Haitham Elmarakeby

3.0k total citations · 1 hit paper
17 papers, 753 citations indexed

About

Haitham Elmarakeby is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Cancer Research. According to data from OpenAlex, Haitham Elmarakeby has authored 17 papers receiving a total of 753 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 6 papers in Pulmonary and Respiratory Medicine and 6 papers in Cancer Research. Recurrent topics in Haitham Elmarakeby's work include Radiomics and Machine Learning in Medical Imaging (5 papers), Cancer Genomics and Diagnostics (5 papers) and Lung Cancer Treatments and Mutations (3 papers). Haitham Elmarakeby is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (5 papers), Cancer Genomics and Diagnostics (5 papers) and Lung Cancer Treatments and Mutations (3 papers). Haitham Elmarakeby collaborates with scholars based in United States, Egypt and Saudi Arabia. Haitham Elmarakeby's co-authors include Eliezer M. Van Allen, Deborah Schrag, Kenneth L. Kehl, Eric Kofman, Jake R. Conway, Shirley Mo, Lenwood S. Heath, Michael J. Hassett, Eva M. Lepisto and Bruce E. Johnson and has published in prestigious journals such as Nature, JAMA and Nature Communications.

In The Last Decade

Haitham Elmarakeby

17 papers receiving 744 citations

Hit Papers

Biologically informed dee... 2021 2026 2022 2024 2021 50 100 150 200
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Biologically informed deep neural network for prostate cancer discovery
    2021 239 citations Haitham Elmarakeby, Justin H. Hwang et al. Nature profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Haitham Elmarakeby United States 12 301 195 159 130 129 17 753
Jenny L. Smith United States 12 193 0.6× 384 2.0× 310 1.9× 95 0.7× 128 1.0× 44 882
Yaping Guo China 13 501 1.7× 61 0.3× 108 0.7× 76 0.6× 72 0.6× 26 756
Yulan Zeng China 14 191 0.6× 57 0.3× 114 0.7× 191 1.5× 136 1.1× 39 633
Zhen Zhou China 18 392 1.3× 145 0.7× 443 2.8× 130 1.0× 309 2.4× 52 1.1k
Marco Chierici Italy 16 289 1.0× 55 0.3× 69 0.4× 204 1.6× 92 0.7× 39 779
Tinghui Wu Taiwan 11 106 0.4× 148 0.8× 179 1.1× 234 1.8× 89 0.7× 28 589
Zhenwei Shi China 21 395 1.3× 386 2.0× 815 5.1× 213 1.6× 293 2.3× 66 1.5k
Lana X. Garmire United States 10 713 2.4× 163 0.8× 184 1.2× 101 0.8× 153 1.2× 22 1.1k
Lei Cao China 17 503 1.7× 77 0.4× 67 0.4× 100 0.8× 83 0.6× 62 932
Liang‐Ru Ke China 18 239 0.8× 61 0.3× 140 0.9× 291 2.2× 98 0.8× 37 767

