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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 Purpose This study aimed to identify the effectiveness of free water MRI (FW-MRI) features for predicting amyloid-beta (Aβ) statuses in Alzheimer’s disease (AD) by constructing diagnostic models using machine...

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 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 ...

Abstract The primary objective of this study is to develop and validate robust data-driven models for accurately predicting bacterial growth inhibition induced by cerium oxide nanoparticles across different bacterial str...

The sustainable utilization of post-consumer waste glass in concrete has emerged as a promising approach to reduce cement consumption, mitigate landfill disposal, and enhance material performance. However, most previous ...

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,...

Heart disease is rapidly increasing. For early and accurate prediction, advanced machine learning (ML) models are needed. However, the sensitive nature of clinical data, along with strict regulatory constraints, creates ...

People learn from experience, but with considerable individual differences in the degree and type of behavioral adjustments resulting from a given experience. Error driven learning rules provide an elegant framework for ...

BackgroundProstate cancer is the sixth most common cause of cancer-related death in males globally and is often identified as a secondary malignancy. Early detection and appropriate management increase the patient’s li...

Abstract Occupational Health and Safety (OHS), which holds substantial importance due to its profound human implications and far-reaching economic consequences, requires effective management to minimize workplace acciden...

With the rapid advancement of online education, students’ sentiment feedback serves as a pivotal factor in enhancing course quality and refining pedagogical strategies. However, conventional sentiment analysis approach...

ABSTRACT Background and Aim As dental anomalies can significantly affect esthetic and function, early detection and diagnosis are crucial for treatment and minimizing potential negative effects. Artificial intelligence (...

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...

This study aimed to evaluate the performance of deep learning models for segmenting the augmented bone following transalveolar sinus floor elevation (TSFE). Cone-beam computed tomography (CBCT) data from 103 patients und...

BackgroundBlended learning has gained momentum in Indian medical education and has the potential to improve access to knowledge and educational outcomes in underserved areas.ObjectiveThis review sought to identify curren...

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...

This study addresses the limited availability of empirically validated differentiated learning models for inclusive elementary classrooms within the Merdeka Curriculum. It aims to develop and examine the feasibility, pra...

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 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...

IntroductionEarly detection of Alzheimer’s disease (AD) is critical for timely intervention, particularly during the mild cognitive impairment (MCI) stage. This study aimed to develop and evaluate a multidomain speech ...

Abstract Background Surgical site infections (SSIs) continue to exert a substantial burden on healthcare systems, particularly in resource-limited settings where they contribute to prolonged hospitalizations, escalated c...

Abstract This study investigates whether machine learning effectively processes high-dimensional data, a challenging task for traditional predictive models, to optimize portfolio strategies. Using daily data from Decembe...

IntroductionAcute Lymphoblastic Leukemia (ALL) is a hematological malignancy, which is life-threatening and demands rapid and precise diagnosis to either enhance or worsen the survival chances. Traditional diagnostic met...