Làszló Tabár
- Oncology top 0.2%
- Global Cancer Incidence and Screening 105
- Colorectal Cancer Screening and Detection 56
- Cancer Risks and Factors 43
- Cancer Research top 0.5%
- Breast Cancer Treatment Studies 51
- Pathology and Forensic Medicine top 0.5%
- Breast Lesions and Carcinomas 28
- Artificial Intelligence top 0.5%
- AI in cancer detection 16
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- Digital Radiography and Breast Imaging 13
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- BRCA gene mutations in cancer 12
Làszló Tabár
146 papers receiving 9.4k citations
Hit Papers
Peers
Comparison fields: 5 of 166
- Oncology 6.8k
- Cancer Research 2.9k
- Pathology and Forensic Medicine 2.1k
- Artificial Intelligence 2.1k
- Radiology, Nuclear Medicine and Imaging 1.5k
Countries citing papers authored by Làszló Tabár
This map shows the geographic impact of Làszló Tabár'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 Làszló Tabár with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Làszló Tabár more than expected).
Fields of papers citing papers by Làszló Tabár
This network shows the impact of papers produced by Làszló Tabár. 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 Làszló Tabár. The network helps show where Làszló Tabár may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Làszló Tabár, 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 | 0 | |
| 2 | 2023 | 1 | |
| 3 | 2023 | 6 | |
| 4 | 2022 | 6 | |
| 5 | 2021 | 83 | |
| 6 | 2015 | 16 | |
| 7 | 2010 | 144 | |
| 8 | 2010 | 19 | |
| 9 | 2005 | 3 | |
| 10 | 2004 | 13 | |
| 11 | 2004 | 171 | |
| 12 | 2003 | 48 | |
| 13 | 2001 | 6 | |
| 14 | Some random-effects models for the analysis of matched-cluster randomised trials: application to the Swedish two-county trial of breast-cancer screening. | 2000 | 21 |
| 15 | 2000 | 82 | |
| 16 | One- versus two-view mammography screening. A prospective population-based study. | 1994 | 14 |
| 17 | 1989 | 10 | |
| 18 | 1987 | 51 | |
| 19 | [Mass screening mammography results in an increased need for surgical wards]. | 1986 | 4 |
| 20 | [Breast cancer screening by mammography in Sweden]. | 1983 | 2 |
About Làszló Tabár
Làszló Tabár is a scholar working on Oncology, Cancer Research and Pathology and Forensic Medicine, having authored 149 papers that have together received 9.9k indexed citations. Recurring topics across this work include Global Cancer Incidence and Screening (105 papers), Colorectal Cancer Screening and Detection (56 papers), Breast Cancer Treatment Studies (51 papers), Cancer Risks and Factors (43 papers), Breast Lesions and Carcinomas (28 papers), AI in cancer detection (16 papers), Digital Radiography and Breast Imaging (13 papers) and BRCA gene mutations in cancer (12 papers). The work is most often cited by research in Oncology (6.8k citations), Cancer Research (2.9k citations) and Pathology and Forensic Medicine (2.1k citations). Làszló Tabár has collaborated with scholars based in Sweden, United Kingdom and United States. Frequent co-authors include Stephen W. Duffy, Chien‐Jen Chen, Robert A. Smith, Lars Holmberg, Bedrich Viták, Peter B. Dean, G Fagerberg, Ahmed Z. Gad, Nicholas Day and Amy Ming‐Fang Yen. Their work appears in journals such as Journal of Medical Screening, Radiology, European Journal of Radiology, The Lancet and Cancer.
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.