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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...

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...

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...

Advances in Artificial Intelligence (AI), particularly through Machine Learning (ML) and Deep Learning (DL), have enabled innovative solutions in industries including automotive, healthcare, and transportation. These tec...

In the context of global changes and the complexity of socio-economic systems, making management decisions is becoming an increasingly challenging process. Digital transformation, which has become a key goal for the deve...

ObjectiveDespite the widespread use of immune checkpoint inhibitors (ICIs) improving survival outcomes in non-small cell lung cancer (NSCLC) patients, immune-related adverse events (irAEs) triggered by ICIs have become a...

Abstract Effort estimation remains a persistent challenge in agile software development, particularly at the user story level where iterative delivery is emphasized. Inaccurate estimations can result in misallocated reso...

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...

Abstract Background Interstitial lung disease (ILD) is characterized by marked heterogeneity and an overall poor prognosis, with many patients experiencing rapid progression and high short-term mortality. Accurate early ...

Abstract Background Accurate prediction of response to neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC) is essential for optimizing treatment decisions. This study aimed to deve...

Abstract Proposed research presents a data-driven framework for forecasting municipal solid waste (MSW) generation and emission dynamics in Erode City, India, by employing supervised machine learning algorithms. Leveragi...

Background: Non-traumatic osteonecrosis of the femoral head (ONFH) can progress to severe osteoarthritis without early intervention. The modified light bulb (MLB) and multiple drilling (MD) techniques aim to preserve the...

Abstract Background Thalassemia is the most prevalent single-gene disorder in Sri Lanka, imposing a significant socioeconomic and healthcare burden. Early carrier detection is essential for genetic counselling and the pr...

Customer feedback is pivotal in enhancing service quality and user satisfaction across digital platforms. However, traditional sentiment analysis methods often struggle with informal languages, contextual nuances, and as...

Abstract The accurate prediction of the deterioration of Continuously Reinforced Concrete Pavement (CRCP) is essential for the effective management of pavements and the maintenance of infrastructure. In this study, a co...

The global aviation industry plays a critical role in economic development and international connectivity. However, it also contributes significantly to environmental challenges, particularly through fuel consumption and...

Background Identifying priority projects in industry–education integration is critical for optimizing policy support and resource allocation. While prior studies have primarily relied on qualitative assessments, there ...

Abstract Air pollution is a major environmental and public health challenge in Greater Cairo due to rapid urbanization, intense traffic activity, and recurrent regional dust intrusions. This study presents a data driven ...

IntroductionOsteoarthritis (OA) is a common joint disease characterized by progressive biomechanical deterioration of cartilage tissue. This study aims to develop an explainable ensemble machine learning model capable of...

Mobile Ad-Hoc Networks (MANET) is a type of ad-hoc networks which use less infrastructure, that means the nodes in this network forward the massages without the need of infrastructure such as routers, switches etc. One o...

Financial institutions worldwide face significant challenges in detecting and preventing illicit financial activities, such as money laundering and terrorism financing. Traditional rule-based methods often generate high ...

Abstract Background Advanced machine learning methods combined with large sets of health screening data provide opportunities for diagnostic value in human and veterinary medicine. Hypothesis/Objectives To derive a model...

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...