Md Nahid Uz Zaman | Nursing and Health Professions | Research Excellence Award

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Md Nahid Uz Zaman | Nursing and Health Professions | Research Excellence Award

Hokkaido University |  Japan

Mr. Md. Nahid Uz Zaman is a registered nurse and global health researcher with more than a decade of professional experience across government and private healthcare systems. Academically distinguished, he ranked first in his Bachelor of Science in Nursing and holds two master’s degrees, one in Nutritional Science and Food Technology and another in Public Health with a specialization in Epidemiology. He is currently pursuing doctoral studies at Hokkaido University, Japan, supported by a prestigious JICA scholarship. His research centers on menstrual health and hygiene (MHH), gender equity, and water, sanitation, and hygiene (WASH) in low-resource settings, with funding support from the Bill & Melinda Gates Foundation. His work emphasizes equity-driven, culturally responsive approaches to improving health outcomes for marginalized populations. He has conducted extensive fieldwork across South and Southeast Asia as well as Japan, generating comparative insights into community health systems and social determinants of health. His research has been presented at leading international forums, including the Sustainable Research and Innovation (SRI) Conference in Finland, reflecting strong engagement with the global research community.

Citation Metrics (Google Scholar)

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Thomas Heston | Health Professions | Best Research Article Award

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Thomas Heston | Health Professions | Best Research Article Award

Washington State University | United States

Dr. Thomas F. Heston, MD, is a distinguished physician, researcher, and academician with over 1,500 citations and an h-index of 22, reflecting his significant contributions to medical science and emerging technologies. He currently serves as Clinical Associate Professor in the Department of Medical Education and Clinical Sciences at Washington State University, Spokane, and as Clinical Assistant Professor of Family Medicine at the University of Washington School of Medicine, Seattle. Dr. Heston holds multiple advanced qualifications, including a Doctor of Medicine from Saint Louis University School of Medicine, a Fellowship in Nuclear Medicine from Johns Hopkins School of Medicine, and an MS in Cryptocurrency and Blockchain Technology from the University of Nicosia, Cyprus—highlighting his interdisciplinary expertise bridging medicine and digital innovation. His academic journey also includes residencies at the University of Washington and Oregon Health and Science University, an internship at Duke University, and undergraduate degrees in Mathematics and Music from the University of the State of New York and the University of Washington, respectively. Board-certified in Artificial Intelligence in Medicine, Family Medicine, Nuclear Cardiology, and Nuclear Medicine, Dr. Heston’s work spans nuclear imaging, clinical education, artificial intelligence, and healthcare innovation. His research integrates data-driven medical diagnostics with emerging technologies, advancing precision medicine and ethical AI in healthcare. Through his teaching, publications, and clinical expertise, Dr. Heston continues to inspire innovation and evidence-based excellence in modern medical practice.

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Featured Publications

Heston, T. F., & Khun, C. (2023). Prompt engineering in medical education. International Medical Education, 2(3), 198–205.

Heston, T. F., & Lewis, L. M. (1992). Gender bias in the evaluation and management of acute nontraumatic chest pain. Family Practice Research Journal, 12(4), 383–389.

Goldsmith, S. J., Parsons, W., Guiberteau, M. J., Stern, L. H., Lanzkowsky, L., & Heston, T. F., et al. (2010). SNM practice guideline for breast scintigraphy with breast-specific γ-cameras 1.0. Journal of Nuclear Medicine Technology, 38(4), 219–224.

Heston, T. F. (2017). A case study in blockchain health care innovation. International Journal of Current Research, 9(11), 60587–60588.

Heston, T. F. (2023). Safety of large language models in addressing depression. Cureus, 15(12), e50729.

Heston, T. F. (2011). Standardizing predictive values in diagnostic imaging research. Journal of Magnetic Resonance Imaging, 33(2), 505–505.

Heston, T. F., & Sigg, D. M. (2005). Quantifying transient ischemic dilation using gated SPECT. Journal of Nuclear Medicine, 46(12), 1990–1996.

Heston, T. F., & Wahl, R. L. (2010). Molecular imaging in thyroid cancer. Cancer Imaging, 10(1), 1.