Éva Ambrózay

409 total citations
25 papers, 239 citations indexed

About

Éva Ambrózay is a scholar working on Cancer Research, Pathology and Forensic Medicine and Oncology. According to data from OpenAlex, Éva Ambrózay has authored 25 papers receiving a total of 239 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cancer Research, 10 papers in Pathology and Forensic Medicine and 8 papers in Oncology. Recurrent topics in Éva Ambrózay's work include Breast Cancer Treatment Studies (12 papers), Breast Lesions and Carcinomas (10 papers) and Radiomics and Machine Learning in Medical Imaging (5 papers). Éva Ambrózay is often cited by papers focused on Breast Cancer Treatment Studies (12 papers), Breast Lesions and Carcinomas (10 papers) and Radiomics and Machine Learning in Medical Imaging (5 papers). Éva Ambrózay collaborates with scholars based in Hungary, United Kingdom and Qatar. Éva Ambrózay's co-authors include Gábor Cserni, Ben Glocker, Gábor Forrai, A.Y. Ng, Róbert Maráz, Gábor Boross, Cary Oberije, Endre Szabó, Elizabeth A. Morris and Nisha Sharma and has published in prestigious journals such as Nature Medicine, Nature Communications and Annals of Surgical Oncology.

In The Last Decade

Éva Ambrózay

24 papers receiving 234 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Éva Ambrózay Hungary 8 108 106 75 71 60 25 239
Lorenza Meneghetti Italy 12 178 1.6× 127 1.2× 45 0.6× 75 1.1× 71 1.2× 26 303
Megha Kapoor United States 7 88 0.8× 60 0.6× 27 0.4× 86 1.2× 67 1.1× 16 226
Katja Siegmann-Luz Germany 10 164 1.5× 46 0.4× 16 0.2× 78 1.1× 95 1.6× 22 307
Valeria Dominelli Italy 10 290 2.7× 85 0.8× 22 0.3× 95 1.3× 103 1.7× 22 369
Jeffrey Hawley United States 7 88 0.8× 61 0.6× 11 0.1× 36 0.5× 51 0.8× 18 180
Roman C. Maron Germany 8 70 0.6× 131 1.2× 58 0.8× 17 0.2× 7 0.1× 8 304
Yiming Gao United States 5 119 1.1× 79 0.7× 15 0.2× 32 0.5× 25 0.4× 6 190
Carolina Rossi Saccarelli United States 8 244 2.3× 107 1.0× 25 0.3× 57 0.8× 37 0.6× 14 305
Mathijn de Jong Netherlands 5 99 0.9× 86 0.8× 32 0.4× 40 0.6× 52 0.9× 7 229
Sophie Chheang United States 5 87 0.8× 45 0.4× 78 1.0× 34 0.5× 10 0.2× 7 264

Countries citing papers authored by Éva Ambrózay

Since Specialization
Citations

This map shows the geographic impact of Éva Ambrózay'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 Éva Ambrózay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Éva Ambrózay more than expected).

Fields of papers citing papers by Éva Ambrózay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Éva Ambrózay. 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 Éva Ambrózay. The network helps show where Éva Ambrózay may publish in the future.

