Torsten Blum
- Molecular Biology top 10%
- Machine Learning in Bioinformatics 6
- Oncology top 10%
- Cancer Immunotherapy and Biomarkers 9
- Pancreatic and Hepatic Oncology Research 7
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- Lung Cancer Diagnosis and Treatment 19
- Lung Cancer Treatments and Mutations 14
- Chronic Obstructive Pulmonary Disease (COPD) Research 8
- Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis 6
- Surgery top 10%
- Emergency Medicine top 10%
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- Radiomics and Machine Learning in Medical Imaging 7
Torsten Blum
55 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 114
- Molecular Biology 829
- Oncology 322
- Pulmonary and Respiratory Medicine 326
- Surgery 324
- Emergency Medicine 59
Countries citing papers authored by Torsten Blum
This map shows the geographic impact of Torsten Blum'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 Torsten Blum with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Torsten Blum more than expected).
Fields of papers citing papers by Torsten Blum
This network shows the impact of papers produced by Torsten Blum. 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 Torsten Blum. The network helps show where Torsten Blum may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Torsten Blum, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 8 | |
| 3 | 2024 | 1 | |
| 4 | 2023 | 2 | |
| 5 | 2023 | 1 | |
| 6 | 2023 | 1 | |
| 7 | 2023 | 16 | |
| 8 | 2021 | 39 | |
| 9 | 2020 | 26 | |
| 10 | 2020 | 7 | |
| 11 | 2020 | 1 | |
| 12 | 2019 | 1 | |
| 13 | 2018 | 2 | |
| 14 | 2013 | 86 | |
| 15 | 2009 | 59 | |
| 16 | 2008 | 33 | |
| 17 | Finding Relevant Biotransformation Routes in Weighted Metabolic Networks. | 2007 | 1 |
| 18 | 2007 | 28 | |
| 19 | Using N-terminal targeting sequences, amino acid composition, and sequence motifs for predicting protein subcellular localizations. | 2005 | 2 |
| 20 | 2001 | 32 |
About Torsten Blum
Torsten Blum is a scholar working on Pulmonary and Respiratory Medicine, Critical Care and Intensive Care Medicine and Oncology, having authored 62 papers that have together received 1.6k indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (19 papers), Lung Cancer Treatments and Mutations (14 papers), Cancer Immunotherapy and Biomarkers (9 papers), Chronic Obstructive Pulmonary Disease (COPD) Research (8 papers), Pancreatic and Hepatic Oncology Research (7 papers), Radiomics and Machine Learning in Medical Imaging (7 papers), Machine Learning in Bioinformatics (6 papers) and Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (6 papers). The work is most often cited by research in Molecular Biology (829 citations), Oncology (322 citations) and Pulmonary and Respiratory Medicine (326 citations). Torsten Blum has collaborated with scholars based in Germany, Italy and France. Frequent co-authors include Oliver Kohlbacher, Sebastian Briesemeister, Annette Höglund, Pierre Dönnes, Patrick Maisonneuve, Hans‐Werner Adolph, P. G. Lankisch, Albert B. Lowenfels, Scott T. Brady and Jens Kollmeier. Their work appears in journals such as Lung Cancer, ERJ Open Research, Bioinformatics, Pancreatology and European Respiratory Journal.
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.