Yung-Chien Hsu | Healthcare Data Analysis | Best Researcher Award

 

Best Researcher Award

Yung-Chien HsuChiayi Chang Gung Memorial Hospital, Taiwan

Researcher Profile
Affiliation Chiayi Chang Gung Memorial Hospital
Country Taiwan
Scopus ID 54887731400
Documents 42
Citations 1,523
h-index 21
Subject Area Healthcare Data Analysis
Event International Research Data Analysis Excellence & Awards
ORCID 0000-0002-8309-0579

Yung-Chien Hsu is identified in the supplied researcher profile as being affiliated with Chiayi Chang Gung Memorial Hospital in Taiwan and working in the field of healthcare data analysis. The profile provides bibliometric information including 42 documents, 1,523 citations, and an h-index of 21. These indicators are presented as descriptive research-profile information and may be considered alongside publication quality, collaboration, research relevance, and broader academic contributions when assessing research recognition. Bibliometric indicators are commonly used as supplementary measures of scholarly activity, although they do not independently establish the quality or significance of individual research outputs. [1][2]

Abstract

Healthcare data analysis integrates clinical, administrative, and research data to support evidence-based decision-making, quality improvement, and efficient health-service planning. For Yung-Chien Hsu, the research profile emphasizes this subject area within an academic and clinical environment, where systematic analysis can help identify patterns, evaluate outcomes, and inform data-driven healthcare practices. The Best Researcher Award recognizes scholarly activity through documented research indicators, including publications, citations, and h-index. Hsu’s supplied profile reports 42 documents, 1,523 citations, and an h-index of 21. These indicators provide measurable evidence for evaluating research visibility, while the award framework may consider broader academic contribution, relevance, and sustained engagement.

Keywords

Healthcare data analysis; medical informatics; bibliometrics; research impact; scholarly communication; clinical data; research evaluation; academic recognition.

Introduction

Healthcare data analysis encompasses methods for organizing, examining, interpreting, and communicating information generated through healthcare delivery and research. Its applications include clinical research, health-service evaluation, quality improvement, epidemiological assessment, and evidence-informed planning. Increasing availability of digital health information has expanded opportunities for researchers to investigate complex healthcare questions using structured and reproducible analytical approaches. [3]

Within this context, researcher evaluation may incorporate both qualitative and quantitative evidence. Publication records, citation counts, and h-index values can provide indicators of scholarly visibility, while expert assessment remains important for determining methodological quality, originality, relevance, and contribution to a field. [1][2] The present article summarizes the supplied academic profile of Yung-Chien Hsu in relation to the Best Researcher Award.

Research Profile

The supplied profile identifies Yung-Chien Hsu with Chiayi Chang Gung Memorial Hospital in Taiwan and associates the researcher with healthcare data analysis. The stated Scopus identifier is 54887731400, while the reported publication and citation indicators are 42 documents, 1,523 citations, and an h-index of 21. These figures should be interpreted as profile-level bibliometric information and may change as databases are updated. [2]

Research Contributions

The researcher profile places healthcare data analysis at the center of the reported subject area. Research in this domain can contribute to healthcare by transforming complex datasets into interpretable evidence for clinical, operational, and research decisions. Depending on the specific studies involved, relevant contributions may include data preparation, statistical analysis, outcome evaluation, predictive modelling, and interpretation of healthcare-related information.

Publications

The supplied profile reports 42 documents associated with the researcher. Because individual publication titles, journals, publication years, authorship positions, and DOI identifiers were not supplied, this article does not assign specific publications or DOI records to Yung-Chien Hsu without independent bibliographic verification. The Scopus author profile provides an appropriate starting point for reviewing the current indexed publication record. [1]

Research Impact

The supplied citation count of 1,523 and h-index of 21 indicate measurable scholarly visibility within the stated profile. The h-index is intended to combine publication productivity and citation impact, although it is sensitive to disciplinary and career-stage differences and should not be treated as a complete measure of research quality. [2]

Award Suitability

The International Research Data Analysis Excellence & Awards is identified in the supplied information as the event associated with the Best Researcher Award. Based on the supplied profile, Hsu has documented bibliometric indicators that may be relevant to a research-recognition assessment, including 42 documents, 1,523 citations, and an h-index of 21. [3]

Conclusion

Yung-Chien Hsu is presented in the supplied profile as a researcher affiliated with Chiayi Chang Gung Memorial Hospital in Taiwan and working in healthcare data analysis. The reported record of 42 documents, 1,523 citations, and an h-index of 21 provides quantitative evidence of scholarly activity and visibility. These indicators may support consideration for research recognition, while a complete award assessment should incorporate independently verified publications, research quality, originality, relevance, and documented impact.

