Wenqiang Hua | Deep Learning | Research Excellence Award

Dr. Wenqiang Hua | Deep Learning | Research Excellence Award

Xi’an University of Posts and Telecommunications | China

Wenqiang Hua is a Lecturer in the School of Computer Science at Xi’an University of Posts and Telecommunications and a member of the Key Laboratory of Big Data and Intelligent Computing. He holds a Ph.D. in Electronic Circuits and Systems with a strong research focus on deep learning, image classification, and remote sensing image analysis, particularly Polarimetric SAR image classification. His work emphasizes semi-supervised learning, contrastive learning, domain adaptation, feature fusion, and multi-modal neural networks for complex remote sensing scenarios. Dr. Hua has published extensively in leading international journals, including IEEE Geoscience and Remote Sensing Letters, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Remote Sensing, Knowledge-Based Systems, and the International Journal of Applied Earth Observation and Geoinformation. He has also led nationally and provincially funded research projects related to small-sample PolSAR terrain classification. Known for his extroverted, optimistic, and enthusiastic character, he actively engages in interdisciplinary research and academic collaboration.

Citation Metrics (Scopus)

700
500
200
100
 0

Citations
419

Documents
41
h-index
11

Citations

Documents

h-index


View Scopus Profile       View Orcid Profile

Featured Publications


Knowledge and Data Co-Driven Deep Learning Model for PolSAR Image Classification

– Results in Engineering

Class-Discrepancy Dynamic Weighting for Cross-Domain Few-Shot Hyperspectral Image Classification

– Remote Sensing

Semi-Supervised Hybrid Contrastive Learning for PolSAR Image Classification

– Knowledge-Based Systems

Global–Local Multigranularity Transformer for Hyperspectral Image Classification

– IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Yayang Duan | Deep learning | Best Researcher Award

Dr. Yayang Duan | Deep learning | Best Researcher Award

Dr. Yayang Duan, Affiliated First Hospital of Anhui University, China.

Dr. Yayang Duan , an accomplished physician and medical researcher, specializes in ultrasound diagnostics and AI applications in liver disease imaging. With a Doctorate in Imaging and Nuclear Medicine from Anhui Medical University, he has published 8+ SCI papers 📄 and reviewed for top journals like European Radiology 🔍. A recipient of the 2024 Wiley China High Contribution Author Award 🏆, he currently serves at the First Affiliated Hospital of Anhui Medical University, combining clinical excellence with impactful research.

Profile

Scopus Profile

Orcid Profile

Google Scholar Profile

🎓 Early Academic Pursuits

Dr. Yayang Duan embarked on an impressive academic journey rooted in medical imaging. She completed her Bachelor’s degree in Medical Imaging from Bengbu Medical College (2012–2017), followed by a Master’s in Imaging and Nuclear Medicine at Dalian Medical University (2017–2020). Her academic trajectory culminated in a Professional Doctorate in Imaging and Nuclear Medicine from Anhui Medical University (2020–2023), reflecting her unwavering commitment to advanced medical education. 🎓📚

💼 Professional Endeavors

Since July 2023, Dr. Duan has served as a Physician in the Department of Ultrasound Medicine at the First Affiliated Hospital of Anhui Medical University. Her clinical practice centers on medical ultrasound diagnosis across various body systems. Her solid educational background seamlessly integrates with her hands-on clinical skills, enabling her to contribute significantly to patient care and medical research. 🏥🩺

🔬 Contributions and Research Focus On Deep learning

Dr. Duan’s research primarily focuses on liver diseases and the integration of artificial intelligence in clinical diagnostics. She has authored eight SCI-indexed papers as the first or corresponding author, along with one paper in a Chinese core journal, and contributed to ten additional SCI publications. Her expertise bridges the gap between diagnostic imaging and cutting-edge AI applications, driving forward the capabilities of non-invasive diagnostics. 🧬📊

