Publications by authors named "Yisu Ge"

Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by inflammation and pain in the joints, which can lead to joint damage and disability over time. Nanotechnology in RA treatment involves using nano-scale materials to improve drug delivery efficiency, specifically targeting inflamed tissues and minimizing side effects. The study aims to develop and optimize a new class of eco-friendly and highly effective layered nanomaterials for targeted drug delivery in the treatment of RA.

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Based on deep learning, pancreatic cancer pathology image segmentation technology effectively assists pathologists in achieving improved treatment outcomes. However, compared to traditional image segmentation tasks, the large size of tissues in pathology images requires a larger receptive field. While methods based on dilated convolutions or attention mechanisms can enhance the receptive field, they cannot capture long-range feature dependencies.

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Healthcare needs in rural areas differ significantly from those in urban areas. Addressing the healthcare challenges in rural communities is of paramount importance, as these regions often lack access to adequate healthcare facilities. Moreover, technological advancements, particularly in the realm of the Internet of Things (IoT), have brought about significant changes in the healthcare industry.

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The main objectives of neuromorphic engineering are the research, modeling, and implementation of neural functioning in the human brain. We provide a hardware solution that can replicate such a nature-inspired system by merging multiple scientific domains and is based on neural cell processes. This work provides a modified version of the original Fitz-Hugh Nagumo (FHN) neuron using a simple 2 term called Hybrid Piece-Wised Base-2 Model (HPWBM), which accurately reproduces numerous patterns of the original neuron model.

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Article Synopsis
  • Two-dimensional Layered double hydroxides (LDHs) are promising for biomedical uses due to their ability to deliver drugs effectively and interact well with biological systems, particularly in treating conditions like Rheumatoid Arthritis (RA).
  • The study developed a modified version of LDHs, called LDH-DS, which targets the affected areas and responds to pH changes, showing effective drug loading and release properties.
  • Using a generative adversarial network (GAN) for analysis, the research confirmed high accuracy in the delivery system and demonstrated that LDHs significantly enhance drug delivery effectiveness, with notable statistical improvements in therapeutic outcomes.
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Outer ear infections (OEs) affect millions of people each year and are associated with significant medical costs.The usage of multiple antibiotics to treat ear contamination is a concern because it can have an environmental impact, especially on soil and water.The increased use of antibiotics has exposed bacterial ecosystems to high concentrations of antibiotic residues.

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A significant portion of the solid waste filling landfills worldwide is debris from construction and demolition projects. Across the world, a significant portion of the solid waste filling landfills is made up of construction and demolition waste. Recycling construction waste may help cut down on the quantity of waste sent to landfills and the requirement for energy and other natural resources.

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Foot & ankle deformity is a chronic disease with high incidence and is best treated in childhood. However, the current diagnostic procedures rely on doctor's consultation and empirical judgment, and lack objective and quantitative evaluation methods, resulting in low screening rates. To solve this problem, this paper aims to construct an evaluation model for children's foot & ankle deformity through data mining and machine learning technologies.

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Neuromorphic engineering is an essential science field which incorporates the basic aspects of issues together such as: physics, mathematics, electronics, etc. The primary block in the Central Nervous System (CNS) is neurons that have functional roles such as: receiving, processing, and transmitting data in the brain. This paper presents Wilson Multiplierless Neuron (WMN) model which is a modified version of the original model.

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Many current convolutional neural networks are hard to meet the practical application requirement because of the enormous network parameters. For accelerating the inference speed of networks, more and more attention has been paid to network compression. Network pruning is one of the most efficient and simplest ways to compress and speed up the networks.

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