Patricia Tai
- Oncology top 5%
- Cancer Research top 5%
- Pulmonary and Respiratory Medicine top 5%
- Surgery top 10%
- Pathology and Forensic Medicine top 5%
- Co-authors
- Edward YuGeorges VlastosVincent Vinh‐HungGábor CserniMelanie RoyceKurian JosephLarry StittWendy A. Woodward
- Topics
- Breast Cancer Treatment Studies (18 papers)Polyomavirus and related diseases (13 papers)Global Cancer Incidence and Screening (12 papers)
- Cited by
- Cancer ResearchOncologyRadiation
- Journals
- Journal of Clinical OncologySHILAP Revista de lepidopterologíaJNCI Journal of the National Cancer Institute
- Partner nations
- CanadaUnited StatesSwitzerland
In The Last Decade
Patricia Tai
74 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 86
- Oncology 664
- Cancer Research 466
- Pulmonary and Respiratory Medicine 426
- Surgery 340
- Pathology and Forensic Medicine 297
Countries citing papers authored by Patricia Tai
This map shows the geographic impact of Patricia Tai'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 Patricia Tai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Patricia Tai more than expected).
Fields of papers citing papers by Patricia Tai
This network shows the impact of papers produced by Patricia Tai. 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 Patricia Tai. The network helps show where Patricia Tai may publish in the future.
Co-authorship network of co-authors of Patricia Tai
This figure shows the co-authorship network connecting the top 25 collaborators of Patricia Tai. A scholar is included among the top collaborators of Patricia Tai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Patricia Tai. Patricia Tai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 10 | |
| 7 | 22 | |
| 8 | 6 | |
| 9 | 12 | |
| 10 | 13 | |
| 11 | 19 | |
| 12 | 44 | |
| 13 | 26 | |
| 14 | 36 | |
| 15 | 14 | |
| 16 | 142 | |
| 17 | 27 | |
| 18 | 31 | |
| 19 | Validation of the Lognormal Model for Prediction of Long-term Survival Rates from Short-term Follow up Data in Stages III and IV Breast Cancer | 2 |
| 20 | 1 |
About Patricia Tai
Patricia Tai is a scholar working on Oncology, Cancer Research and Radiation, having authored 80 papers that have together received 1.5k indexed citations. Recurring topics across this work include Breast Cancer Treatment Studies (18 papers), Polyomavirus and related diseases (13 papers) and Global Cancer Incidence and Screening (12 papers). The work is most often cited by research in Cancer Research (466 citations), Oncology (664 citations) and Radiation (166 citations). Patricia Tai has collaborated with scholars based in Canada, United States and Switzerland. Frequent co-authors include Edward Yu, Georges Vlastos, Vincent Vinh‐Hung, Gábor Cserni, Melanie Royce, Kurian Joseph, Larry Stitt, Wendy A. Woodward, Jon Tonita and Guy Storme. Their work appears in journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and JNCI Journal of the National Cancer Institute.
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.