Asmaa Ibrahim

537 total citations
22 papers, 270 citations indexed

About

Asmaa Ibrahim is a scholar working on Cancer Research, Artificial Intelligence and Oncology. According to data from OpenAlex, Asmaa Ibrahim has authored 22 papers receiving a total of 270 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cancer Research, 10 papers in Artificial Intelligence and 9 papers in Oncology. Recurrent topics in Asmaa Ibrahim's work include AI in cancer detection (10 papers), Breast Cancer Treatment Studies (6 papers) and Cancer Genomics and Diagnostics (6 papers). Asmaa Ibrahim is often cited by papers focused on AI in cancer detection (10 papers), Breast Cancer Treatment Studies (6 papers) and Cancer Genomics and Diagnostics (6 papers). Asmaa Ibrahim collaborates with scholars based in Egypt, United Kingdom and Qatar. Asmaa Ibrahim's co-authors include Emad A. Rakha, Ronnachai Jaroensri, Po-Hsuan Cameron Chen, Craig H. Mermel, Paul Gamble, Mohammed M. Abdelsamea, Michael S. Toss, Ayat Lashen, Ayaka Katayama and Fayyaz Minhas and has published in prestigious journals such as SHILAP Revista de lepidopterología, British Journal of Cancer and European Journal of Cancer.

In The Last Decade

Asmaa Ibrahim

22 papers receiving 265 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Asmaa Ibrahim Egypt	9	156	139	84	79	35	22	270
Andrew Lagree Canada	11	151 1.0×	192 1.4×	61 0.7×	52 0.7×	29 0.8×	15	295
Marko van Treeck Germany	11	209 1.3×	178 1.3×	60 0.7×	64 0.8×	45 1.3×	21	345
Ayesha Azam United Kingdom	4	144 0.9×	118 0.8×	42 0.5×	86 1.1×	31 0.9×	7	236
Ronnachai Jaroensri United States	5	200 1.3×	151 1.1×	43 0.5×	57 0.7×	44 1.3×	7	328
Charles Maussion France	4	190 1.2×	178 1.3×	57 0.7×	67 0.8×	30 0.9×	12	338
Christina Glasner Germany	3	129 0.8×	153 1.1×	53 0.6×	93 1.2×	31 0.9×	4	279
Emmanuel Agosto‐Arroyo United States	5	207 1.3×	148 1.1×	57 0.7×	81 1.0×	44 1.3×	11	327
Nicholas Meti Canada	9	96 0.6×	91 0.7×	43 0.5×	109 1.4×	42 1.2×	21	289
Kyunghyun Paeng South Korea	9	104 0.7×	136 1.0×	48 0.6×	92 1.2×	21 0.6×	29	237
Chiara Maria Lavinia Loeffler Germany	8	108 0.7×	112 0.8×	74 0.9×	73 0.9×	43 1.2×	12	240

Countries citing papers authored by Asmaa Ibrahim

Since Specialization

Citations

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

Fields of papers citing papers by Asmaa Ibrahim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Asmaa Ibrahim

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

All Works

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20 of 20 papers shown

Ibrahim, Asmaa, et al.. (2024). Deciphering the Role of ASPM in Breast Cancer: A Comprehensive Multicohort Study. Cancers. 16(22). 3814–3814. 1 indexed citations

Lashen, Ayat, Noorul Wahab, Michael S. Toss, et al.. (2024). Characterization of Breast Cancer Intra-Tumor Heterogeneity Using Artificial Intelligence. Cancers. 16(22). 3849–3849. 1 indexed citations

Abdelsameea, Eman, et al.. (2024). Exploring the prognostic significance of blood carnitine and acylcarnitines in hepatitis C virus-induced hepatocellular carcinoma. SHILAP Revista de lepidopterología. 14(1). 1 indexed citations

Masisi, Brendah K., Rokaya El Ansari, Lutfi Alfarsi, et al.. (2024). Tripartite Motif-Containing 2, a Glutamine Metabolism-Associated Protein, Predicts Poor Patient Outcome in Triple-Negative Breast Cancer Treated with Chemotherapy. Cancers. 16(11). 1949–1949. 1 indexed citations

