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Accurate failure tracing is essential for closed-loop control of CNC machine tools. To address poor interpretability, strong subjectivity, and complex modeling in existing methods, a meta-action failure tracing method is...

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...

Early detection of Parkinson’s disease (PD) through speech analysis offers significant clinical advantages, yet no validated tools exist for Arabic-speaking populations, representing a critical gap in global healthcare...

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 ...

The rapid growth of Internet of Things (IoT) devices, including smartwatches, home assistants, and connected appliances, has brought significant convenience to daily life, but it has also introduced serious security chal...

Abstract Assembly geometric error as a part of the machine tool system errors has a significant influence on the machining accuracy of the multi-axis machine tool. And it cannot be eliminated due to the error propagation...

BackgroundInterstitial fibrosis and tubular atrophy (IFTA) are key pathological features of chronic kidney damage and progression in diabetic nephropathy (DN). Early identification of patients at higher risk of IFTA may ...

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...

BackgroundThe integration of artificial intelligence (AI) into emergency medicine holds promise for enhancing early diagnosis and clinical decision-making. Traditional diagnostic approaches often rely on physician judgme...

The prediction and design of photonic features have traditionally been guided by theory-driven computational methods, spanning a wide range of direct solvers and optimization techniques. Motivated by enormous advances in...

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...

ABSTRACT Background & Aims Dengue is a significant vector‐borne disease that has severely impacted public health in Bangladesh, underscoring the growing importance of digital health in enhancing surveillance and preven...

Abstract Machine-generated music (MGM) has become a groundbreaking innovation with wide-ranging applications, such as music therapy, personalised editing, and creative inspiration within the music industry. However, the ...

Abstract Background Postoperative complications of mediastinal tumors significantly impact patients’ quality of life and long-term outcomes; however, a notable gap in the development of predictive tools for their occur...

Abstract Background Preterm low birth weight (PLBW) is a major global contributor to neonatal morbidity and mortality. This study aims to develop and evaluate a novel artificial neural network (ANN) based predictive mode...

ABSTRACT Background and Aims Familial Mediterranean Fever (FMF) is a monogenic autoinflammatory disease caused by mutations in the MEFV gene, resulting in recurrent inflammatory episodes and a risk of developing amyloido...

Abstract Background Optimization of biotechnological processes is traditionally limited by time-consuming trial-and-error approaches and the complexity of simultaneously optimizing multiple, often conflicting objectives....

Abstract Background Knee osteoarthritis (OA) is a leading global cause of disability, yet conventional tools lack sensitivity for early detection and precise prognostication. Artificial intelligence (AI) and machine lear...

BackgroundArtificial intelligence (AI) has substantial potential to advance periodontal and peri- implant care through novel diagnostic, prognostic, and therapeutic opportunities. Nevertheless, the evidence is scattered ...

Selected aspects of methodological developments in socio-economic research are addressed from a conceptual perspective, with outlining the areas of transformations in methodology, and illustrating the feasibilities of it...

Abstract Previous studies have highlighted the significant impacts of El Niño–Southern Oscillation (ENSO) and the Madden–Julian Oscillation (MJO) on wintertime precipitation over the contiguous United States (CONUS)...