Robert Dürichen

1.0k total citations
23 papers, 732 citations indexed

About

Robert Dürichen is a scholar working on Radiation, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering. According to data from OpenAlex, Robert Dürichen has authored 23 papers receiving a total of 732 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Radiation, 8 papers in Radiology, Nuclear Medicine and Imaging and 8 papers in Biomedical Engineering. Recurrent topics in Robert Dürichen's work include Advanced Radiotherapy Techniques (8 papers), Non-Invasive Vital Sign Monitoring (7 papers) and Lung Cancer Diagnosis and Treatment (5 papers). Robert Dürichen is often cited by papers focused on Advanced Radiotherapy Techniques (8 papers), Non-Invasive Vital Sign Monitoring (7 papers) and Lung Cancer Diagnosis and Treatment (5 papers). Robert Dürichen collaborates with scholars based in Germany, United Kingdom and United States. Robert Dürichen's co-authors include Philip Schmidt, Attila Reiss, Achim Schweikard, Kristof Van Laerhoven, Floris Ernst, Michael Hanselmann, Rainer Stiefelhagen, Marco A. F. Pimentel, David A. Clifton and Lei Clifton and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Biomedical Engineering and Sensors.

In The Last Decade

Robert Dürichen

22 papers receiving 717 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Robert Dürichen Germany 12 183 178 175 144 136 23 732
Giovanni Luca Masala Italy 16 151 0.8× 305 1.7× 166 0.9× 189 1.3× 65 0.5× 60 867
Esko Alasaarela Finland 19 283 1.5× 127 0.7× 174 1.0× 73 0.5× 90 0.7× 68 1.0k
Mohamed Hédi Bedoui Tunisia 15 164 0.9× 182 1.0× 233 1.3× 266 1.8× 56 0.4× 124 927
Raffaella Lanzarotti Italy 14 153 0.8× 35 0.2× 302 1.7× 60 0.4× 54 0.4× 42 602
Giuliano Grossi Italy 11 147 0.8× 74 0.4× 122 0.7× 36 0.3× 34 0.3× 49 461
Melissa Berthelot United Kingdom 6 212 1.2× 511 2.9× 203 1.2× 346 2.4× 21 0.2× 11 1.3k
Kai Lawonn Germany 19 80 0.4× 135 0.8× 582 3.3× 155 1.1× 19 0.1× 106 1.0k
Xi Wu China 16 65 0.4× 388 2.2× 268 1.5× 244 1.7× 14 0.1× 81 974
Michael R. Anderson United States 16 78 0.4× 259 1.5× 190 1.1× 60 0.4× 48 0.4× 46 1.2k
Inga Strümke Norway 9 85 0.5× 271 1.5× 102 0.6× 168 1.2× 12 0.1× 35 892

Countries citing papers authored by Robert Dürichen

Since Specialization
Citations

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

Fields of papers citing papers by Robert Dürichen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Robert Dürichen

This figure shows the co-authorship network connecting the top 25 collaborators of Robert Dürichen. A scholar is included among the top collaborators of Robert Dürichen 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 Robert Dürichen. Robert Dürichen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Heldt, Frank S., Marcela P. Vizcaychipi, Fernando Andreotti, et al.. (2021). Early risk assessment for COVID-19 patients from emergency department data using machine learning. Scientific Reports. 11(1). 4200–4200. 63 indexed citations
3.
Schmidt, Philip, Robert Dürichen, Attila Reiss, Kristof Van Laerhoven, & Thomas Plötz. (2019). Multi-target affect detection in the wild: an exploratory study.. 211–219. 1 indexed citations
4.
Schweiker, Marcel, et al.. (2019). Personal thermal perception models using skin temperatures and HR/HRV features. 96–105. 12 indexed citations
5.
Schmidt, Philip, Attila Reiss, Robert Dürichen, & Kristof Van Laerhoven. (2019). Wearable-Based Affect Recognition—A Review. Sensors. 19(19). 4079–4079. 144 indexed citations
6.
Schmidt, Philip, Robert Dürichen, Attila Reiss, Kristof Van Laerhoven, & Thomas Plötz. (2019). Multi-target affect detection in the wild. 211–219. 41 indexed citations
7.
Dürichen, Robert, et al.. (2018). Prediction of electrocardiography features points using seismocardiography data. 19. 96–99. 6 indexed citations
8.
Dürichen, Robert, Marco A. F. Pimentel, Lei Clifton, Achim Schweikard, & David A. Clifton. (2014). Multi-task Gaussian process models for biomedical applications. 492–495. 13 indexed citations
9.
Dürichen, Robert, Tobias Wissel, & Achim Schweikard. (2014). Controlling motion prediction errors in radiotherapy with relevance vector machines. International Journal of Computer Assisted Radiology and Surgery. 10(4). 363–371. 3 indexed citations
10.
Dürichen, Robert, Marco A. F. Pimentel, Lei Clifton, Achim Schweikard, & David A. Clifton. (2014). Multitask Gaussian Processes for Multivariate Physiological Time-Series Analysis. IEEE Transactions on Biomedical Engineering. 62(1). 314–322. 108 indexed citations
11.
Dürichen, Robert, Tobias Wissel, Floris Ernst, Alexander Schlaefer, & Achim Schweikard. (2014). Multivariate respiratory motion prediction. Physics in Medicine and Biology. 59(20). 6043–6060. 14 indexed citations
12.
Wissel, Tobias, Benjamin Wagner, Robert Dürichen, et al.. (2014). Tissue thickness estimation for high precision head-tracking using a galvanometric laser scanner — A case study. PubMed. 2014. 3106–3109. 7 indexed citations
13.
Dürichen, Robert, et al.. (2013). Evaluation of the potential of multi-modal sensors for respiratory motion prediction and correlation. PubMed. 2013. 5678–5681. 22 indexed citations
14.
Dürichen, Robert, Tobias Wissel, Floris Ernst, & Achim Schweikard. (2013). Multi-modal respiratory motion prediction using sequential forward selection method.. 183–187. 2 indexed citations
15.
Dürichen, Robert, Tobias Wissel, & Achim Schweikard. (2013). Optimized order estimation for autoregressive models to predict respiratory motion. International Journal of Computer Assisted Radiology and Surgery. 8(6). 1037–1042. 1 indexed citations
16.
Dürichen, Robert, Tobias Wissel, Floris Ernst, & Achim Schweikard. (2013). Respiratory Motion Compensation with Relevance Vector Machines. Lecture notes in computer science. 16(Pt 2). 108–115. 20 indexed citations
17.
Ernst, Floris, Robert Dürichen, Alexander Schlaefer, & Achim Schweikard. (2013). Evaluating and comparing algorithms for respiratory motion prediction. Physics in Medicine and Biology. 58(11). 3911–3929. 72 indexed citations
18.
Dürichen, Robert, Tobias Wissel, & Achim Schweikard. (2012). Efficient SVR model update approaches for respiratory motion prediction.. 107–110. 1 indexed citations
19.
Blanck, Oliver, Robert Dürichen, Floris Ernst, et al.. (2012). OC-0022 EVALUATION OF A WAVELET-BASED LEAST MEAN SQUARE MOTION PREDICTION ALGORITHM FOR LUNG AND LIVER PATIENTS. Radiotherapy and Oncology. 103. S7–S8. 4 indexed citations
20.
Dürichen, Robert, Tobias Wissel, & Achim Schweikard. (2012). Prediction of respiratory motion using wavelet based support vector regression. 2012. 1–6. 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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