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Materias / palabras clave: machine learning, artificial intelligence, computational physics, reinforcement learning, neural networks, applied algorithms; Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics: Computer e...

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 ...

Background: Climate change increasingly shapes development outcomes, necessitating its integration into evaluation processes. In Africa, recurrent droughts, floods and temperature extremes disrupt progress across sector...

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 ...

Cadmium poses severe threats to ecosystems and human health due to its high toxicity and bioaccumulative nature. The global regulatory limits for Cd are often low at 0.1-0.6 mg kg−1, which is 1 to 2 orders of magnitude...

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 This model is highly helpful in thermal management and complex energy systems, particularly where precise control over heat and mass transfer is required. Solarized nanofluids can be used to improve heat absorpt...

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...

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...

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...

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...

Introduction: This study aimed to identify dental pain using machine learning (ML) algorithms in Brazilian adolescents for public health screening purposes. Methods: Data from 2 cross-sectional waves of the Brazilian Nat...

BackgroundOpioid overdose remains a leading cause of preventable death in the United States. Existing approaches to identify individuals at elevated risk rely on imprecise rule-based criteria that misclassify patients’...

Abstract Per- and polyfluoroalkyl carboxylic acids (PFCAs) are of global concern for their ubiquitous presence in the environment. However, precise quantification of PFCAs remains challenging due to the shortage of stand...

Abstract The Indian Western Himalayan (IWH) region experiences persistent threats from natural hazards mainly influenced by land use and land cover (LULC) changes resulting from rapid urbanization. The present study aims...

The current study uses machine learning and explainable AI to predict Bedaquiline (BDQ) resistance in Mycobacterium tuberculosis clinical isolates and also predicts 15 new BDQ-resistant genes from whole-genome sequencing...

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 ...

Abstract Background Genetic aberrations are among the critical driving factors of lung cancer. Importantly, the impact of genetic variations on proteomic dysregulations with the goal of characterizing potential diagnosti...

Soil erosion is a major environmental concern that affects land productivity and water quality. Although soil erosion is a serious global environmental challenge, understanding its potential influence in the Bardha Water...

Abstract Microrobotic systems offer significant potential for precision medicine by enabling minimally invasive interventions in complex fluidic environments. However, effective operation in these settings requires actua...

Metasurfaces, interacted with artificial intelligence, have now been motivating many contemporary research studies to revisit established fields, e.g., direction of arrival (DOA) estimation. Conventional DOA estimation ...