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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...

Tuberculosis (TB) continues to be one of the foremost public health issues in the world, and remains the second most salient communicable cause of death after COVID-19. In 2022, TB accounted for 10.6 million new infectio...

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...

Abstract Accurate prediction of bio-oil yield from pyrolysis of organic solid waste is still the main problem in the field of biomass valorization, mostly because of high variability in the composition and the heterogene...

Subsurface temperature uncertainty represents a major risk in geothermal drilling, particularly in volcanic systems where permeability, lithology, and fluid circulation create highly heterogeneous thermal regimes. This s...

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...

In this work, a structured hierarchy of hyperdatasets for Monkeypox image classification is presented, aiming to evaluate the robustness and generalization ability of deep classification models for Mpox detection. A syst...

BackgroundNon-suicidal self-injury (NSSI) is common among adolescents and young adults and remains difficult to detect early using conventional approaches. machine learning (ML) has increasingly been applied to develop p...

Abstract Background This study aims to explore spatial heterogeneity within tumors, establish and validate an interpretable machine learning model combining habitat radiomics and deep learning, and investigate its predic...

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...

Abstract Background Colorectal signet ring cell carcinoma (CSRCC) is a rare subtype of colorectal cancer characterized by an exceptionally poor prognosis. Currently, accurate survival prediction models for CSRCC are lack...

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...

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 ...

Abstract Background Musculoskeletal diseases, such as Juvenile Idiopathic Arthritis (JIA), can lead to altered joint mobility and changes in gait pattern. While marker-based motion capture systems are considered the gold...

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...

Manual Gross Tumor Volume (GTV) delineation for radiotherapy is time‑consuming and prone to inter‑observer variability. Deep Learning (DL)-based auto‑segmentation offers faster and more consistent solutions, but tr...

ABSTRACT Intelligent and adaptive defence systems that can quickly thwart changing cyberthreats are becoming more and more necessary in the dynamic and data‐intensive Internet of things (IoT) environment. Using the NSL...

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...

Abstract Background Chronic conditions cause millions of deaths annually worldwide. Remote patient monitoring using wearable devices and sensors, combined with machine learning (ML), offers promising strategies for disea...

Abstract Upper-limb prosthesis users usually lack comprehensive feedback or touch. This significantly hinders their ability to interact with their environment and lead normal lives. This research involves the development...

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...

As green solvents, ionic liquids (ILs) were highly effective for CO2 absorption. However, lots of possible anion–cation combinations made experimental measurement of CO2 solubility for each IL time- and resource-intens...

IntroductionAlthough virtual reality (VR) is increasingly deployed as a tool for education, little is known about how learning modality influences cognitive processing or whether wearable neuroimaging technologies can ac...

Abstract The increase in vehicle ownership and urban population puts a strain on roads and increases traffic congestion within developed and developing nations. Congestion affects an individual’s time and increases an ...