Josef Schepers

748 total citations
9 papers, 394 citations indexed

About

Josef Schepers is a scholar working on Genetics, Health Information Management and Artificial Intelligence. According to data from OpenAlex, Josef Schepers has authored 9 papers receiving a total of 394 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Genetics, 2 papers in Health Information Management and 2 papers in Artificial Intelligence. Recurrent topics in Josef Schepers's work include Genomics and Rare Diseases (4 papers), Cryptography and Data Security (2 papers) and Electronic Health Records Systems (2 papers). Josef Schepers is often cited by papers focused on Genomics and Rare Diseases (4 papers), Cryptography and Data Security (2 papers) and Electronic Health Records Systems (2 papers). Josef Schepers collaborates with scholars based in Germany and Denmark. Josef Schepers's co-authors include Sylvia Thun, Moritz Lehne, Julian Saß, Andrea Essenwanger, Fabian Praßer, Phillipp Schoppmann, Julia L. Fleck, Jannik Schaaf, Martin Lablans and Kay Hamacher and has published in prestigious journals such as Journal of Translational Medicine, Orphanet Journal of Rare Diseases and npj Digital Medicine.

In The Last Decade

Josef Schepers

7 papers receiving 375 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Josef Schepers Germany	5	83	81	78	72	59	9	394
Julian Saß Germany	5	61 0.7×	67 0.8×	79 1.0×	82 1.1×	18 0.3×	15	324
Andrea Essenwanger Germany	4	59 0.7×	66 0.8×	78 1.0×	79 1.1×	15 0.3×	6	304
Holger Storf Germany	11	66 0.8×	31 0.4×	77 1.0×	42 0.6×	120 2.0×	64	439
Jonathan Guo United Kingdom	5	53 0.6×	99 1.2×	46 0.6×	32 0.4×	29 0.5×	8	524
Benjamin Fine Canada	14	87 1.0×	119 1.5×	50 0.6×	27 0.4×	55 0.9×	42	804
Frank J. Manion United States	15	174 2.1×	45 0.6×	49 0.6×	67 0.9×	53 0.9×	31	592
Evert-Ben van Veen Netherlands	12	81 1.0×	48 0.6×	22 0.3×	177 2.5×	27 0.5×	26	479
Christine M. Cutillo United States	7	91 1.1×	90 1.1×	30 0.4×	60 0.8×	202 3.4×	7	504
Jerry Sheehan United States	6	59 0.7×	27 0.3×	52 0.7×	70 1.0×	16 0.3×	8	415
Jan Christoph Germany	11	52 0.6×	25 0.3×	59 0.8×	47 0.7×	18 0.3×	48	441

Countries citing papers authored by Josef Schepers

Since Specialization

Citations

This map shows the geographic impact of Josef Schepers's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Josef Schepers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Josef Schepers more than expected).

Fields of papers citing papers by Josef Schepers

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Josef Schepers. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Josef Schepers. The network helps show where Josef Schepers may publish in the future.

Co-authorship network of co-authors of Josef Schepers

This figure shows the co-authorship network connecting the top 25 collaborators of Josef Schepers. A scholar is included among the top collaborators of Josef Schepers based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Josef Schepers. Josef Schepers is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

1.

Sedlmayr, Martin, Gabriele Müller, Helge Hebestreit, et al.. (2024). Secondary use of patient data within decentralized studies using the example of rare diseases in Germany: A data scientist's exploration of process and lessons learned. Digital Health. 10. 599908931–599908931. 1 indexed citations

2.

Zschüntzsch, Jana, et al.. (2024). Improving Clinical Documentation of Rare Neuromuscular Diseases: Development of a Standardised Information Model. Studies in health technology and informatics. 316. 1418–1419. 1 indexed citations

3.

Schepers, Josef, et al.. (2022). Record linkage based patient intersection cardinality for rare disease studies using Mainzelliste and secure multi-party computation. Journal of Translational Medicine. 20(1). 458–458. 5 indexed citations

4.

Schepers, Josef, Julia L. Fleck, & Jannik Schaaf. (2022). Die Medizininformatik-Initiative und Seltene Erkrankungen: Routinedaten der nächsten Generation für Diagnose, Therapiewahl und Forschung. Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz. 65(11). 1151–1158. 4 indexed citations

5.

Lehne, Moritz, Phillipp Schoppmann, Fabian Praßer, et al.. (2020). A Secure Multi-Party Computation Protocol for Time-To-Event Analyses. Studies in health technology and informatics. 270. 8–12. 4 indexed citations

6.

Lehne, Moritz, et al.. (2020). The use of machine learning in rare diseases: a scoping review. Orphanet Journal of Rare Diseases. 15(1). 145–145. 126 indexed citations

7.

Ganslandt, Thomas, Jannik Schaaf, Josef Schepers, et al.. (2019). Experiences from the National Demonstrator Study within the German Medical Informatics Initiative.. AMIA.

8.

Lehne, Moritz, Julian Saß, Andrea Essenwanger, Josef Schepers, & Sylvia Thun. (2019). Why digital medicine depends on interoperability. npj Digital Medicine. 2(1). 79–79. 252 indexed citations

9.

Schepers, Josef, et al.. (1980). Haus und Hof westfälischer Bauern. Aschendorff eBooks. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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