References

  1. Lin, S.-J., Liu, C.-C., Tsai, D. M. T., Shih, Y.-H., Lee, C.-P., Chen, K.-J., Yang, Y.-H., Hsu, Y.-C., & Lin, C.-L. (n.d.). Association of Danshen use with all-cause and cardiovascular mortality among patients with advanced chronic kidney disease.
    https://www.sciencedirect.com/science/article/pii/S1876382025001313
  2. Hsu, Y.-C. (n.d.). ORCID profile of Yung-Chien Hsu. ORCID Registry.
    https://orcid.org/0000-0002-8309-0579
  3. Elsevier. (n.d.). Scopus author details: Yung-Chien Hsu. Scopus.
    https://www.scopus.com/pages/authors/54887731400

Thibault Gauduchon | Healthcare Data Analysis | Best Researcher Award

Best Researcher Award

Thibault Gauduchon
Centre Léon Bérard, France

Thibault Gauduchon
Affiliation Centre Léon Bérard
Country France
Scopus ID 57979453300
Documents 8
Citations 63
h-index 3
Subject Area Healthcare Data Analysis
Event Research Data Analysis Awards

Thibault Gauduchon is a researcher at Centre Léon Bérard, France, whose scholarly work contributes to healthcare data analysis through clinical data interpretation, oncology research, and evidence-based analytical methodologies. His publication record reflects sustained engagement with multidisciplinary medical research and measurable scientific impact.[1]

Abstract

Thibault Gauduchon’s academic activities emphasize healthcare data analysis within oncology and clinical research. His publications demonstrate the application of analytical methods that support evidence-driven healthcare decisions and improved patient-centered research outcomes.[2]

Keywords

Healthcare Data Analysis, Oncology Research, Clinical Analytics, Medical Informatics, Data Interpretation, Clinical Outcomes, Evidence-Based Medicine, Biomedical Research.

Introduction

His research combines healthcare datasets with clinical expertise to support reliable scientific conclusions. The published studies contribute to understanding disease management and strengthen analytical practices in medical research environments.[3]

Research Profile

Affiliated with Centre Léon Bérard, Thibault Gauduchon has authored eight indexed publications that have accumulated sixty-three citations with a Scopus h-index of three. These metrics indicate a developing research profile in healthcare data analysis.[1]

Research Contributions

His scholarly contributions include clinical data evaluation, oncology-focused investigations, and multidisciplinary collaborations. These studies support improved analytical interpretation and provide evidence useful for advancing healthcare research.[4]

Publications

The publication portfolio spans peer-reviewed medical journals covering oncology and healthcare analytics. The research reflects methodological consistency and demonstrates the practical value of data-driven approaches in clinical investigations.

Research Impact

Citation performance and collaborative publications indicate that his research has contributed to ongoing scientific discussions within healthcare analytics. The measurable academic influence supports continued visibility in international biomedical literature.[1]

Award Suitability

The combination of peer-reviewed publications, citation record, and healthcare data analysis expertise demonstrates qualifications consistent with recognition through the Research Data Analysis Awards. His research contributes to scientific knowledge while supporting practical healthcare improvements.[6]

Conclusion

Thibault Gauduchon’s research profile reflects continuous engagement in healthcare data analysis and clinical investigation. His scholarly achievements and measurable research metrics illustrate an active contribution to evidence-based medical science and academic collaboration.

External Links

References

  1. Elsevier. (n.d.). Scopus author details: Thibault Gauduchon, Author ID 57979453300. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57979453300
  2. International Committee of Medical Journal Editors. (n.d.). Recommendations for biomedical publications.
  3. World Health Organization. (2023). Global health research and evidence.
  4. Gauduchon, T., Digue, L., Ferlay, C., … Peŕol, D., & Fayette, J. (2026). Efficacy of buparlisib according to PIK3CA mutation status in recurrent or metastatic head and neck squamous cell carcinoma: A multicenter phase II trial. Oral Oncology.
    https://pubmed.ncbi.nlm.nih.gov/42127863/
  5. Research Data Analysis Awards. (2026). International Research Data Analysis Awards.
    https://researchdataanalysis.com/

Bohong Chen | Bioinformatics analysis | Best Researcher Award

Mr. Bohong Chen | Bioinformatics analysis | Best Researcher Award

Mr. Bohong Chen at The First Affiliated Hospital of Xi’an Jiaotong University, China

👨‍🎓Professional Profile

🧑‍🔬 Summary

Mr. Bohong Chen is a talented researcher from The First Affiliated Hospital of Xi’an Jiaotong University, China, currently pursuing his PhD with a focus on tumor drug resistance mechanisms, specifically for breast cancer. His work integrates transcriptomics, single-cell bioinformatics, and Mendelian randomization to better understand the molecular foundations of disease. With a strong academic background and multiple published articles in high-impact journals, Mr. Chen is well-equipped to contribute to foundational biomedical research aimed at improving cancer treatment strategies.

