In healthcare, predictive analysis using unstructured medical data is crucial for gaining insights into patient conditions and outcomes. However, unstructured data, which contains valuable patient information such as symptoms and medical histories, o...
Medical image segmentation is crucial for computer-aided diagnosis and treatment planning, directly influencing clinical decision-making. To enhance segmentation accuracy, existing methods typically fuse local, global, and various other features. How...
Osteoarthritis is a degenerative condition that affects bones and cartilage, often leading to structural changes, including osteophyte formation, bone density loss, and the narrowing of joint spaces. Over time, this process may disrupt the glenohumer...
Marine plastic debris poses a significant environmental threat. In order to study and combat this pollution, efficient and automated detection methods are essential. Hyperspectral imaging and deep learning provide a robust framework for classifying f...
Most conventional crash severity models attempt to achieve a low classification error rate, implicitly assuming the same losses for all classification errors. In this paper, we suggest that this setting has limitations in terms of reasonableness, as ...
International journal of medical informatics
Jul 1, 2025
OBJECTIVE: This study introduces an ensemble framework that integrates Vision Transformer (ViT) and Convolutional Neural Networks (CNN) models to leverage their complementary strengths, generating visualized and decision-transparent recommendations f...
CRISPR-based diagnostics have gained increasing attention as biosensing tools able to address limitations in contemporary molecular diagnostic tests. To maximize the performance of CRISPR-based assays, much effort has focused on optimizing the chemis...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Semi-supervised learning can significantly boost model performance by leveraging unlabeled data, particularly when labeled data is scarce. However, real-world unlabeled data often contain unseen-class samples, which can hinder the classification of s...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Courts require the extraction of crucial information about various cases from heterogeneous evidence lists for knowledge-driven decision-making. However, traditional manual screening is complex and inaccurate when confronted with massive evidence lis...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Many memristive circuits tend to oversimplify the process of emotion generation as a linear event, disregarding crucial factors such as negative feedback and other regulatory mechanisms. In this paper, a memristive circuit of emotion with negative fe...
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