Eva Falkensammer | Digital Health and Computational Biology | Innovative Research Award

Innovative Research Award

Eva Falkensammer
Paracelsus Medizinische Universität, Austria

Eva Falkensammer
Affiliation Paracelsus Medizinische Universität
Country Austria
Scopus ID 57073845600
Documents 11
Citations 732
h-index 6
Subject Area Digital Health and Computational Biology
Event Computational Biologists Awards
ORCID 0000-0002-8340-446X

Eva Falkensammer is a researcher affiliated with Paracelsus Medizinische Universität in Austria whose documented scholarly profile is situated within the intersection of digital health and computational biology. The available bibliometric information records 11 documents, 732 citations, and an h-index of 6 in Scopus. These indicators provide a quantitative context for assessing the visibility and scholarly influence of the research record, while the stated subject area provides a basis for considering its relevance to computational approaches in contemporary biomedical research. [1]

Abstract

Eva Falkensammer is a researcher at Paracelsus Medizinische Universität, Austria, whose academic profile is associated with digital health and computational biology. Available Scopus information identifies 11 documents, 732 citations, and an h-index of 6, indicating a research record with measurable scholarly visibility. Her profile reflects the growing integration of computational methods with biomedical and health-related research, where digital approaches can support data interpretation, evidence generation, and scientific collaboration. The Innovative Research Award recognizes research profiles demonstrating meaningful contributions to computationally informed scientific inquiry and innovation within contemporary biological and health sciences. [1]

Keywords

Eva Falkensammer; Innovative Research Award; Computational Biology; Digital Health; Biomedical Research; Bioinformatics; Health Data; Computational Methods; Research Impact; Paracelsus Medizinische Universität.

Introduction

Computational biology and digital health increasingly depend on the systematic analysis of complex biological and clinical information. Researchers working across these fields contribute to methodological development, data interpretation, and the translation of computational evidence into biomedical contexts. Within this landscape, Falkensammer’s documented subject classification places her scholarly profile within an interdisciplinary research environment connecting computational science and health research. [2]

Research Profile

Falkensammer’s profile is characterized by its association with Digital Health and Computational Biology at Paracelsus Medizinische Universität. The available bibliometric record comprises 11 documents and 732 citations, with an h-index of 6. These data indicate a sustained scholarly presence and provide measurable evidence for evaluating the reach of the documented publication record. [1]

Research Contributions

The stated subject area suggests contributions positioned at the interface of computational biology and digital health. Such interdisciplinary research can involve computational analysis of biomedical information, digital approaches to health research, and the application of quantitative methods to biological questions. Because detailed publication-level findings are not supplied in the available profile data, specific methodological or experimental contributions should be interpreted conservatively. [3]

Publications

The Scopus profile associated with author ID 57073845600 records 11 documents for Eva Falkensammer. The available information does not provide a complete publication bibliography, individual article titles, journal information, or article-level citation data. Consequently, the publication record is best described using the verified aggregate indicators supplied for this recognition profile rather than attributing specific findings or papers without supporting bibliographic evidence. [1]

Research Impact

The reported 732 citations and h-index of 6 provide quantitative indicators of scholarly impact within the indexed research literature. Citation measures are useful for describing research visibility, although they should not be interpreted independently of disciplinary context, publication age, collaboration patterns, and differences in citation practices between fields. In this profile, the indicators therefore serve as supporting evidence rather than as a standalone measure of research quality. [1] [4]

Award Suitability

The profile is suitable for consideration for an Innovative Research Award because its documented subject area directly corresponds with computational biology and digital health, two fields in which computational approaches play an important role in contemporary biomedical research. The combination of an identifiable institutional affiliation, 11 indexed documents, 732 citations, and an h-index of 6 provides an objective bibliometric basis for recognition, while final award decisions should also consider the originality, methodological significance, and practical or scientific contribution of the underlying research. [1] [3]

Conclusion

Eva Falkensammer’s documented academic profile reflects engagement with Digital Health and Computational Biology at Paracelsus Medizinische Universität. The available bibliometric record of 11 documents, 732 citations, and an h-index of 6 supports the assessment of an established scholarly presence. On the evidence supplied, the profile demonstrates relevance to an Innovative Research Award focused on computationally informed biological and health research, while detailed assessment of research originality should be based on the underlying publications and contributions. [1]

References

  1. Elsevier. (n.d.). Scopus author details: Eva Falkensammer, Author ID 57073845600. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57073845600
  2. Journal article. (2026.). Development of DEEP-URO, a Generic Research Tool for Enhancing Antimicrobial Stewardship in a Surgical Specialty.
    https://doi.org/10.3390/antibiotics15010074
  3. Journal article. (2024. ) Systematic Review and Meta-Analysis Provide no Guidance on Management of Asymptomatic Bacteriuria within the First Year after Kidney Transplantation.
    https://doi.org/10.3390/antibiotics13050442
  4. Computational Biologists Awards. (2026.). Official award website.
    https://computationalbiologists.com/
  5. ORCID. (n.d.). ORCID record: Eva Falkensammer, 0000-0002-8340-446X. ORCID.
    https://orcid.org/0000-0002-8340-446X