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Abstract Accurate tumor targeting is vital in prostate cancer (PCa) radiotherapy for precise dose delivery and minimizing healthy tissue exposure. Currently, no artificial intelligence (AI) tool exists to predict setup d...

Abstract As reported by the World Health Organization (WHO), Skin Cancer (SC) is a growing medical concern with millions of cases diagnosed each year. Deep Learning methods show promising results in early detection and c...

Abstract Lung cancer remains the primary cause of cancer-related deaths throughout the world. The main reason behind this is late diagnosis and the restrictions in the manual interpretation of imaging data. In these days...

Abstract Vision Transformers have demonstrated strong performance across diverse visual tasks; however, their high computational cost due to long token sequences remains a critical challenge. Sequence reduction via pooli...

Abstract Contemporary distribution transformers face modern technological and integration challenges due to modern electrification and load increase. Motivated by the need for improvement of transformer safety, lifetime,...

Abstract Integrated chem-bio characterization of microbial strain libraries can streamline natural product discovery by prioritizing candidate producers. Here, we employ language- and transformer-based models to extract ...

Abstract The transformer architecture has demonstrated significant performance in image super-resolution (SR). However, for existing Transformer-based models, there are common drawbacks. They often fall short in local fe...

Abstract Accurate monitoring and prediction of Chlorophyll-a (Chl-a) concentrations are critical for protecting desalination systems from algal blooms. This study presents an advanced framework employing the Graph Neural...

Abstract Although UNet has proven its success in various tasks involving medical image segmentation, its capacity to capture global context is restricted by the finite receptive field inherent to convolutional operations...

Abstract Glaucoma remains one of the primary causes of irreversible blindness, characterized by gradual damage to the optic nerve, which often goes undetected until advanced stages. Accurate and early diagnosis depends h...

Abstract Air pollution, particularly Nitrogen Dioxide ( $$\text {NO}_2$$ ) and ground-level ozone ( $$\text {O}_3$$ ), poses major risks to human health and the environment, making accurate forecasting essential for effe...

Abstract Production safety and efficiency depends on the reliability of the critical components in industrial equipment. However, signals measured by sensors may have complicated nonlinear and long-term sequential dynami...

Abstract Medical image segmentation is fundamental for delineating lesion and organ boundaries in clinical workflows. While UNet-based models remain widely used, CNN-dominant designs are limited in modeling long-range co...

Abstract Access to large, diverse biomedical datasets is critical for advancing medical research, yet privacy regulations severely restrict data sharing. We present an end-to-end framework for privacy-preserving health d...

Abstract Reliable interpretation of clinical imaging requires integrating complementary evidence across modalities, yet most AI systems remain limited by single-modality analysis and poor generalization across institutio...

Abstract Carbon markets play a critical role in emission reduction and sustainable economic transition; however, carbon price series exhibit high volatility, nonlinear dynamics, and complex cross-feature interactions, ma...

Abstract Recognizing tactical formations is a critical task in professional football performance analytics. However, existing methods often fail to capture the dynamic and continuously evolving nature of modern tactical ...

Abstract Machine-generated music (MGM) has become a groundbreaking innovation with wide-ranging applications, such as music therapy, personalised editing, and creative inspiration within the music industry. However, the ...

Abstract Facial Expression Recognition (FER) demonstrates significant value in practical scenarios such as intelligent human–computer interaction. However, conventional FER methods often struggle to balance performance...

Abstract Surgical planning for clear cell renal cell carcinoma (ccRCC) is highly dependent on tumor aggressiveness. However, current decisions are predominantly based on postoperative pathology, limiting opportunities fo...

Abstract The latent features of RNA sequences are crucial for our understanding of their functions. Thus, Transformer-based nucleotide language models have received widespread attention; however, the O(n²) complexity of...