Usama Salem

509 total citations
19 papers, 334 citations indexed

About

Usama Salem is a scholar working on Surgery, Oncology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Usama Salem has authored 19 papers receiving a total of 334 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Surgery, 8 papers in Oncology and 6 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Usama Salem's work include Radiomics and Machine Learning in Medical Imaging (3 papers), Hepatocellular Carcinoma Treatment and Prognosis (3 papers) and Cardiac tumors and thrombi (3 papers). Usama Salem is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (3 papers), Hepatocellular Carcinoma Treatment and Prognosis (3 papers) and Cardiac tumors and thrombi (3 papers). Usama Salem collaborates with scholars based in United States, Egypt and Türkiye. Usama Salem's co-authors include John E. Madewell, Dhiego Chaves de Almeida Bastos, Pascal O. Zinn, Vinodh A. Kumar, Sujit S. Prabhu, Ganesh Rao, Jeffrey S. Weinberg, Rivka R. Colen, Donald F. Schomer and Corey T. Jensen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Radiology.

In The Last Decade

Usama Salem

16 papers receiving 332 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Usama Salem United States 9 142 123 96 60 51 19 334
Amandine Pallardy France 12 241 1.7× 52 0.4× 137 1.4× 49 0.8× 78 1.5× 28 446
James K. O’Donnell United States 12 299 2.1× 105 0.9× 114 1.2× 81 1.4× 32 0.6× 29 458
Dhiego Chaves de Almeida Bastos United States 12 127 0.9× 117 1.0× 110 1.1× 85 1.4× 24 0.5× 22 421
Eun Seong Lee South Korea 11 153 1.1× 41 0.3× 106 1.1× 38 0.6× 93 1.8× 34 454
Xingqi Lu China 11 242 1.7× 48 0.4× 181 1.9× 40 0.7× 41 0.8× 25 479
Hiroto Murata Japan 11 73 0.5× 77 0.6× 52 0.5× 65 1.1× 28 0.5× 36 345
Maximilian Rauch Germany 10 48 0.3× 113 0.9× 57 0.6× 60 1.0× 125 2.5× 28 326
Julia Fruehwald‐Pallamar Austria 12 278 2.0× 93 0.8× 57 0.6× 122 2.0× 39 0.8× 20 458
Frédérique Charbonneau France 12 181 1.3× 34 0.3× 145 1.5× 40 0.7× 20 0.4× 30 404
Deborah Bauwens Belgium 8 236 1.7× 177 1.4× 39 0.4× 50 0.8× 53 1.0× 9 469

Countries citing papers authored by Usama Salem

Since Specialization
Citations

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

Fields of papers citing papers by Usama Salem

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Usama Salem

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

All Works

19 of 19 papers shown
1.
Hwang, Ken‐Pin, Jingfei Ma, Usama Salem, et al.. (2025). T2‐weighted imaging of rectal cancer using a 3D fast spin echo sequence with and without deep learning reconstruction: A reader study. Journal of Applied Clinical Medical Physics. 26(5). e70031–e70031.
2.
Awiwi, Muhammad O., et al.. (2025). Rectal Cancer MRI: An Update. Seminars in Roentgenology. 60(1). 61–77.
3.
Cazoulat, Guillaume, Sireesha Yedururi, B. Rigaud, et al.. (2024). Fully automated deep learning based auto-contouring of liver segments and spleen on contrast-enhanced CT images. Scientific Reports. 14(1). 4678–4678. 3 indexed citations
4.
Elsayes, Khaled M., et al.. (2024). Tumor-like conditions that mimic liver tumors. Diagnostic and Interventional Radiology. 31(4). 285–294.
5.
Awiwi, Muhammad O., Raghunandan Vikram, Emre Altınmakas, et al.. (2023). MRI and PSMA PET/CT of Biochemical Recurrence of Prostate Cancer. Radiographics. 43(12). e230112–e230112. 12 indexed citations
6.
Awiwi, Muhammad O., Harmeet Kaur, Randy D. Ernst, et al.. (2023). Restaging MRI of Rectal Adenocarcinoma after Neoadjuvant Chemoradiotherapy: Imaging Findings and Potential Pitfalls. Radiographics. 43(4). e220135–e220135. 16 indexed citations
7.
Awiwi, Muhammad O., et al.. (2022). The Prognostic Value of Baseline Clinical and Radiologic Imaging Features in Patients with Unresectable Hepatocellular Carcinoma Treated with Atezolizumab Plus Bevacizumab. SHILAP Revista de lepidopterología. Volume 9. 913–927. 6 indexed citations
8.
Jensen, Corey T., Shiva Gupta, Mohammed Saleh, et al.. (2022). Reduced-Dose Deep Learning Reconstruction for Abdominal CT of Liver Metastases. Radiology. 303(1). 90–98. 72 indexed citations
9.
Salem, Usama, Brinda Rao Korivi, Michael T. Corwin, et al.. (2022). Cystic adrenal masses: spectrum of multimodality imaging features and pathological correlation. Clinical Radiology. 77(7). 479–488. 1 indexed citations
10.
Kothari, Anai N., Michael G. White, Oliver Peacock, et al.. (2022). Pathological response following neoadjuvant immunotherapy in mismatch repair-deficient/microsatellite instability-high locally advanced, non-metastatic colorectal cancer. British journal of surgery. 109(6). 489–492. 19 indexed citations
11.
Jensen, Corey T., Ahmed Taher, Ajaykumar C. Morani, et al.. (2021). Mastocytosis—A Review of Disease Spectrum with Imaging Correlation. Cancers. 13(20). 5102–5102. 5 indexed citations
12.
Moawad, Ahmed W., Usama Salem, Brinda Rao Korivi, et al.. (2021). Oncologic Imaging of the Lymphatic System: Current Perspective with Multi-Modality Imaging and New Horizon. Cancers. 13(18). 4554–4554. 6 indexed citations
13.
Salem, Usama, Vinodh A. Kumar, John E. Madewell, et al.. (2019). Neurosurgical applications of MRI guided laser interstitial thermal therapy (LITT). Cancer Imaging. 19(1). 65–65. 128 indexed citations
14.
Yedururi, Sireesha, Behrang Amini, Wei Wei, et al.. (2018). Tumor thrombus in the large veins draining primary pelvic osteosarcoma on cross sectional imaging. European Journal of Radiology. 105. 49–55. 10 indexed citations
15.
Salem, Usama, Behrang Amini, Hubert H. Chuang, et al.. (2017). 18F-FDG PET/CT as an Indicator of Survival in Ewing Sarcoma of Bone. Journal of Cancer. 8(15). 2892–2898. 19 indexed citations
16.
Chrisinger, John S.A., Usama Salem, Lars‐Gunnar Kindblom, et al.. (2017). Synovial Sarcoma of Peripheral Nerves. The American Journal of Surgical Pathology. 41(8). 1087–1096. 9 indexed citations
17.
Salem, Usama, