Runze Wen | Cardiac Imaging | Best Researcher Award

Published on by Cardiology and Cardiovascular Medicine

Dr. Runze Wen | Cardiac Imaging | Best Researcher Award

The First Affiliated Hospital of University of Science and Technology | China

Dr. Runze Wen is an emerging scholar in the field of Cardiac Nuclear Medicine, currently pursuing his doctoral degree at the University of Science and Technology of China. His research focuses on advancing nuclear imaging techniques for cardiovascular diagnostics, with a strong emphasis on enhancing the precision and clinical applicability of cardiac assessments. Despite being at an early stage in his academic career, Dr. Wen has already demonstrated remarkable productivity and impact within the scientific community, with 3 published documents, 13 citations across 13 referencing works, and an h index of 3, a clear indication of the relevance and influence of his research. His investigations often integrate nuclear imaging modalities with innovative diagnostic approaches to improve the understanding of coronary microvascular dysfunction and other complex cardiac conditions. In addition to his academic achievements, Dr. Wen is a Fellow in Training (FIT) member of the American College of Cardiology (ACC), reflecting his commitment to professional development and international collaboration within the cardiology field. His ability to bridge advanced imaging science with clinical cardiology has earned him recognition as a promising young researcher dedicated to transforming cardiovascular diagnostics. Through his ongoing research and active engagement in academic circles, Dr. Runze Wen continues to contribute meaningfully to the future of nuclear cardiology, aiming to enhance patient care through evidence based innovation and interdisciplinary research excellence.

Profiles: Scopus | Orcid

Featured Publications

Wen, R., Xie, Q., Pan, B., Ni, M., Zhu, X., Meng, X., Wei, Z., Wu, X., Li, D., & Wang, X. (2025). Simultaneous 13N-ammonia and gadolinium perfusion using integrated PET–MRI: Diagnostic accuracy in coronary microvascular dysfunction. Frontiers in Medicine

Wen, R., Zhao, M., Chen, C., Yang, Y., & Zhang, B. (2023). A novel nomogram integrated with preablation stimulated thyroglobulin and thyroglobulin/thyroid-stimulating hormone ratio to predict the therapeutic response of intermediate- and high-risk differentiated thyroid cancer patients: A bi-center retrospective study.

Ibtasam Wajid | Cardiovascular Diseases | Best Researcher Award

Published on by Cardiology and Cardiovascular Medicine

Mr. Ibtasam Wajid | Cardiovascular Diseases | Best Researcher Award

Shenzhen University | China

Mr. Ibtasam Wajid is an emerging researcher whose work focuses on the intersection of biomedical engineering, health informatics, and data science, with a particular interest in developing innovative machine learning and deep learning models for improving healthcare outcomes. His research explores how advanced computational techniques can be applied to disease prediction, medical imaging, and clinical decision support, contributing to the growing field of digital health transformation. With an academic background spanning biochemistry, health informatics, and biomedical research, he brings an interdisciplinary perspective to addressing complex challenges in modern medicine. He has authored three research documents, accumulating a total of six citations and holding an h-index of one, reflecting a steadily growing research impact at an early stage of his academic career. Alongside his research contributions, he has actively participated in mentoring undergraduate students, organizing technical workshops, and promoting collaborative learning environments within the scientific community. His ongoing studies and projects continue to focus on integrating artificial intelligence into healthcare systems to enhance accuracy, efficiency, and patient-centered care. Through his dedication to continuous learning and innovation, he demonstrates the potential to make lasting contributions to biomedical science and the advancement of data-driven healthcare solutions worldwide.

Profiles: Scopus | Google Scholar

Featured Publications

Sultan, H., Javed, I., Zubair, M., Iqbal, K., Bilal, M., Iqbal, J., & Wajid, I. (2021). Protein and polysaccharide-based biomaterial for the formation of composite bone scaffold. AlQalam Journal of Medical and Applied Sciences, 4(2), 80–88.

Wajid, I., Dan, L., & Wang, Q. (2025). Hybrid ensemble approaches for cardiovascular disease prediction: Leveraging interpretable AI for clinical insight. Intelligence-Based Medicine, 100297.

Ishaq, S., Afzal, S., Usmani, S. A., Wajid, I., Aziz, A., Tahir, R., Ahmad, A., & Ullah, A. (2025). Inflammatory cell death and leukemia treatment. Critical Reviews in Oncology/Hematology, 104909.