🌍 Impact and Influence

With more than 15 expert peer reviews for prestigious journals such as European Radiology, European Journal of Nuclear Medicine and Molecular Imaging, and iScience, Dr. Duan plays an integral role in shaping the scientific discourse in medical imaging. Her influence extends beyond her own publications, reflecting a trusted voice within the global academic community. 🌐📝

🧠 Research Skills

Dr. Duan is highly proficient in medical ultrasound diagnostics, particularly in abdominal and soft tissue applications. She combines this clinical acumen with technical research expertise in AI-driven imaging analysis, liver pathology, and nuclear medicine. Her skills span both laboratory-based research and real-time patient diagnostics. 🖥️🔍

🏅 Awards and Honors

In recognition of her scholarly impact, Dr. Duan was awarded the 2024 Q1 Wiley China High Contribution Author Award 🏆—a testament to her dedication, high-quality publications, and thought leadership in medical research.

🏛️ Legacy and Future Contributions

With a promising career ahead, Dr. Duan is poised to make lasting contributions to ultrasound medicine, AI-integrated diagnostics, and clinical education. As a rising star in medical imaging, she embodies a unique blend of academic excellence, clinical dedication, and innovation that will shape the future of diagnostic medicine. 🚀📌

Publications Top Notes

  • 📄 Title: Performance of a generative adversarial network using ultrasound images to stage liver fibrosis and predict cirrhosis based on a deep-learning radiomics nomogram
    📘 Journal: Clinical Radiology
    📊 Citations: 16
    📅 Year: 2022

  • 📄 Title: Clinical value of hemodynamic changes in diagnosis of hepatic encephalopathy after transjugular intrahepatic portosystemic shunt
    📘 Journal: Scandinavian Journal of Gastroenterology
    📊 Citations: 14
    📅 Year: 2022

  • 📄 Title: Development of a machine learning-based model to predict prognosis of alpha-fetoprotein-positive hepatocellular carcinoma
    📘 Journal: Journal of Translational Medicine
    📊 Citations: 11
    📅 Year: 2024

  • 📄 Title: Radiomics analysis of breast lesions in combination with coronal plane of ABVS and strain elastography
    📘 Journal: Breast Cancer: Targets and Therapy
    📊 Citations: 7
    📅 Year: 2023

  • 📄 Title: Performance of two-dimensional shear wave elastography for detecting advanced liver fibrosis and cirrhosis in patients with biliary atresia: a systematic review and meta-analysis
    📘 Journal: Pediatric Radiology
    📊 Citations: 6
    📅 Year: 2023

  • 📄 Title: A sonogram radiomics model for differentiating granulomatous lobular mastitis from invasive breast cancer: A multicenter study
    📘 Journal: La Radiologia Medica
    📊 Citations: 6
    📅 Year: 2023

  • 📄 Title: An overview of ultrasound-derived radiomics and deep learning in liver
    📘 Journal: Medical Ultrasonography
    📊 Citations: 5
    📅 Year: 2023

  • 📄 Title: Multimodal radiomics and nomogram‐based prediction of axillary lymph node metastasis in breast cancer: An analysis considering optimal peritumoral region
    📘 Journal: Journal of Clinical Ultrasound
    📊 Citations: 5
    📅 Year: 2023

  • 📄 Title: Diagnostic accuracy of contrast-enhanced ultrasound for detecting clinically significant portal hypertension and severe portal hypertension in chronic liver disease: a meta-analysis
    📘 Journal: Expert Review of Gastroenterology & Hepatology
    📊 Citations: 3
    📅 Year: 2023

  • 📄 Title: Ultrasound-based deep learning radiomics nomogram for the assessment of lymphovascular invasion in invasive breast cancer: a multicenter study
    📘 Journal: Academic Radiology
    📊 Citations: 2
    📅 Year: 2024

  • 📄 Title: Enhancing malignancy prediction in thyroid nodules: A multimodal ultrasound radiomics approach in TI‐RADS category 4 lesions
    📘 Journal: Journal of Clinical Ultrasound
    📊 Citations: 2
    📅 Year: 2024