and analyzing traffic. They can provide critical insights for transport planning, management, and operation through scenario ...

Abstract Purpose This study aimed to identify the effectiveness of free water MRI (FW-MRI) features for predicting amyloid-beta (Aβ) statuses in Alzheimer’s disease (AD) by constructing diagnostic models using machine...

BackgroundGlobal population aging is accelerating, and China faces a significant challenge with “aging before affluent.” The disabled older adults population in China is projected to reach 58 million by 2050. Early i...

BackgroundTranscriptome−wide association study (TWAS) contributes to discovering novel susceptibility genes related to diseases. Single-cell RNA sequencing (scRNA-seq) has been extensively applied to characterize cellu...

Both The functionality and the non-functionality for what the system does as well as doesn't of software systems requirements are documented in a Software Requirements Specification (SRS). Moreover in requirements engin...