Daniel Tse
Impact in
- Health Informatics top 0.2%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Medical Imaging Techniques and Applications
Papers in
-
- Lung Cancer Diagnosis and Treatment 4
- Neonatal Respiratory Health Research 1
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- COVID-19 diagnosis using AI 3
- Radiomics and Machine Learning in Medical Imaging 3
- Radiology practices and education 2
- Co-authors
- Joshua Reicher (4 shared papers)Greg S. Corrado (3 shared papers)Mozziyar Etemadi (2 shared papers)Lily Peng (2 shared papers)David P. Naidich (1 shared paper)Sujeeth Bharadwaj (2 shared papers)Wenxing Ye (1 shared paper)Diego Ardila (2 shared papers)
- Journals
- Radiology (2 papers)JAMA Network Open (1 paper)Nature Medicine (1 paper)British Journal of Radiology (1 paper)Hong Kong journal of psychiatry (1 paper)
- Partner nations
- United StatesHong Kong
In The Last Decade
Daniel Tse
7 papers receiving 1.4k citations
Daniel Tse's Hit Papers
Peers
Comparison fields: 5 of 126
- Health Informatics 268
- Radiology, Nuclear Medicine and Imaging 991
- Pulmonary and Respiratory Medicine 542
- Artificial Intelligence 476
- Health Information Management 59
Countries citing papers authored by Daniel Tse
This map shows the geographic impact of Daniel Tse'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 Tse with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Tse more than expected).
Fields of papers citing papers by Daniel Tse
This network shows the impact of papers produced by Daniel Tse. 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 Tse. The network helps show where Daniel Tse may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Tse, 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 | End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography Hit paper breakdown → | 2019 | 1221 |
| 2 | 2019 | 171 | |
| 3 | 2022 | 30 | |
| 4 | 2023 | 19 | |
| 5 | 2021 | 13 | |
| 6 | Perception of Doctors and Nurses on the Care and Bereavement Support for Relatives of Terminally Ill Patients in an Acute Setting | 2006 | 9 |
| 7 | Improving the specificity of lung cancer screening CT using deep learning | 2018 | 1 |
About Daniel Tse
Daniel Tse is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging, Pediatrics, Perinatology and Child Health, Radiological and Ultrasound Technology and Clinical Psychology, having authored 7 papers that have together received 1.5k indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (4 papers), COVID-19 diagnosis using AI (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Radiology practices and education (2 papers), Grief, Bereavement, and Mental Health (1 paper), Palliative Care and End-of-Life Issues (1 paper), Family and Patient Care in Intensive Care Units (1 paper) and Neonatal Respiratory Health Research (1 paper). The work is most often cited by research in Health Informatics (268 citations), Radiology, Nuclear Medicine and Imaging (991 citations), Pulmonary and Respiratory Medicine (542 citations), Artificial Intelligence (476 citations) and Health Information Management (59 citations). Daniel Tse has collaborated with scholars based in United States and Hong Kong. Frequent co-authors include Joshua Reicher, Greg S. Corrado, Mozziyar Etemadi, Lily Peng, David P. Naidich, Sujeeth Bharadwaj, Wenxing Ye, Diego Ardila, Safal Shetty and Atilla P. Kiraly. Their work appears in journals such as Radiology, JAMA Network Open, Nature Medicine, British Journal of Radiology and Hong Kong journal of psychiatry.
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.