Jackie Wu
Impact in
- Endocrine and Autonomic Systems top 10%
- Circadian rhythm and melatonin
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- Dietary Effects on Health
- Diet and metabolism studies
Papers in
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- Brain Metastases and Treatment 1
- Lung Cancer Diagnosis and Treatment 1
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- Circadian rhythm and melatonin 2
- Co-authors
- Krista A Varady (2 shared papers)Sofia Cienfuegos (2 shared papers)Shaina J. Alexandria (2 shared papers)Kelsey Gabel (2 shared papers)Lisa Tussing‐Humphreys (2 shared papers)Mark Ezpeleta (2 shared papers)Terry G. Unterman (2 shared papers)Vasiliki Pavlou (2 shared papers)
- Journals
- Journal of Clinical Oncology (1 paper)Journal of Personalized Medicine (1 paper)JAMA Network Open (1 paper)Oral Oncology (1 paper)International Journal of Radiation Oncology*Biology*Physics (1 paper)
- Partner nations
- United StatesAustraliaHong Kong
In The Last Decade
Jackie Wu
6 papers receiving 222 citations
Peers
Comparison fields: 5 of 36
- Endocrine and Autonomic Systems 62
- Physiology 118
- Otorhinolaryngology 15
- Health Informatics 4
- Radiology, Nuclear Medicine and Imaging 56
Countries citing papers authored by Jackie Wu
This map shows the geographic impact of Jackie Wu'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 Jackie Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jackie Wu more than expected).
Fields of papers citing papers by Jackie Wu
This network shows the impact of papers produced by Jackie Wu. 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 Jackie Wu. The network helps show where Jackie Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Jackie Wu, 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 | 2023 | 69 | |
| 2 | 2023 | 58 | |
| 3 | 2019 | 43 | |
| 4 | 2024 | 30 | |
| 5 | 2018 | 18 | |
| 6 | 2023 | 5 |
About Jackie Wu
Jackie Wu is a scholar working on Pulmonary and Respiratory Medicine, Endocrine and Autonomic Systems, Radiology, Nuclear Medicine and Imaging, Physiology and Surgery, having authored 6 papers that have together received 223 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (2 papers), Diet and metabolism studies (2 papers), Dietary Effects on Health (2 papers), MRI in cancer diagnosis (2 papers), Circadian rhythm and melatonin (2 papers), Brain Metastases and Treatment (1 paper), Advanced X-ray and CT Imaging (1 paper) and Lung Cancer Diagnosis and Treatment (1 paper). The work is most often cited by research in Endocrine and Autonomic Systems (62 citations), Physiology (118 citations), Otorhinolaryngology (15 citations), Health Informatics (4 citations) and Radiology, Nuclear Medicine and Imaging (56 citations). Jackie Wu has collaborated with scholars based in United States, Australia and Hong Kong. Frequent co-authors include Krista A Varady, Sofia Cienfuegos, Shaina J. Alexandria, Kelsey Gabel, Lisa Tussing‐Humphreys, Mark Ezpeleta, Terry G. Unterman, Vasiliki Pavlou, Shuhao Lin and Andrea Mulas. Their work appears in journals such as Journal of Clinical Oncology, Journal of Personalized Medicine, JAMA Network Open, Oral Oncology and International Journal of Radiation Oncology*Biology*Physics.
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.