Fried-Michael Dahlweid
- Radiology, Nuclear Medicine and Imaging top 10%
- Artificial Intelligence top 10%
- Health Informatics top 1%
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Co-authors
- Mauricio ReyesRoland WiestRaphael MeierRonald M. SummersSérgio PereiraCarlos A. SilvaHendrik von Tengg‐KobligkAlexander Leichtle
- Topics
- Biomedical Text Mining and Ontologies (5 papers)Artificial Intelligence in Healthcare and Education (5 papers)Machine Learning in Healthcare (4 papers)
- Journals
- Journal of Medical Internet ResearchJournal of Biomedical InformaticsBiomedical Signal Processing and Control
- Partner nations
- SwitzerlandGermanyChina
In The Last Decade
Fried-Michael Dahlweid
11 papers receiving 390 citations
Peers
Comparison fields: 5 of 97
- Radiology, Nuclear Medicine and Imaging 169
- Artificial Intelligence 133
- Health Informatics 124
- Biomedical Engineering 60
- Computer Vision and Pattern Recognition 42
Countries citing papers authored by Fried-Michael Dahlweid
This map shows the geographic impact of Fried-Michael Dahlweid'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 Fried-Michael Dahlweid with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fried-Michael Dahlweid more than expected).
Fields of papers citing papers by Fried-Michael Dahlweid
This network shows the impact of papers produced by Fried-Michael Dahlweid. 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 Fried-Michael Dahlweid. The network helps show where Fried-Michael Dahlweid may publish in the future.
Co-authorship network of co-authors of Fried-Michael Dahlweid
This figure shows the co-authorship network connecting the top 25 collaborators of Fried-Michael Dahlweid. A scholar is included among the top collaborators of Fried-Michael Dahlweid 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 Fried-Michael Dahlweid. Fried-Michael Dahlweid is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 7 | |
| 7 | 2 | |
| 8 | 21 | |
| 9 | 4 | |
| 10 | 1 | |
| 11 | 14 | |
| 12 | 36 | |
| 13 | 283 | |
| 14 | 23 | |
| 15 | 1 | |
| 16 | 0 | |
| 17 | 8 |
About Fried-Michael Dahlweid
Fried-Michael Dahlweid is a scholar working on Health Informatics, Health Information Management and Developmental Neuroscience, having authored 17 papers that have together received 401 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (5 papers), Artificial Intelligence in Healthcare and Education (5 papers) and Machine Learning in Healthcare (4 papers). The work is most often cited by research in Health Informatics (124 citations), Radiology, Nuclear Medicine and Imaging (169 citations) and Drug Discovery (1 citation). Fried-Michael Dahlweid has collaborated with scholars based in Switzerland, Germany and China. Frequent co-authors include Mauricio Reyes, Roland Wiest, Raphael Meier, Ronald M. Summers, Sérgio Pereira, Carlos A. Silva, Hendrik von Tengg‐Kobligk, Alexander Leichtle, Matthew R. Scott and Xiaojun Hu. Their work appears in journals such as Journal of Medical Internet Research, Journal of Biomedical Informatics and Biomedical Signal Processing and Control.
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.