Xinke Wang | Heart Failure | Best Researcher Award

Published on by Cardiology and Cardiovascular Medicine

Ms. Xinke Wang | Heart Failure | Best Researcher Award

China Medical University | China

Ms. Xinke Wang is a dedicated researcher and master’s scholar at China Medical University, specializing in cardiovascular diseases with a particular focus on heart failure. Her academic background integrates clinical and epidemiological research, emphasizing the translation of basic scientific discoveries into effective clinical applications. Through her work, she strives to elucidate novel mechanisms underlying heart failure progression and identify innovative therapeutic strategies to improve patient care and outcomes. Ms. Wang has contributed significantly to various aspects of research, including data curation, conceptualization, methodology design, software development, formal analysis, validation, and manuscript preparation. Her ability to bridge clinical insight with analytical expertise underscores her commitment to advancing cardiovascular medicine. Collaborating with esteemed institutions such as Kailuan General Hospital, she actively engages in multidisciplinary research aimed at improving diagnostic precision and treatment efficacy in heart failure management. Her growing body of work reflects both academic rigor and practical relevance, contributing to the evolving landscape of cardiovascular research. Ms. Wang’s scholarly efforts exemplify a strong dedication to medical innovation, evidence-based practice, and collaborative science. By combining her expertise in epidemiology with a passion for clinical application, she continues to advance the understanding of cardiovascular health and disease, fostering new approaches that hold promise for enhancing patient outcomes and shaping the future of cardiovascular research.

Profile: Orcid

Featured Publication

Wang, X., Ning, N., Li, Y., Huang, R., Liu, Y., Miao, Y., Zhang, W., Chen, S., Gao, J., Wu, S., et al. (2025). Association of scores on the Life’s Essential 8 scale with progression to type 2 diabetes, heart failure, and death: A multistate Markov model analysis. Maturitas.

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.