Daniel G. Chong
Impact in
- Hematology top 5%
- Acute Myeloid Leukemia Research
- Chronic Myeloid Leukemia Treatments
- Genetics top 10%
- Myeloproliferative Neoplasms: Diagnosis and Treatment
Papers in
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- Advanced MRI Techniques and Applications 3
- MRI in cancer diagnosis 1
-
- Protein Degradation and Inhibitors 1
- Co-authors
- Roland Kreis (4 shared papers)Chris Boesch (3 shared papers)Warren Fiskus (4 shared papers)Kapil N. Bhalla (4 shared papers)Celalettin Üstün (4 shared papers)Rekha Rao (4 shared papers)Ramesh Balusu (3 shared papers)Daniel Nanz (1 shared paper)
- Journals
- Blood (4 papers)Magnetic Resonance in Medicine (1 paper)Drug and Alcohol Dependence (1 paper)NMR in Biomedicine (1 paper)Diabetes (1 paper)
- Partner nations
- SwitzerlandUnited StatesAustralia
In The Last Decade
Daniel G. Chong
12 papers receiving 678 citations
Peers
Comparison fields: 5 of 64
- Hematology 169
- Genetics 118
- Radiology, Nuclear Medicine and Imaging 186
- Molecular Biology 225
- Physiology 60
Countries citing papers authored by Daniel G. Chong
This map shows the geographic impact of Daniel G. Chong'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 G. Chong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel G. Chong more than expected).
Fields of papers citing papers by Daniel G. Chong
This network shows the impact of papers produced by Daniel G. Chong. 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 G. Chong. The network helps show where Daniel G. Chong may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel G. Chong, 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 | 2009 | 149 | |
| 2 | 2013 | 124 | |
| 3 | 2011 | 101 | |
| 4 | 2011 | 68 | |
| 5 | 2011 | 63 | |
| 6 | 2011 | 50 | |
| 7 | 2010 | 42 | |
| 8 | 2009 | 41 | |
| 9 | 2020 | 14 | |
| 10 | 2020 | 14 | |
| 11 | 2009 | 8 | |
| 12 | 2020 | 8 |
About Daniel G. Chong
Daniel G. Chong is a scholar working on Radiology, Nuclear Medicine and Imaging, Molecular Biology, Oncology, Hematology and Genetics, having authored 12 papers that have together received 682 indexed citations. Recurring topics across this work include Advanced MRI Techniques and Applications (3 papers), Cancer Mechanisms and Therapy (1 paper), Cardiovascular and exercise physiology (1 paper), Chronic Myeloid Leukemia Treatments (1 paper), Acute Myeloid Leukemia Research (1 paper), Galectins and Cancer Biology (1 paper), MRI in cancer diagnosis (1 paper) and Protein Degradation and Inhibitors (1 paper). The work is most often cited by research in Hematology (169 citations), Genetics (118 citations), Radiology, Nuclear Medicine and Imaging (186 citations), Molecular Biology (225 citations) and Physiology (60 citations). Daniel G. Chong has collaborated with scholars based in Switzerland, United States and Australia. Frequent co-authors include Roland Kreis, Chris Boesch, Warren Fiskus, Kapil N. Bhalla, Celalettin Üstün, Rekha Rao, Ramesh Balusu, Daniel Nanz, Harriet C. Thoeny and Johannes M. Froehlich. Their work appears in journals such as Blood, Magnetic Resonance in Medicine, Drug and Alcohol Dependence, NMR in Biomedicine and Diabetes.
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.