Riham Eiada

519 total citations
7 papers, 355 citations indexed

About

Riham Eiada is a scholar working on Pathology and Forensic Medicine, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Riham Eiada has authored 7 papers receiving a total of 355 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Pathology and Forensic Medicine, 4 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Riham Eiada's work include Breast Lesions and Carcinomas (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and MRI in cancer diagnosis (3 papers). Riham Eiada is often cited by papers focused on Breast Lesions and Carcinomas (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and MRI in cancer diagnosis (3 papers). Riham Eiada collaborates with scholars based in Canada, Saudi Arabia and Israel. Riham Eiada's co-authors include Supriya Kulkarni, Pavel Crystal, Anabel M. Scaranelo, Derek Muradali, Lindsay M. Jacks, Juexiao Zhou, Zhongxiao Li, Haoyang Li, Lihua Li and Xigang Xiao and has published in prestigious journals such as Scientific Reports, Radiology and IEEE Transactions on Medical Imaging.

In The Last Decade

Riham Eiada

7 papers receiving 352 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Riham Eiada Canada	6	243	141	104	84	45	7	355
Lonie R. Salkowski United States	13	245 1.0×	157 1.1×	93 0.9×	155 1.8×	25 0.6×	24	468
Silvia Penco Italy	14	326 1.3×	119 0.8×	147 1.4×	173 2.1×	29 0.6×	35	564
Francesca Abbate Italy	12	366 1.5×	139 1.0×	146 1.4×	105 1.3×	43 1.0×	31	549
Heather Greenwood United States	14	310 1.3×	210 1.5×	148 1.4×	63 0.8×	28 0.6×	36	486
L K Joynt United States	9	124 0.5×	148 1.0×	120 1.2×	83 1.0×	42 0.9×	10	360
Toshiyuki Ishiba Japan	9	163 0.7×	38 0.3×	75 0.7×	123 1.5×	8 0.2×	35	331
David Spak United States	5	193 0.8×	70 0.5×	71 0.7×	153 1.8×	10 0.2×	10	335
Lorenza Meneghetti Italy	12	178 0.7×	71 0.5×	75 0.7×	127 1.5×	11 0.2×	26	303
Tommy E. Cupples United States	7	89 0.4×	158 1.1×	133 1.3×	143 1.7×	46 1.0×	10	311
Katja Siegmann-Luz Germany	10	164 0.7×	95 0.7×	78 0.8×	46 0.5×	6 0.1×	22	307

Countries citing papers authored by Riham Eiada

Since Specialization

Citations

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

Fields of papers citing papers by Riham Eiada

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Riham Eiada

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

All Works

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7 of 7 papers shown

1.

Ghebeh, Hazem, Adher Alsayed, Riham Eiada, et al.. (2021). Weekly Paclitaxel given concurrently with Durvalumab has a favorable safety profile in triple-negative metastatic breast cancer. Scientific Reports. 11(1). 19154–19154. 18 indexed citations

2.

Zhou, Longxi, Zhongxiao Li, Juexiao Zhou, et al.. (2020). A Rapid, Accurate and Machine-Agnostic Segmentation and Quantification Method for CT-Based COVID-19 Diagnosis. IEEE Transactions on Medical Imaging. 39(8). 2638–2652. 129 indexed citations

3.

Mousa, Noha A., Riham Eiada, Pavel Crystal, Dan Nayot, & Robert F. Casper. (2012). The effect of acute aromatase inhibition on breast parenchymal enhancement in magnetic resonance imaging. Menopause The Journal of The North American Menopause Society. 19(4). 420–425. 23 indexed citations

4.

Scaranelo, Anabel M., Riham Eiada, Karina Bukhanov, & Pavel Crystal. (2012). Evaluation of breast amorphous calcifications by a computer-aided detection system in full-field digital mammography. British Journal of Radiology. 85(1013). 517–522. 9 indexed citations

5.

Eiada, Riham, et al.. (2012). Papillary Lesions of the Breast: MRI, Ultrasound, and Mammographic Appearances. American Journal of Roentgenology. 198(2). 264–271. 91 indexed citations

6.

Scaranelo, Anabel M., Riham Eiada, Lindsay M. Jacks, Supriya Kulkarni, & Pavel Crystal. (2011). Accuracy of Unenhanced MR Imaging in the Detection of Axillary Lymph Node Metastasis: Study of Reproducibility and Reliability. Radiology. 262(2). 425–434. 82 indexed citations

7.

Scaranelo, Anabel M., et al.. (2010). Imaging Approaches and Findings in the Reconstructed Breast: A Pictorial Essay. Canadian Association of Radiologists Journal. 62(1). 60–72. 3 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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