Iris To
Impact in
- Pathology and Forensic Medicine top 10%
- Lymphoma Diagnosis and Treatment
-
- CAR-T cell therapy research
Papers in
-
- Lymphoma Diagnosis and Treatment 13
- Genetics 5
- Chronic Lymphocytic Leukemia Research 5
- Co-authors
- Lihua Elizabeth Budde (8 shared papers)Sarit E. Assouline (6 shared papers)Huang Huang (3 shared papers)Nancy L. Bartlett (6 shared papers)Matthew J. Matasar (6 shared papers)Michael C. Wei (5 shared papers)Matthew Ku (4 shared papers)Pratyush Giri (4 shared papers)
- Journals
- Blood (5 papers)Blood Advances (2 papers)American Journal of Hematology (1 paper)Journal of Clinical Oncology (1 paper)Journal of the American Veterinary Medical Association (1 paper)
- Partner nations
- United StatesAustraliaCanada
In The Last Decade
Iris To
13 papers receiving 285 citations
Peers
Comparison fields: 5 of 21
- Pathology and Forensic Medicine 173
- Oncology 200
- Radiology, Nuclear Medicine and Imaging 86
- Genetics 31
- Immunology 34
Countries citing papers authored by Iris To
This map shows the geographic impact of Iris To'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 Iris To with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Iris To more than expected).
Fields of papers citing papers by Iris To
This network shows the impact of papers produced by Iris To. 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 Iris To. The network helps show where Iris To may publish in the future.
Co-authors
The 25 scholars most cited alongside Iris To, 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 | 71 | |
| 2 | 2023 | 71 | |
| 3 | 2024 | 45 | |
| 4 | 2020 | 31 | |
| 5 | 2022 | 29 | |
| 6 | 2023 | 15 | |
| 7 | 2022 | 15 | |
| 8 | 2025 | 10 | |
| 9 | 2023 | 6 | |
| 10 | 2021 | 1 | |
| 11 | 2024 | 1 | |
| 12 | 2024 | 1 | |
| 13 | 2024 | 1 | |
| 14 | 2026 | 0 | |
| 15 | 2024 | 0 | |
| 16 | 2026 | 0 | |
| 17 | 2026 | 0 |
About Iris To
Iris To is a scholar working on Pathology and Forensic Medicine, Genetics, Oncology, Dermatology and Radiology, Nuclear Medicine and Imaging, having authored 17 papers that have together received 297 indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (13 papers), CAR-T cell therapy research (8 papers), Monoclonal and Polyclonal Antibodies Research (5 papers), Chronic Lymphocytic Leukemia Research (5 papers), Cutaneous lymphoproliferative disorders research (4 papers), Biosimilars and Bioanalytical Methods (1 paper) and Veterinary Medicine and Surgery (1 paper). The work is most often cited by research in Pathology and Forensic Medicine (173 citations), Oncology (200 citations), Radiology, Nuclear Medicine and Imaging (86 citations), Genetics (31 citations) and Immunology (34 citations). Iris To has collaborated with scholars based in United States, Australia and Canada. Frequent co-authors include Lihua Elizabeth Budde, Sarit E. Assouline, Huang Huang, Nancy L. Bartlett, Matthew J. Matasar, Michael C. Wei, Matthew Ku, Pratyush Giri, Elicia M. Penuel and Laurie Helen Sehn. Their work appears in journals such as Blood, Blood Advances, American Journal of Hematology, Journal of Clinical Oncology and Journal of the American Veterinary Medical Association.
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.