Daniel Chow
Impact in
- Health Informatics top 0.5%
-
- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- Medical Imaging Techniques and Applications
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 32
- MRI in cancer diagnosis 10
- Radiology practices and education 6
- Co-authors
- Christopher G. Filippi (17 shared papers)Peter Chang (29 shared papers)Min‐Ying Su (11 shared papers)Peter Chang (11 shared papers)Jack Grinband (9 shared papers)Brent D. Weinberg (12 shared papers)Michelle Bardis (12 shared papers)Daniela A. Bota (5 shared papers)
- Journals
- American Journal of Neuroradiology (10 papers)American Journal of Roentgenology (9 papers)Frontiers in Neurology (5 papers)Journal of Clinical Oncology (5 papers)Academic Radiology (4 papers)
- Partner nations
- United StatesSouth KoreaTaiwan
In The Last Decade
Daniel Chow
88 papers receiving 2.6k citations
Daniel Chow's Hit Papers
Peers
Comparison fields: 5 of 136
- Health Informatics 159
- Radiology, Nuclear Medicine and Imaging 1.4k
- Genetics 627
- Neurology 323
- Neurology 309
Countries citing papers authored by Daniel Chow
This map shows the geographic impact of Daniel Chow'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 Chow with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Chow more than expected).
Fields of papers citing papers by Daniel Chow
This network shows the impact of papers produced by Daniel Chow. 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 Chow. The network helps show where Daniel Chow may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Chow, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 95 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Deep-Learning Convolutional Neural Networks Accurately Classify Genetic Mutations in Gliomas Hit paper breakdown → | 2018 | 325 |
| 2 | 2018 | 193 | |
| 3 | 2019 | 169 | |
| 4 | 2016 | 124 | |
| 5 | 2020 | 102 | |
| 6 | 2019 | 87 | |
| 7 | 2019 | 85 | |
| 8 | 2017 | 84 | |
| 9 | 2019 | 77 | |
| 10 | 2011 | 68 | |
| 11 | 2019 | 67 | |
| 12 | 2020 | 63 | |
| 13 | 2016 | 56 | |
| 14 | 2020 | 55 | |
| 15 | 2013 | 54 | |
| 16 | 2017 | 52 | |
| 17 | 2015 | 51 | |
| 18 | 2020 | 50 | |
| 19 | 2021 | 50 | |
| 20 | 2020 | 47 |
About Daniel Chow
Daniel Chow is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Epidemiology, Neurology and Genetics, having authored 95 papers that have together received 2.6k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (32 papers), Acute Ischemic Stroke Management (15 papers), Glioma Diagnosis and Treatment (14 papers), MRI in cancer diagnosis (10 papers), Venous Thromboembolism Diagnosis and Management (9 papers), AI in cancer detection (7 papers), Radiology practices and education (6 papers) and Intracerebral and Subarachnoid Hemorrhage Research (6 papers). The work is most often cited by research in Health Informatics (159 citations), Radiology, Nuclear Medicine and Imaging (1.4k citations), Genetics (627 citations), Neurology (323 citations) and Neurology (309 citations). Daniel Chow has collaborated with scholars based in United States, South Korea and Taiwan. Frequent co-authors include Christopher G. Filippi, Peter Chang, Min‐Ying Su, Peter Chang, Jack Grinband, Brent D. Weinberg, Michelle Bardis, Daniela A. Bota, Yang Zhang and Angela Lignelli. Their work appears in journals such as American Journal of Neuroradiology, American Journal of Roentgenology, Frontiers in Neurology, Journal of Clinical Oncology and Academic Radiology.
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.