Karsten Sternickel

486 total citations
9 papers, 324 citations indexed

About

Karsten Sternickel is a scholar working on Artificial Intelligence, Economics and Econometrics and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Karsten Sternickel has authored 9 papers receiving a total of 324 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 3 papers in Economics and Econometrics and 2 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Karsten Sternickel's work include Neural Networks and Applications (4 papers), Complex Systems and Time Series Analysis (3 papers) and ECG Monitoring and Analysis (2 papers). Karsten Sternickel is often cited by papers focused on Neural Networks and Applications (4 papers), Complex Systems and Time Series Analysis (3 papers) and ECG Monitoring and Analysis (2 papers). Karsten Sternickel collaborates with scholars based in Germany and United States. Karsten Sternickel's co-authors include A. I. Braginski, Klaus Lehnertz, Peter David, Christoph Rieke, Ralph G. Andrzejak, Christian E. Elger, Mark J. Embrechts, Bolesław K. Szymański, Thanakorn Naenna and G. Panaitov and has published in prestigious journals such as Physical Review Letters, Computer Methods and Programs in Biomedicine and Superconductor Science and Technology.

In The Last Decade

Karsten Sternickel

9 papers receiving 293 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Karsten Sternickel Germany	7	113	95	84	62	52	9	324
Toshio Utsunomiya Japan	7	55 0.5×	56 0.6×	123 1.5×	60 1.0×	5 0.1×	28	474
Juha Montonen Finland	17	256 2.3×	454 4.8×	82 1.0×	54 0.9×	32 0.6×	43	708
Mario A. Quiroz‐Juárez Mexico	11	204 1.8×	80 0.8×	39 0.5×	33 0.5×	11 0.2×	38	420
Xiaoxia Li China	11	48 0.4×	14 0.1×	30 0.4×	77 1.2×	15 0.3×	33	417
Di Ge France	10	110 1.0×	73 0.8×	31 0.4×	36 0.6×	23 0.4×	23	306
Yasuaki Teramachi Japan	10	130 1.2×	29 0.3×	40 0.5×	188 3.0×	17 0.3×	25	325
J.L. Schiano United States	11	42 0.4×	5 0.1×	32 0.4×	55 0.9×	15 0.3×	32	425
K.T. Ng United States	9	27 0.2×	71 0.7×	27 0.3×	164 2.6×	9 0.2×	46	316
F. Hanser Austria	12	22 0.2×	347 3.7×	20 0.2×	104 1.7×	12 0.2×	49	532
Jerald G. Graeme	5	51 0.5×	19 0.2×	14 0.2×	214 3.5×	12 0.2×	6	390

Countries citing papers authored by Karsten Sternickel

Since Specialization

Citations

This map shows the geographic impact of Karsten Sternickel'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 Karsten Sternickel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Karsten Sternickel more than expected).

Fields of papers citing papers by Karsten Sternickel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Karsten Sternickel. 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 Karsten Sternickel. The network helps show where Karsten Sternickel may publish in the future.

Co-authorship network of co-authors of Karsten Sternickel

This figure shows the co-authorship network connecting the top 25 collaborators of Karsten Sternickel. A scholar is included among the top collaborators of Karsten Sternickel 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 Karsten Sternickel. Karsten Sternickel 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.

Bitzen, A., Karsten Sternickel, Thorsten Lewalter, et al.. (2007). Automatic P Wave Analysis Over 24 Hours in Patients with Paroxysmal or Persistent Atrial Fibrillation. Annals of Noninvasive Electrocardiology. 12(4). 306–315. 6 indexed citations

2.

Long, Han, et al.. (2006). Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms. The European Symposium on Artificial Neural Networks. 221–226. 6 indexed citations

3.

Long, Han, et al.. (2006). Random Forests Feature Selection with Kernel Partial Least Squares: Detecting Ischemia from MagnetoCardiograms. 5 indexed citations

4.

Sternickel, Karsten & A. I. Braginski. (2006). Biomagnetism using SQUIDs: status and perspectives. Superconductor Science and Technology. 19(3). S160–S171. 129 indexed citations

5.

Embrechts, Mark J., et al.. (2004). Use of machine learning for classification of magnetocardiograms. 2. 1400–1405. 18 indexed citations

6.

Sternickel, Karsten. (2002). Automatic pattern recognition in ECG time series. Computer Methods and Programs in Biomedicine. 68(2). 109–115. 82 indexed citations

7.

Rieke, Christoph, Karsten Sternickel, Ralph G. Andrzejak, et al.. (2002). Measuring Nonstationarity by Analyzing the Loss of Recurrence in Dynamical Systems. Physical Review Letters. 88(24). 244102–244102. 44 indexed citations

8.

Sternickel, Karsten, et al.. (2001). Nonlinear noise reduction using reference data. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 63(3). 36209–36209. 15 indexed citations

9.

Bick, M., et al.. (2001). SQUID gradiometry for magnetocardiography using different noise cancellation techniques. IEEE Transactions on Applied Superconductivity. 11(1). 673–676. 19 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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