BACKGROUND: Large language models (LLMs) have demonstrated remarkable capabilities in natural language processing tasks, including medical question-answering (QA). However, individual LLMs often exhibit varying performance across different medical QA...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 10, 2025
Gliomas are the most common malignant primary brain tumors, and grading their severity, particularly the diagnosis of low-grade gliomas, remains a challenging task for clinicians and radiologists. With advancements in deep learning and medical image ...
The progression of Alzheimer's disease is relentless, leading to a worsening of mental faculties over time. Currently, there is no remedy for this illness. Accurate detection and prompt intervention are pivotal in mitigating the progression of the di...
Deep learning primarily operates on images which contain hidden patterns that are quantified through pixel intensities. Deep learning is used to analyze the image patterns and to recognize the objects. The detection process includes the creation of l...
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 ...
In recent years, the prevalence of chronic diseases such as Ulcerative Colitis (UC) has increased, bringing a heavy burden to healthcare systems. Traditional Chinese Medicine (TCM) stands out for its cost-effective and efficient treatment modalities,...
Recognizing the level of driver distraction during the execution of secondary tasks within the intelligent cockpit is crucial for ensuring a seamless interaction between human drivers and intelligent vehicle systems. To address this issue, this paper...
Emotion recognition is a key research area in artificial intelligence, playing a critical role in enhancing human-computer interaction and optimizing user experience design. This study explores the application and effectiveness of ensemble learning m...
International journal of medical informatics
Jun 3, 2025
BACKGROUND AND OBJECTIVE: To develop and validate a machine learning model based on stacking ensemble learning and feature selection strategies to predict vertebral refracture risk after percutaneous vertebroplasty.
Environmental science and pollution research international
May 7, 2025
Accurate slope stability prediction is crucial for mitigating slope failures, but conventional methods are challenging due to their complexity and high data requirements. To overcome these limitations, researchers have used machine learning (ML) tech...
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