Ibrahim, Asmaa, et al.. (2023). Novel 2 Gene Signatures Associated With Breast Cancer Proliferation: Insights From Predictive Differential Gene Expression Analysis. Modern Pathology. 37(2). 100403–100403. 4 indexed citations

Ibrahim, Asmaa, et al.. (2023). Software Defects Prediction At Method Level Using Ensemble Learning Techniques. 23(2). 28–49. 3 indexed citations

Cavanagh, Robert, Asmaa Ibrahim, Amanda K. Pearce, et al.. (2023). Chain-extension in hyperbranched polymers alters tissue distribution and cytotoxicity profiles in orthotopic models of triple negative breast cancers. Biomaterials Science. 11(19). 6545–6560. 1 indexed citations

Wahab, Noorul, Michael S. Toss, Asmaa Ibrahim, et al.. (2023). Evaluation of tumour infiltrating lymphocytes in luminal breast cancer using artificial intelligence. British Journal of Cancer. 129(11). 1747–1758. 22 indexed citations

Ibrahim, Asmaa, et al.. (2023). Combined proliferation and apoptosis index provides better risk stratification in breast cancer. Histopathology. 82(7). 1029–1047. 2 indexed citations

10.

Ibrahim, Asmaa, Islam M. Miligy, Michael S. Toss, Andrew R. Green, & Emad A. Rakha. (2023). High Inner Centromere Protein Expression Correlates with Aggressive Features and Predicts Poor Prognosis in Patients with Invasive Breast Cancer. Pathobiology. 90(6). 377–388. 1 indexed citations

11.

Ibrahim, Asmaa, Mostafa Jahanifar, Noorul Wahab, et al.. (2023). Artificial Intelligence-Based Mitosis Scoring in Breast Cancer: Clinical Application. Modern Pathology. 37(3). 100416–100416. 11 indexed citations

12.

Wahab, Noorul, Michael S. Toss, Asmaa Ibrahim, et al.. (2023). Deciphering the Morphology of Tumor-Stromal Features in Invasive Breast Cancer Using Artificial Intelligence. Modern Pathology. 36(10). 100254–100254. 5 indexed citations

13.

Wahab, Noorul, Michael S. Toss, Islam M. Miligy, et al.. (2023). AI-enabled routine H&E image based prognostic marker for early-stage luminal breast cancer. npj Precision Oncology. 7(1). 122–122. 8 indexed citations

14.

Quinn, Cecily, Michael S. Toss, Mansour Alsaleem, et al.. (2023). Quantitative expression of oestrogen receptor in breast cancer: Clinical and molecular significance. European Journal of Cancer. 197. 113473–113473. 6 indexed citations

15.

Lu, Wenqi, Ayat Lashen, Noorul Wahab, et al.. (2023). AI‐based intra‐tumor heterogeneity score of Ki67 expression as a prognostic marker for early‐stage ER+/HER2− breast cancer. The Journal of Pathology Clinical Research. 10(1). e346–e346. 4 indexed citations

16.

Quinn, Cecily, Michael S. Toss, Asmaa Ibrahim, et al.. (2023). Characterisation of luminal and triple-negative breast cancer with HER2 Low protein expression. European Journal of Cancer. 195. 113371–113371. 15 indexed citations

17.

Ibrahim, Asmaa, et al.. (2022). Improving mitotic cell counting accuracy and efficiency using phosphohistone‐H3 (PHH3) antibody counterstained with haematoxylin and eosin as part of breast cancer grading. Histopathology. 82(3). 393–406. 11 indexed citations

18.

Lashen, Ayat, Asmaa Ibrahim, Ayaka Katayama, et al.. (2021). Visual assessment of mitotic figures in breast cancer: a comparative study between light microscopy and whole slide images. Histopathology. 79(6). 913–925. 11 indexed citations

19.

Ibrahim, Asmaa, Ayat Lashen, Ayaka Katayama, et al.. (2021). Defining the area of mitoses counting in invasive breast cancer using whole slide image. Modern Pathology. 35(6). 739–748. 17 indexed citations

20.

Ibrahim, Asmaa, Paul Gamble, Ronnachai Jaroensri, et al.. (2019). Artificial intelligence in digital breast pathology: Techniques and applications. The Breast. 49. 267–273. 122 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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