Countries citing papers authored by Haitham Elmarakeby

Since Specialization
Citations

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

Fields of papers citing papers by Haitham Elmarakeby

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haitham Elmarakeby

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

All Works

17 of 17 papers shown
1.
Elmarakeby, Haitham, et al.. (2023). Empirical evaluation of language modeling to ascertain cancer outcomes from clinical text reports. BMC Bioinformatics. 24(1). 328–328. 8 indexed citations
2.
Kehl, Kenneth L., Stefan Groha, Eva M. Lepisto, et al.. (2021). Clinical Inflection Point Detection on the Basis of EHR Data to Identify Clinical Trial–Ready Patients With Cancer. JCO Clinical Cancer Informatics. 5(5). 622–630. 12 indexed citations
3.
Eid, Fatma-Elzahraa, Haitham Elmarakeby, Yujia A. Chan, et al.. (2021). Systematic auditing is essential to debiasing machine learning in biology. Communications Biology. 4(1). 183–183. 22 indexed citations
4.
Kehl, Kenneth L., Wenxin Xu, Alexander Gusev, et al.. (2021). Artificial intelligence-aided clinical annotation of a large multi-cancer genomic dataset. Nature Communications. 12(1). 7304–7304. 33 indexed citations
5.
Elmarakeby, Haitham, Justin H. Hwang, Rand Arafeh, et al.. (2021). Biologically informed deep neural network for prostate cancer discovery. Nature. 598(7880). 348–352. 239 indexed citations breakdown →
6.
Reardon, Brendan, Nathanael D. Moore, Nicholas Moore, et al.. (2021). Integrating molecular profiles into clinical frameworks through the Molecular Oncology Almanac to prospectively guide precision oncology. Nature Cancer. 2(10). 1102–1112. 15 indexed citations
7.
AlDubayan, Saud H., Jake R. Conway, Sabrina Y. Camp, et al.. (2020). Detection of Pathogenic Variants With Germline Genetic Testing Using Deep Learning vs Standard Methods in Patients With Prostate Cancer and Melanoma. JAMA. 324(19). 1957–1957. 24 indexed citations
8.
Kehl, Kenneth L., Wenxin Xu, Eva M. Lepisto, et al.. (2020). Natural Language Processing to Ascertain Cancer Outcomes From Medical Oncologist Notes. JCO Clinical Cancer Informatics. 4(4). 680–690. 63 indexed citations
9.
Keenan, Tanya E., David Liu, Haitham Elmarakeby, et al.. (2019). Abstract CT050: Expansion cohort of Phase I study of oral sapacitabine and oral seliciclib in patients with metastatic breast cancer and BRCA1/2 mutations. Cancer Research. 79(13_Supplement). CT050–CT050. 3 indexed citations
10.
Kehl, Kenneth L., Haitham Elmarakeby, Mizuki Nishino, et al.. (2019). Assessment of Deep Natural Language Processing in Ascertaining Oncologic Outcomes From Radiology Reports. JAMA Oncology. 5(10). 1421–1421. 97 indexed citations
11.
Conway, Jake R., Eric Kofman, Shirley Mo, Haitham Elmarakeby, & Eliezer M. Van Allen. (2018). Genomics of response to immune checkpoint therapies for cancer: implications for precision medicine. Genome Medicine. 10(1). 93–93. 113 indexed citations
12.
Kehl, Kenneth L., Haitham Elmarakeby, Eliezer M. Van Allen, & Deborah Schrag. (2018). Clinical trajectory modeling to predict hospitalization or death after palliative chemotherapy.. Journal of Clinical Oncology. 36(15_suppl). 6509–6509. 1 indexed citations
13.
Ni, Ying, Delasa Aghamirzaie, Haitham Elmarakeby, et al.. (2016). A Machine Learning Approach to Predict Gene Regulatory Networks in Seed Development in Arabidopsis. Frontiers in Plant Science. 7. 1936–1936. 37 indexed citations
14.
15.
Schneider, Andrew M., Delasa Aghamirzaie, Haitham Elmarakeby, et al.. (2015). Potential targets of VIVIPAROUS1/ABI3‐LIKE1 (VAL1) repression in developing Arabidopsis thaliana embryos. The Plant Journal. 85(2). 305–319. 54 indexed citations
16.
Weisberg, Alexandra J., Haitham Elmarakeby, Lenwood S. Heath, & Boris A. Vinatzer. (2015). Similarity-Based Codes Sequentially Assigned to Ebolavirus Genomes Are Informative of Species Membership, Associated Outbreaks, and Transmission Chains. Open Forum Infectious Diseases. 2(1). ofv024–ofv024. 8 indexed citations
17.
Elmarakeby, Haitham, et al.. (2014). Human microRNAs targeting hepatitis C virus. 41. 184–187. 1 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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