Daniel Heim
Impact in
- Biophysics top 5%
- Cell Image Analysis Techniques
- Artificial Intelligence top 5%
- AI in cancer detection
- Explainable Artificial Intelligence (XAI)
Papers in
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- Cancer Genomics and Diagnostics 8
-
- Cell Image Analysis Techniques 2
- Co-authors
- Frederick Klauschen (15 shared papers)Stephan Wienert (6 shared papers)Albrecht Stenzinger (7 shared papers)Peter Hufnagl (6 shared papers)Carsten Denkert (4 shared papers)Manfred Dietel (3 shared papers)Michael Beil (2 shared papers)Kai Saeger (1 shared paper)
- Journals
- International Journal of Cancer (3 papers)Nature Communications (2 papers)The Journal of Pathology (1 paper)Oncotarget (1 paper)Genes Chromosomes and Cancer (1 paper)
- Partner nations
- GermanyUnited KingdomSouth Korea
In The Last Decade
Daniel Heim
19 papers receiving 818 citations
Peers
Comparison fields: 5 of 74
- Biophysics 81
- Artificial Intelligence 308
- Cancer Research 111
- Health Informatics 18
- Immunology 79
Countries citing papers authored by Daniel Heim
This map shows the geographic impact of Daniel Heim'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 Daniel Heim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Heim more than expected).
Fields of papers citing papers by Daniel Heim
This network shows the impact of papers produced by Daniel Heim. 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 Daniel Heim. The network helps show where Daniel Heim may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Heim, 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 | 2012 | 197 | |
| 2 | 2021 | 121 | |
| 3 | 2019 | 101 | |
| 4 | 2017 | 82 | |
| 5 | 2022 | 64 | |
| 6 | 2015 | 53 | |
| 7 | 2013 | 37 | |
| 8 | 2014 | 37 | |
| 9 | 2016 | 35 | |
| 10 | 2021 | 27 | |
| 11 | 2022 | 25 | |
| 12 | 2016 | 13 | |
| 13 | 2015 | 10 | |
| 14 | 2018 | 8 | |
| 15 | 2018 | 8 | |
| 16 | 2019 | 8 | |
| 17 | 2018 | 3 | |
| 18 | 2019 | 3 | |
| 19 | 2020 | 3 |
About Daniel Heim
Daniel Heim is a scholar working on Cancer Research, Biophysics, Artificial Intelligence, Oncology and Molecular Biology, having authored 19 papers that have together received 835 indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (8 papers), AI in cancer detection (3 papers), Cell Image Analysis Techniques (2 papers), Lung Cancer Treatments and Mutations (1 paper), Epigenetics and DNA Methylation (1 paper), Bioinformatics and Genomic Networks (1 paper), Ocular Oncology and Treatments (1 paper) and Head and Neck Surgical Oncology (1 paper). The work is most often cited by research in Biophysics (81 citations), Artificial Intelligence (308 citations), Cancer Research (111 citations), Health Informatics (18 citations) and Immunology (79 citations). Daniel Heim has collaborated with scholars based in Germany, United Kingdom and South Korea. Frequent co-authors include Frederick Klauschen, Stephan Wienert, Albrecht Stenzinger, Peter Hufnagl, Carsten Denkert, Manfred Dietel, Michael Beil, Kai Saeger, Michael Ludwig Bockmayr and Klaus- Robert Müller. Their work appears in journals such as International Journal of Cancer, Nature Communications, The Journal of Pathology, Oncotarget and Genes Chromosomes and Cancer.
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.