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Introduction Conducting surveys on domestic violence across diverse countries, particularly in lower-middle-income nations like Nepal, poses significant challenges in understanding and addressing the multifaceted dynamic...

Carbon allowances constitute a foundational component of national carbon emission control frameworks, as they govern the equitable distribution of subsequent allocations and directly shape the overall effectiveness of gr...

Abstract Preterm birth (PTB) affects an estimated 15 million infants worldwide each year, raising an enormous challenge in the field of maternal-fetal medicine. This work explores machine learning approaches for disting...

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 Model instability remains a core challenge for data‐driven parameterizations, especially those developed with supervised algorithms, and rigorous methods to address it are lacking. Here, by integrating machine...

Machine-Learned Likelihood (MLL) is a method that, by combining modern machine-learning techniques with likelihood-based inference tests, allows estimating the experimental sensitivity of high-dimensional data sets. Here...

Car classification is important in daily life because there are many distinct types of automobiles made by various manufacturers. Although there are numerous methods for classifying autos, machine learning technologies h...

Abstract Background Bacterial diseases include any illness caused by bacteria. Bacteria are tiny microorganisms that can only be seen with a microscope. Other types of microorganisms include viruses, fungi, and some para...

The mode of teaching and learning had been drastically changed over the decades. Therefore, one approach might not fit into all scenarios. Collaborative learning promotes collaboration between the students in completing ...

The rapid growth and increasing complexity of Internet of Things (IoT) networks require efficient real-time monitoring and anomaly detection mechanisms. Traditional machine learning approaches often struggle to handle th...

Wildfires are among the most destructive natural disasters and pose significant risks to ecosystems, infrastructure, and human lives. This study focuses on wildfire susceptibility mapping in Los Angeles County, a region ...

With the constant advancement of the smart grid, zero-day attack processes in Advanced Metering Infrastructure (AMI) and Supervisory Control and Data Acquisition (SCADA) networks are also continually evolving. This study...

This study investigates the long-term aging effects and structural degradation mechanisms of photovoltaic (PV) modules integrated into smart city furniture, with a particular focus on panels of 10 W, 25 W, and 40 W nomin...

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...

Cloud computing environments face persistent structural challenges in cost control, dynamic resource allocation, and security risk management, which traditional infrastructure approaches fail to address adequately. This ...

Abstract Background Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder that is linked to cardiovascular, metabolic, and neurocognitive complications. However, its diagnosis relies on polysomnograp...

Abstract Alzheimer’s disease, a progressive neurodegenerative disorder, presents a growing global health challenge due to its increasing prevalence and lack of accessible early diagnostic methods. Even though it has en...

BackgroundChronic hepatitis B (CHB) caused by the hepatitis B virus (HBV) remains a major global health burden. The immune-active (IA) phase, characterized by positive Hepatitis B surface antigens (HBsAg), elevated alani...

Contrast-induced acute kidney injury (CI-AKI), the third most common cause of hospital-acquired kidney injury, is associated with poor clinical outcomes, highlighting the need for accurate prediction. In this study, we u...

IntroductionParkinson’s disease (PD) is the second most common neurodegenerative disorder. The risk of frailty is significantly higher in patients with PD than in age-matched individuals without PD. This study aimed to...

Plastic pollution has become a pressing global environmental challenge. Polyethylene terephthalate (PET), one of the most widely used synthetic polymers, represents a major contributor to this problem. The development of...

Background Lupus nephritis (LN) is a leading cause of mortality in patients with systemic lupus erythematosus (SLE), and the accurate classification of renal pathological subtypes is crucial for reducing mortality rates ...

With the continuous expansion of data availability in many large-scale, complex, and networked systems, such as surveillance, security, Internet, and finance, it becomes critical to advance the fundamental understanding ...

A major assumption in many machine learning and data mining algorithms is that the training and future data must be in the same feature space and have the same distribution. However, in many real-world applications, this...