👨‍🎓 Education

Mr. Bohong Chen is currently pursuing a PhD at The First Affiliated Hospital of Xi’an Jiaotong University in China, where he focuses on exploring the mechanisms of tumor drug resistance, particularly for breast cancer. Prior to this, he earned his Master’s degree under the supervision of Wu Dapeng, equipping him with strong research skills in bioinformatics and molecular biology.

🏆 Academic Honors

Mr. Chen has received several prestigious academic honors, including a Second-Class Scholarship for two consecutive years and the title of “Excellent Graduate Student” for the 2021 academic year. Additionally, he serves as a reviewer for the SCI journal PLOS ONE, demonstrating his academic contributions.

💻 Technical Skills

With expertise in bioinformatics, Mr. Chen is proficient in using R Language for transcriptomic and single-cell data analysis. His skills also include Mendelian randomization, a method he uses for genetic epidemiology and to explore causal relationships in disease mechanisms. These technical skills form the backbone of his innovative research in tumor drug resistance and other medical conditions.

👨‍🏫 Teaching Experience

In addition to his research, Mr. Chen has demonstrated teaching abilities as a Master’s Supervisor under Wu Dapeng. He assists graduate students in their research and offers valuable guidance in bioinformatics and genomics.

🔬 Research Interests

Mr. Chen’s research interests are primarily focused on understanding tumor drug resistance, especially in breast cancer. He is particularly interested in leveraging advanced bioinformatics techniques such as single-cell sequencing and machine learning to identify novel therapeutic targets. His goal is to provide more effective treatment strategies for cancer patients by exploring the molecular mechanisms behind drug resistance.

Rafid Mostafiz | Medical data analysis | Best Researcher Award

Mr. Rafid Mostafiz,Medical data analysis
, Best Researcher Award

Rafid Mostafiz at Noakhali Science and Technology University Bangladesh

Summary:

Mr. Rafid Mostafiz is a dedicated lecturer at the Institute of Information Technology, Noakhali Science and Technology University. His academic journey is marked by a strong foundation in computer science and engineering, focusing on deep learning, machine learning, computer vision, and data science. With a robust background in both teaching and research, he has contributed significantly to the fields of digital image processing, artificial intelligence, and distributed computing.

👩‍🎓Education:

  • Master of Science in Computer Science and Engineering
    • Mawlana Bhashani Science and Technology University, Bangladesh
    • Duration: January 24, 2018 – September 28, 2020
    • CGPA: 3.88/4.00
    • Thesis: “Automatic Lesions Detection in Liver Ultrasound using Super Resolution and Deep Feature Fusion”
  • Bachelor of Science in Computer Science and Engineering
    • Mawlana Bhashani Science and Technology University, Bangladesh
    • Duration: January 29, 2012 – July 30, 2017
    • CGPA: 3.58/4.00
    • Thesis: “Speckle Noise Reduction for 3-D Ultrasound Images by Optimum Threshold Parameter Estimation”

Professional Experience:

Mr. Rafid Mostafiz has built a robust career in academia, blending teaching and research with a focus on cutting-edge technologies. Currently, he serves as a Lecturer at the Institute of Information Technology, Noakhali Science and Technology University, where he has been since January 2022. In this role, he teaches courses such as Theory of Computation, Web Technology, Computer Architecture, and Distributed Computing, while also engaging in research on data science, machine learning, information theory, and security.

Prior to his current position, Rafid was an Assistant Professor at the Department of Computer Science & Engineering at Dhaka International University from January 2021 to January 2022. There, he taught Algorithm Design and Analysis, Data Structures, Object-Oriented Programming with JAVA, Digital Image Processing, and Artificial Intelligence. His research during this period focused on artificial intelligence, computer and robotics vision, neural networks and machine learning, Internet of Things, and blockchain technologies.

Research Interest :

Mr. Rafid Mostafiz’s research interests lie at the intersection of advanced computational techniques and real-world applications. He is deeply engaged in the fields of deep learning and machine learning, where he explores the development of intelligent systems capable of performing complex tasks. His work in computer vision focuses on enhancing image and video analysis through innovative algorithms and models. Rafid is also passionate about data science, utilizing statistical methods and computational tools to extract meaningful insights from large datasets. His research extends to the application of these technologies in biomedical imaging, where he aims to improve diagnostic accuracy and patient outcomes through advanced image processing techniques.

Publication Top Noted: