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

Dr .Rie Nakayama | Diagnostic Analytics | Research Excellence Award

Dr .Rie Nakayama | Diagnostic Analytics | Research Excellence Award

Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Science | Japan

Dr. Rie Nakayama is a Japanese cardiologist and Assistant Professor (Special Appointment) at Okayama University’s Graduate School of Medicine, Dentistry and Pharmaceutical Sciences. She earned her MD from Kagawa University  and completed her PhD in Cardiovascular Medicine at Okayama University. With extensive clinical and academic experience, she specializes in cardiovascular medicine, echocardiography, and cardiac rehabilitation. Dr. Nakayama holds multiple board certifications from leading Japanese medical societies and has received several prestigious awards for her research presentations. Her work reflects a strong commitment to advancing cardiovascular care, clinical research, and medical education in Japan.

View Orcid Profile

Featured Publications

Wei Liang | Healthcare Data Analysis | Best Researcher Award

Dr. Wei Liang | Healthcare Data Analysis | Best Researcher Award

Doctorate at East China University of Science and Technology, China

 Author Profile 👨‍🎓

Early Academic Pursuits 🎓

Dr. Wei Liang embarked on his academic journey at East China University of Science and Technology, where he earned his Bachelor’s degree in Engineering (B.E.) in 2020. His interest in Brain-Computer Interfaces (BCI) and Machine Learning became evident during his undergraduate studies, setting the stage for his continued academic success. Currently, he is pursuing his PhD at the same institution, delving deeper into the intersection of neuroscience, computer science, and biomedical engineering. His early education laid a strong foundation for his research in the emerging field of BCI technology.

Professional Endeavors 💼

As a PhD candidate, Wei Liang is already contributing to the rapidly evolving field of Brain-Computer Interfaces, particularly in motor imagery and neural signal processing. His research involves collaboration with prominent experts in the fields of computer science, neuroscience, and biomedical engineering, such as Andrzej Cichocki, Ian Daly, and Brendan Allison. Liang’s professional journey has been shaped by these collaborations, allowing him to gain insights from diverse disciplines, further honing his expertise in BCI.

Contributions and Research Focus 🧠

Wei Liang’s research focuses on advancing Brain-Computer Interface (BCI) technology, particularly in motor imagery and neural signal processing. His work has led to the development of SecNet, a second-order neural network designed to improve motor imagery decoding from electroencephalography (EEG) signals. Liang’s innovative approaches include variance-preserving spatial patterns for EEG signal processing and the use of graph convolutional networks for optimal channel selection. These contributions have enhanced the accuracy and reliability of BCI systems, making them more applicable to real-world scenarios such as stroke rehabilitation and neural engineering.

Impact and Influence 🌍

Wei Liang’s work is making significant strides in improving BCI systems, which have far-reaching applications in medicine, rehabilitation, and human-computer interaction. By optimizing EEG decoding strategies, his research could impact the development of more effective neuroprosthetics and assistive technologies for individuals with motor impairments. His collaboration with leading researchers from around the world further amplifies the global impact of his work, positioning him as a rising star in BCI research.

Academic Citations 📚

Despite being in the early stages of his career, Wei Liang has already made a notable impact on the academic community. His research has led to the publication of five papers, accumulating a total of 14 citations and an h-index of 2. Notable papers include works published in Information Processing & Management, Frontiers in Human Neuroscience, and IEEE Journal of Biomedical and Health Informatics, among others. These publications highlight his contributions to improving BCI systems and their applications.

Technical Skills 🛠️

Wei Liang possesses a strong technical skill set, particularly in the areas of machine learning, neural network architecture, and EEG signal processing. He has expertise in developing novel algorithms for motor imagery decoding, including the use of second-order neural networks and graph convolutional networks. Liang is proficient in various computational tools and programming languages necessary for his research, positioning him as an expert in his field.

Teaching Experience 🏫

Though primarily focused on research, Wei Liang’s academic journey has also included some teaching experience, collaborating with faculty and providing guidance to students. His strong academic background, coupled with his research expertise, allows him to mentor and inspire others in the field of Brain-Computer Interfaces.

Legacy and Future Contributions 🌟

Wei Liang’s research trajectory holds great promise for shaping the future of Brain-Computer Interface technology. His innovative methodologies have the potential to revolutionize how we understand and utilize EEG signals for communication and rehabilitation. In the long term, his contributions could lead to breakthroughs in neuroprosthetics, enhancing the quality of life for individuals with disabilities. With continued dedication and innovation, Liang is on track to leave a lasting legacy in the realm of neuroscience and technology.

Teaching and Mentorship 🧑‍🏫

Although Liang is primarily focused on research, his experiences collaborating with top researchers and participating in academia have enriched his teaching and mentorship skills. His ability to translate complex ideas into understandable concepts makes him an effective communicator, ready to guide the next generation of researchers in the field of BCI.

Awards and Recognition 🏆

Wei Liang has been recognized for his groundbreaking research, publishing in high-impact journals and earning accolades for his contributions to BCI technology. As a promising young researcher, he is poised to receive even greater recognition as his work continues to influence and shape the future of the field.

Top Noted Publications📖

Novel Channel Selection Model Based on Graph Convolutional Network for Motor Imagery
    • Authors: W Liang, J Jin, I Daly, H Sun, X Wang, A Cichocki
    • Journal: Cognitive Neurodynamics
    • Year: 2023
Variance Characteristic Preserving Common Spatial Pattern for Motor Imagery BCI
    • Authors: W Liang, J Jin, R Xu, X Wang, A Cichocki
    • Journal: Frontiers in Human Neuroscience
    • Year: 2023
SecNet: A Second Order Neural Network for MI-EEG
    • Authors: W Liang, BZ Allison, R Xu, X He, X Wang, A Cichocki, J Jin
    • Journal: Information Processing & Management
    • Year: 2025
Multiscale Spatial-Temporal Feature Fusion Neural Network for Motor Imagery Brain-Computer Interfaces
    • Authors: J Jin, W Chen, R Xu, W Liang, X Wu, X He, X Wang, A Cichocki
    • Journal: IEEE Journal of Biomedical and Health Informatics
    • Year: 2024
Leveraging Transfer Superposition Theory for StableState Visual Evoked Potential Cross-Subject Frequency Recognition
    • Authors: X He, BZ Allison, K Qin, W Liang, X Wang, A Cichocki, J Jin
    • Journal: IEEE Transactions on Biomedical Engineering
    • Year: 2024