Ümit Topaloĝlu
Impact in
- Health Informatics top 5%
- Toxicology top 2%
- Pharmacovigilance and Adverse Drug Reactions
Papers in
-
- Biomedical Text Mining and Ontologies 11
-
- Cryptography and Data Security 4
- Semantic Web and Ontologies 4
- Co-authors
- Matvey B. Palchuk (2 shared papers)Jiang Bian (9 shared papers)Ender Dulundu (14 shared papers)Göksel Şener (9 shared papers)Feri̇ha Ercan (9 shared papers)Erkan Özkan (12 shared papers)Özer Şehırlı (3 shared papers)Boris Pasche (8 shared papers)
- Journals
- Journal of Clinical Oncology (7 papers)JCO Clinical Cancer Informatics (7 papers)Surgery Today (4 papers)Cancers (3 papers)Learning Health Systems (2 papers)
- Partner nations
- United StatesTürkiyeChina
In The Last Decade
Ümit Topaloĝlu
96 papers receiving 1.9k citations
Ümit Topaloĝlu's Hit Papers
Peers
Comparison fields: 5 of 141
- Health Informatics 34
- Toxicology 80
- Health Information Management 84
- Oncology 286
- Cancer Research 153
Countries citing papers authored by Ümit Topaloĝlu
This map shows the geographic impact of Ümit Topaloĝlu'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 Ümit Topaloĝlu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ümit Topaloĝlu more than expected).
Fields of papers citing papers by Ümit Topaloĝlu
This network shows the impact of papers produced by Ümit Topaloĝlu. 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 Ümit Topaloĝlu. The network helps show where Ümit Topaloĝlu may publish in the future.
Co-authors
The 25 scholars most cited alongside Ümit Topaloĝlu, 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 103 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Using a Federated Network of Real-World Data to Optimize Clinical Trials Operations Hit paper breakdown → | 2018 | 219 |
| 2 | 2012 | 192 | |
| 3 | 2019 | 114 | |
| 4 | 2007 | 84 | |
| 5 | 2007 | 77 | |
| 6 | 2017 | 76 | |
| 7 | 2021 | 74 | |
| 8 | 2022 | 69 | |
| 9 | 2007 | 54 | |
| 10 | 2021 | 53 | |
| 11 | 2014 | 51 | |
| 12 | 2020 | 47 | |
| 13 | 2018 | 47 | |
| 14 | 2008 | 46 | |
| 15 | 2011 | 42 | |
| 16 | 2022 | 33 | |
| 17 | 2020 | 32 | |
| 18 | 2019 | 31 | |
| 19 | 2021 | 31 | |
| 20 | 2011 | 31 |
About Ümit Topaloĝlu
Ümit Topaloĝlu is a scholar working on Molecular Biology, Artificial Intelligence, Surgery, Oncology and Pulmonary and Respiratory Medicine, having authored 103 papers that have together received 2.0k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (11 papers), Electronic Health Records Systems (7 papers), Cancer Genomics and Diagnostics (7 papers), Cancer Immunotherapy and Biomarkers (6 papers), Lung Cancer Treatments and Mutations (5 papers), Cryptography and Data Security (4 papers), Ethics in Clinical Research (4 papers) and Semantic Web and Ontologies (4 papers). The work is most often cited by research in Health Informatics (34 citations), Toxicology (80 citations), Health Information Management (84 citations), Oncology (286 citations) and Cancer Research (153 citations). Ümit Topaloĝlu has collaborated with scholars based in United States, Türkiye and China. Frequent co-authors include Matvey B. Palchuk, Jiang Bian, Ender Dulundu, Göksel Şener, Feri̇ha Ercan, Erkan Özkan, Özer Şehırlı, Boris Pasche, Nursal Gedik and Suraj Rajendran. Their work appears in journals such as Journal of Clinical Oncology, JCO Clinical Cancer Informatics, Surgery Today, Cancers and Learning Health Systems.
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.