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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 ...

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...

Waste material, including glass, presents significant environmental challenges due to its non-biodegradable nature and low global recycling rates. Incorporating waste glass into concrete offers a sustainable solution, bu...

Abstract The Internet plays a pivotal role in tackling global climate challenges, particularly in facilitating a transition toward low-carbon behavior. However, the mechanisms by which the Internet shapes low-carbon beha...

Financial institutions constantly face at the risk of default by borrowers which can result in significant financial losses. It is essential to develop an appropriate predictive model for loan default to reduce these ris...

Abstract Crosscutting technologies to resolve several stress factors should be exploited to address multiple nutrient deficiencies in standing crops. Executing translational research is vital for the long-term sustenance...

Abstract While housing price prediction is well-studied, the prediction of large-scale housing conditions remains underexplored due to data limitations. This paper addresses this gap by developing a machine-learning mode...

"In agitated systems, the phase inversion (PI) phenomenon – the mechanism by which a dispersed phase becomes the continuous one – has been studied extensively in an empirical manner and few models have been put for...

This work presents a systematic literature review on the application of Machine Learning algorithms in the development of effective movie recommender systems. With the increasing popularity of movie recommender systems i...

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...

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’...

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 ...

Abstract Backgrounds Neoadjuvant chemoradiation (nCRT) is a standard treatment for rectal carcinoma that reduces tumor size and local recurrence while improving the rate of sphincter preservation. However, many patients ...

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...

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...

Food products are an essential source of human life, so they have a very important place, and it will be important to monitor and determine their quality in a short time. Our study deals with a very important and indispe...

BackgroundIntracranial infection (ICI) is a serious complication following spontaneous intracerebral hemorrhage (ICH) and is associated with prolonged intensive care, increased morbidity, and poor functional outcomes. Ea...

BackgroundChildhood obesity represents a significant global public health challenge. Accurate and rapid prediction models for identifying obesity risk in children and adolescents are essential for facilitating early prev...

Abstract Background Carotid atherosclerosis is a kind of systemic atherosclerosis in the carotid arteries. It remains one of the leading causes of ischemic stroke. However, the efficiency of treatment is insufficient. Th...

Abstract Background Hepatocellular carcinoma (HCC) is a critical condition characterized by unchecked cellular growth in the liver, often leading to systemic inflammation and organ failure. Although its complex molecular...

Abstract Breast cancer is still the most significant contributor to morbidity and mortality among women in China. Despite advances in imaging and molecular testing, few reliable biomarkers exist for early detection and d...

ObjectiveTo develop and internally validate an interpretable, non-invasive machine learning framework to predict detrusor underactivity (DU) in patients with benign prostatic hyperplasia (BPH).MethodsThis retrospective c...