Automated segmentation of pediatric brain tumors (PBTs) can support precise diagnosis and treatment monitoring, but it is still poorly investigated in literature. This study proposes two different Deep Learning approaches for semantic segmentation of...
The application of sophisticated computer vision techniques for medical image segmentation (MIS) plays a vital role in clinical diagnosis and treatment. Although Transformer-based models are effective at capturing global context, they are often ineff...
Agriculture provides the basics for producing food, driving economic growth, and maintaining environmental sustainability. On the other hand, plant diseases have the potential to reduce crop productivity and raise expenses, posing a risk to food secu...
This study examines the evolving perspective on semantic processing, which has shifted from the traditional view of an isolated semantic memory system to one that recognizes the involvement of dynamic, distributed neural networks. Recent evidence sup...
People's need for English translation is gradually growing in the modern era of technological advancements, and a computer that can comprehend and interpret English is now more crucial than ever. Some issues, including ambiguity in English translatio...
The purpose of this study is to realize the automatic identification and classification of fouls in football matches and improve the overall identification accuracy. Therefore, a Deep Learning-Based Saliency Prediction Model (DLSPM) is proposed. DLSP...
Predicting potential drug-drug interactions (DDIs) from biomedical data plays a critical role in drug therapy, drug development, drug regulation, and public health. However, it remains challenging due to the large number of possible drug combinations...
This paper introduces a novel approach to visual dialogue that is based on neuro-symbolic procedural semantics. The approach builds further on earlier work on procedural semantics for visual question answering and expands it with neuro-symbolic mecha...
Semantic segmentation involves an imminent part in the investigation of medical images, particularly in the domain of microvascular decompression, where publicly available datasets are scarce, and expert annotation is demanding. In response to this c...
International journal of molecular sciences
May 21, 2025
The prediction of microRNA-disease associations (MDAs) is crucial for understanding disease mechanisms and biomarker discovery. While graph neural networks have emerged as promising tools for MDA prediction, existing methods face critical limitations...
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