Accurate classification of biomedical signals is crucial for advancing non-invasive diagnostic methods, particularly for identifying gastrointestinal and related medical conditions where conventional techniques often fall short. An ensemble learning ...
Accurate real-time optical diagnosis that distinguishes neoplastic from non-neoplastic colorectal lesions during colonoscopy can lower the costs of pathological assessments, prevent unnecessary polypectomies, and help avoid adverse events. Using a mu...
The assessment of Intercultural Competence (IC) is increasingly recognized as an essential component of students' professional competency development in higher education settings. This study looks at the objectives of creating ICC and offers an asses...
With the rapid advancement of urbanization and industrialization in cities, air pollution has become one of the significant environmental challenges and issues in many countries. The concentration of particulate matter with an aerodynamic diameter of...
This study developed machine learning models to predict Aβ positivity in Alzheimer's disease by integrating early-phase F-Florbetaben PET and clinical data to improve diagnostic accuracy. Furthermore, the study explored machine learning models to pre...
Renal stones (RS) are common urologic condition with unclear pathogenesis. Role of aging-related differentially expressed genes (ARDEGs) in RS remains poorly understood. This study aims to identify potential aging-related biomarkers for RS, explore t...
Depression is a prevalent mental health disorder, and early detection is crucial for timely intervention. Traditional diagnostics often rely on subjective judgments, leading to variability and inefficiency. This study proposes a fusion model for auto...
Convolutional Neural Networks (CNNs), a sophisticated deep learning technique, have proven highly effective in identifying and classifying abnormalities related to various diseases. The manual classification of these is a hectic and time-consuming pr...
The universal demand for the development and deployment of responsive medical infrastructure and damage control techniques, including the application of technology, is the foremost necessity that emerged immediately in the post-pandemic era. Numerous...
Living kidney donors typically experience approximately a 30% reduction in kidney function after donation, although the degree of reduction varies among individuals. This study aimed to develop a machine learning (ML) model to predict serum creatinin...
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