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This research introduces a hybrid modeling framework that combines intricate combustion dynamics with machine learning (ML) to facilitate the decarbonization and retrofitting of traditional diesel engines utilizing Hydro...

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 ...

Background: Conventional HIV testing approaches continue to fall short of overcoming barriers to HIV testing, especially among key and priority populations at higher risk of acquiring and transmitting HIV. Artificial in...

BackgroundYoung women with localized breast cancer represent a clinically distinct population with heterogeneous outcomes, yet age-specific prognostic models remain limited. Conventional risk stratification tools derived...

Abstract Background Landslides are one of the most frequent and damaging disasters in the Nepal Himalaya region, triggered primarily by intense rainfall events. With the increasing impacts of climate change, extreme prec...

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...

In the recent years, a dramatic boost of the research is observed at the junction of photonics, machine learning and artificial intelligence. A new methodology can be applied to the description of a variety of photonic s...

Abstract Backgrounds Acute primary angle-closure glaucoma (APACG) and chronic primary angle-closure glaucoma (CPACG) exhibit distinct clinical features, yet the molecular mechanisms underlying their differing progression...

Abstract Despite significant progress in the Prognostics and Health Management (PHM) domain using pattern learning systems from data, machine learning (ML) still faces challenges related to limited generalization and wea...

Data analytics is the essential component in deriving insights from data obtained from multiple sources. It represents the technology, methods and techniques used to obtain insights from massive datasets. As data increas...

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...

Vegetation optical depth (VOD), as a key parameter of vegetation, plays an important role in the process of vegetation growth and change. The spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) technolog...

Forest growth and yield projection is essential for sustainable forest management planning. In Brazil, the Clutter model is widely applied for yield forecasting and commonly achieves prediction errors below 10%. However,...

Resveratrol, a natural polyphenol, may serve as a potential drug for pulmonary fibrosis (PF). This study uses meta-analysis and machine learning to assess resveratrol's efficacy and optimal treatment on PF animals. Four ...

Zian Zhong,* Liangjin Zhang,* Ping Yu, Bing Xu Department of Neurology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, Hubei, People’s Republic of Ch...

BackgroundThere is limited understanding regarding the factors that predict recreational therapy engagement among veterans in long-term care facilities. We aimed to develop and validate machine learning models to predict...

ObjectiveTo address the issues of parameter optimization and prediction accuracy of the surface roughness of spiral bevel gears, and to overcome the limitations of traditional methods in effectively handling complex nonl...

The article contains a feasibility analysis of using big data of payment systems for building forecasting models for the dynamics of consumer demand as a core factor of the retail turnover. The relevance of this research...

BackgroundPersonal characteristics, income, social capital, and immigration policies influence immigrants’ social integration (SI) in European Union (EU) countries. However, few studies have used machine learning (ML) ...

Atherosclerosis, driven by elevated cholesterol levels, remains a major risk factor for cardiovascular disease. 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGR), the rate-limiting enzyme involved in cholesterol bio...

Abstract Background Machine learning methods are widely used to detect behavioural data patterns. Although these new mathematical methods are useful tools, the interpretation of the results are often ambivalent unless ...

BackgroundSecondary hyperlipidemia is a common and serious complication in patients with clinically diagnosed depressive disorders, yet early screening tools are lacking. This study aims to develop and validate a machine...

Sevgi Ünal,1 Remzi Gürfidan2 1Department of Radiology, Izmir Katip Celebi University Ataturk Training and Research Hospital, Izmir, Türkiye; 2Database, Network Design and Management, Isparta University of Applied Scie...