A5087895775- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- AI in cancer detection
- Metallurgy and Material Forming
- Composite Material Mechanics
- Machine Learning in Materials Science
- Titanium Alloys Microstructure and Properties
- Artificial Intelligence in Healthcare and Education
- Liver Disease Diagnosis and Treatment
- Cellular Mechanics and Interactions
- Hepatocellular Carcinoma Treatment and Prognosis
- High-Velocity Impact and Material Behavior
- Ultrasonics and Acoustic Wave Propagation
- Non-Destructive Testing Techniques
- Theoretical and Computational Physics
- Evolutionary Algorithms and Applications
- Machine Learning in Healthcare
- Thermal properties of materials
- Structural Analysis and Optimization
- Hydrogen embrittlement and corrosion behaviors in metals
- Rock Mechanics and Modeling
- Micro and Nano Robotics
- Molecular Communication and Nanonetworks
- Remote Sensing and Land Use
- COVID-19 and healthcare impacts
Yichang Central People's Hospital
2022-2025
China Three Gorges University
2020-2025
Changchun University of Technology
2021-2024
Tsinghua University
2018-2023
China Academy of Space Technology
2023
Determining the macroscopic mechanical properties of composites with complex microstructures is a key issue in many their applications. In this Letter, machine learning-based approach proposed to predict effective elastic arbitrary shapes and distributions inclusions. Using several data sets generated from finite element method, convolutional neural network method developed Young's modulus Poisson's ratio directly window microstructural image. Through numerical experiments, we demonstrate...
Abstract Recent developments of deep learning methods have demonstrated their feasibility in liver malignancy diagnosis using ultrasound (US) images. However, most these require manual selection and annotation US images by radiologists, which limit practical application. On the other hand, videos provide more comprehensive morphological information about masses relationships with surrounding structures than images, potentially leading to a accurate diagnosis. Here, we developed fully...
Abstract A novel windmill‐shaped metasurface (MTS) structure is firstly presented and applied to realise broadband antennas with stable radiation patterns. Different from conventional square MTS structure, the proposed formed by etching several triangular sawtooth slots instead of rectangular on radiating patch. Through characteristic mode analysis, it can be found that exhibits a much broadside within large bandwidth 45.9%. Besides, tapered edges resulted regarded as smoother transitions,...
Droplet collisions are widely observed in daily life and industries. The study of droplet collision dynamics can guide engineering applications in, for examples, inkjet printing, fan cooling, engine spraying. In this Letter, a numerical simulation method is proposed on the basis many-body dissipative particle dynamics. For two droplets same size, post-collision morphology analyzed terms key factors: initial eccentricity parameter Weber number. Then, learned classified conjunction with...
Within COVID-19 there is an urgent unmet need to predict at the time of hospital admission which patients will recover from disease, and how fast they deliver personalized treatments properly allocate resources so that healthcare systems do not become overwhelmed. To this end, we have combined clinically salient CT imaging data synergistically with laboratory testing in integrative machine learning model organ-specific recovery COVID-19. We trained validated our 285 on each separate major...