Yuzheng He

ORCID: 0009-0005-9432-646X
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About
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Research Areas
  • Nanofabrication and Lithography Techniques
  • Physical Unclonable Functions (PUFs) and Hardware Security
  • Radiomics and Machine Learning in Medical Imaging
  • Lung Cancer Diagnosis and Treatment
  • Cell Image Analysis Techniques
  • Advanced X-ray and CT Imaging
  • Neurological Disorders and Treatments
  • AI in cancer detection
  • Acute Ischemic Stroke Management
  • Neurological Disease Mechanisms and Treatments

Hebei Medical University
2024-2025

Second Hospital of Hebei Medical University
2024-2025

Hengshui University
2008

Extracting image features can predict the prognosis and treatment effect of non-small cell lung cancer, which has been increasingly confirmed. However, specific operation using 3D-Slicer still lacks standardization. For example, segmentation is manually performed based on window or automatically through mediastinal window. The images used for feature extraction are either enhanced plain scanned. It questionable whether these influencing factors will affect results be affected. This article...

10.1186/s12885-025-14094-z article EN cc-by-nc-nd BMC Cancer 2025-04-17

Rationale: Kartagener syndrome is a rare respiratory disorder caused by genetic mutation that often combines abnormal manifestations of multiple systems. By discussing this case, we will be able to further deepen our understanding and improve the diagnosis rate disease reduce its misdiagnosis rate. Patient concerns: A 62-year-old Chinese man had history bronchiectasis for 5 years developed small amount hemoptysis days before admission. Diagnoses: Peripheral blood tests indicated primary...

10.1097/md9.0000000000000361 article EN Medicine Case Reports and Study Protocols 2025-04-01

Purpose: In situations where pathological acquisition is difficult, there a lack of consensus on distinguishing between adenocarcinoma and squamous cell carcinoma from imaging images, each doctor can only make judgments based their own experience. This study aims to extract features chest CT, sensitive factors through logistic univariate multivariate analysis, model distinguish lung adenocarcinoma. Methods: We downloaded CT scans with clear diagnosis The Cancer Imaging Archive (TCIA),...

10.2147/cmar.s462951 article EN cc-by-nc Cancer Management and Research 2024-06-01

<title>Abstract</title> Purpose Extracting image features can predict the prognosis and treatment effect of non-small cell lung cancer, which has been increasingly confirmed. However, specific operation using 3D-Slicer still lacks standardization. For example, segmentation is manually performed based on window or automatically through mediastinal window. The images used for feature extraction are either enhanced plain scanned. It questionable whether these influencing factors will affect...

10.21203/rs.3.rs-4420586/v1 preprint EN cc-by Research Square (Research Square) 2024-05-30

Anti-counterfeiting technologies are indeed crucial for information security and protecting product authenticity. Traditional anti-counterfeiting methods have their limitations due to clonable nature. Exploring new technologies, particularly those based on pixel-level textures is a promising avenue address the issue high encoding capacity. However, research in this field still its infancy. This work introduces fluorescent label technology with four key characteristics: efficient laser...

10.48550/arxiv.2407.11886 preprint EN arXiv (Cornell University) 2024-07-16

Anti-counterfeiting technologies are indeed crucial for information security and protecting product authenticity. Traditional anti-counterfeiting methods have their limitations due to clonable nature. Exploring new technologies, particularly those based on pixel-level textures, is a promising avenue address the issue high encoding capacity. However, research in this field still its early stages. This work introduces fluorescent label technology with four key characteristics: efficient laser...

10.20517/jmi.2024.36 article EN Journal of Materials Informatics 2024-10-31
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