Segmentation of lesions on CT enables automatic measurement for clinical
assessment of chronic diseases (e.g., lymphoma). Integrating large language
models (LLMs) into the lesion segmentation workflow offers the potential to
combine imaging feature... read more
We present a concept of physically unclonable functions utilizing the photoacoustic effect to generate structurally random, inference-resistant cryptographic keys. The system consists of a CuO/SnO₂ nanoparticle composite, where CuO acts as a visible-... read more
Semiconductor biohybrid systems are emerging as promising strategies for enhanced carbon dioxide fixation and synthesis of organic compounds, with the potential to transcend biological limitations. However, the effects of experimental variables on th... read more
Droplet-based microfluidic devices enable the generation of uniform droplets with precise control over size and production rate-key factors in diagnostics and pharmaceutical screening. Achieving such control is essential for enhancing efficiency and ... read more
Pretrained neural networks have attracted significant interest in chemistry
and small molecule drug design. Embeddings from these models are widely used
for molecular property prediction, virtual screening, and small data learning
in molecular chem... read more
Effective financial risk management in healthcare systems requires intelligent decision-making that balances treatment quality with cost efficiency. This paper proposes a novel hybrid framework that integrates reinforcement learning (RL) with knowled... read more
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that
severely impairs cognitive function and quality of life. Timely intervention in
AD relies heavily on early and precise diagnosis, which remains challenging due
to the complex... read more
Magnetic Particle Imaging (MPI) is a recent imaging modality where
superparamagnetic nanoparticles are employed as tracers. The reconstruction
task is to obtain the spatial particle distribution from a voltage signal
induced by the particles. Gener... read more
Large Language Models (LLMs) have shown remarkable capabilities through two
complementary paradigms: Retrieval-Augmented Generation (RAG), which enhances
knowledge grounding, and Reinforcement Learning from Verifiable Rewards (RLVR),
which optimize... read more
Over the past two decades, mobile imaging has experienced a profound
transformation, with cell phones rapidly eclipsing all other forms of digital
photography in popularity. Today's cell phones are equipped with a diverse
range of imaging technolog... read more
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