Co-authorship network of co-authors of Éva Ambrózay

This figure shows the co-authorship network connecting the top 25 collaborators of Éva Ambrózay. A scholar is included among the top collaborators of Éva Ambrózay 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 Éva Ambrózay. Éva Ambrózay is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Cserni, Gábor, et al.. (2024). Histological Patterns and Mammographic Presentation of Invasive Lobular Carcinoma Show No Obvious Associations. Cancers. 16(9). 1640–1640. 5 indexed citations
2.
Ng, Annie, Ben Glocker, Cary Oberije, et al.. (2023). Artificial Intelligence as Supporting Reader in Breast Screening: A Novel Workflow to Preserve Quality and Reduce Workload. Journal of Breast Imaging. 5(3). 267–276. 17 indexed citations
3.
Ng, A.Y., Cary Oberije, Éva Ambrózay, et al.. (2023). Prospective implementation of AI-assisted screen reading to improve early detection of breast cancer. Nature Medicine. 29(12). 3044–3049. 68 indexed citations
4.
Sharma, Nisha, A.Y. Ng, Jonathan J. James, et al.. (2023). Multi-vendor evaluation of artificial intelligence as an independent reader for double reading in breast cancer screening on 275,900 mammograms. BMC Cancer. 23(1). 460–460. 37 indexed citations
5.
Sharma, Nisha, et al.. (2023). Automatic correction of performance drift under acquisition shift in medical image classification. Nature Communications. 14(1). 6608–6608. 12 indexed citations
6.
Forrai, Gábor, Eszter Kovács, Éva Ambrózay, et al.. (2022). Use of Diagnostic Imaging Modalities in Modern Screening, Diagnostics and Management of Breast Tumours 1st Central-Eastern European Professional Consensus Statement on Breast Cancer. Pathology & Oncology Research. 28. 1610382–1610382. 10 indexed citations
7.
8.
Maráz, Róbert, et al.. (2019). Negative pressure wound therapy of Corynebacterium jeikeium associated granulomatous mastitis. The Breast Journal. 26(3). 508–510. 3 indexed citations
9.
Cserni, Gábor, et al.. (2019). Spontaneous pathological complete regression of high-grade triple-negative breast cancer with axillary metastasis. Polish Journal of Pathology. 70(2). 139–143. 5 indexed citations
10.
Maráz, Róbert, Tamás Zombori, Éva Ambrózay, & Gábor Cserni. (2017). The role of preoperative axillary ultrasound and fine-needle aspiration cytology in identifying patients with extensive axillary lymph node involvement. European Journal of Surgical Oncology. 43(11). 2021–2028. 4 indexed citations
11.
Ambrózay, Éva, et al.. (2017). Mit tehet a háziorvos a mammográfiás szűréseken való részvétel javításáért? A prevenciós nővér szerepe. Orvosi Hetilap. 158(8). 311–315. 1 indexed citations
12.
Forrai, Gábor, Éva Ambrózay, Katalin Borbély, et al.. (2016). [Use of imaging methods in the current screening, diagnostics and treatment of breast cancer - Professional guidelines. 3rd Breast Cancer Consensus Meeting].. PubMed. 60(3). 181–93. 1 indexed citations
13.
Maráz, Róbert, et al.. (2014). The role of sentinel node biopsy in male breast cancer. Breast Cancer. 23(1). 85–91. 14 indexed citations
14.
Meretoja, Tuomo J, Päivi Heikkilä, Aaron S. Mansfield, et al.. (2014). A Predictive Tool to Estimate the Risk of Axillary Metastases in Breast Cancer Patients with Negative Axillary Ultrasound. Annals of Surgical Oncology. 21(7). 2229–2236. 22 indexed citations
15.
Maráz, Róbert, et al.. (2013). Internal Mammary Sentinel Node Biopsy in Breast Cancer. Is it Indicated?. Pathology & Oncology Research. 20(1). 169–177. 12 indexed citations
16.
Maráz, Róbert, Gábor Boross, Éva Ambrózay, Mihály Svébis, & Gábor Cserni. (2013). Selective Ductectomy for the Diagnosis and Treatment of Intraductal Papillary Lesions Presenting with Single Duct Discharge. Pathology & Oncology Research. 19(3). 589–595. 4 indexed citations
17.
Forrai, Gábor, Éva Szabó, Katalin Ormándi, et al.. (2010). A képalkotó vizsgálómódszerek alkalmazása az emlődaganatok korszerű diagnosztikájában és szűrésében. PubMed. 54(3). 211–216. 3 indexed citations
18.
Cserni, Gábor, Rita Bori, István Sejben, et al.. (2009). Analysis of predictive tools for further axillary involvement in patients with sentinel lymph node positive small (≤15 mm) invasive breast cancer. Orvosi Hetilap. 150(48). 2182–2188. 5 indexed citations
19.
Cserni, Gábor, Gábor Boross, Róbert Maráz, et al.. (2006). [Sentinel lymph node biopsy for in situ carcinoma of the breast. Experience at the Bács-Kiskun County Hospital and review of the literature].. PubMed. 59(3). 164–72. 2 indexed citations
20.
Maráz, Róbert, et al.. (2005). [Response rates following neoadjuvant chemotherapy and breast preserving treatment in patients with locally advanced breast cancer].. PubMed. 58(4). 225–32. 2 indexed citations

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.

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