Bahar Çiftçi | Healthcare Data Analysis | Best Researcher Award

Best Researcher Award: Bahar Çiftçi

Bahar Çiftçi – Atatürk Üniversitesi ,Turkey

Bahar Çiftçi
Affiliation Atatürk Üniversitesi
Country Turkey
Scopus ID 56798076100
Documents 59
Citations 338
h-index 11
Subject Area Healthcare Data Analysis
Event International Research Data Analysis Excellence & Awards
ORCID 0009-0006-6682-7192

Bahar Çiftçi is a researcher affiliated with Atatürk Üniversitesi in Turkey. The supplied academic profile identifies healthcare data analysis as the subject area and reports 59 documents, 338 citations, and an h-index of 11. These bibliometric indicators provide an overview of reported scholarly activity and offer a starting point for evaluating research output and academic visibility [2].

Abstract

This article presents an academic profile of Bahar Çiftçi, a researcher affiliated with Atatürk Üniversitesi in Turkey. The supplied information identifies healthcare data analysis as the relevant subject area and reports 59 documents, 338 citations, and an h-index of 11. These indicators summarize reported research productivity and citation visibility but should be interpreted alongside qualitative evidence of research quality [1].

Keywords

Bahar Çiftçi; healthcare data analysis; research analytics; bibliometrics; academic publications; citation analysis; h-index; health research; scholarly impact; research recognition

Introduction

Healthcare data analysis involves examining health-related information to identify patterns, evaluate outcomes, and support evidence-based decisions. Researchers in this field contribute to the interpretation of complex datasets and the development of analytical approaches. Bahar Çiftçi’s supplied profile provides a starting point for reviewing research activity, publication output, and scholarly visibility within the identified subject area [3].

Research Profile

Bahar Çiftçi is listed as affiliated with Atatürk Üniversitesi in Turkey, with healthcare data analysis identified as the relevant subject area. The supplied bibliometric information reports 59 documents, 338 citations, and an h-index of 11. These figures provide a quantitative overview of the research profile. The institutional affiliation and publication records should be verified against official academic sources [2].

Research Contributions

Healthcare data analysis supports research through statistical evaluation, data interpretation, identification of patterns, and assessment of health-related outcomes. The available profile identifies this field as relevant to Bahar Çiftçi’s academic work. Specific contributions, methodologies, and findings should be established by reviewing individual publications. This approach ensures that descriptions of research achievements remain evidence-based, accurate, and academically appropriate [1].

Publications

The supplied Scopus profile reports 59 documents associated with Bahar Çiftçi. Publication records can help readers examine research themes, co-authorship, publication venues, and scholarly development over time. Individual article titles, publication dates, and digital object identifiers should be obtained from verified bibliographic records. Reviewing these sources provides a more complete understanding of research output than aggregate metrics alone [2].

Research Impact

The supplied profile reports 338 citations and an h-index of 11, indicating measurable citation activity across the recorded research output. Citation indicators help describe scholarly visibility but may vary according to discipline, publication age, and database coverage. A balanced assessment should also consider methodological rigor, originality, reproducibility, practical relevance, and the influence of individual publications [3].

Award Suitability

The Best Researcher Award provides an opportunity to recognize scholarly activity, research contributions, and sustained academic engagement. Bahar Çiftçi’s supplied profile offers publication and citation indicators for preliminary consideration. A fair evaluation should additionally examine verified publications, originality, research quality, documented contributions, and the award’s eligibility requirements. Bibliometric indicators can support an assessment but cannot independently establish award eligibility or guarantee selection [2].

Conclusion

Bahar Çiftçi’s supplied profile identifies an academic affiliation with Atatürk Üniversitesi in Turkey and a research subject area of healthcare data analysis. The reported 59 documents, 338 citations, and h-index of 11 provide a quantitative overview of scholarly activity. Further evaluation should combine verified publication records with qualitative assessment of research contributions, originality, and award criteria [1].

References

  1. Effect of social support on the treatment adherence of hypertension patients
    https://www.researchgate.net/publication/329516529
  2. The effect of video assisted instruction on central venous catheter application skills, anxiety and satisfaction in nursing students: a randomised controlled study
    https://link.springer.com/article/10.1186/s12909-026-09532-w
  3. Exploring academic mobbing among graduate nursing students: a mixed-methods study
    https://link.springer.com/article/10.1186/s12909-026-09561-5

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

 

Best Researcher Award

Yung-Chien Hsu — Chiayi 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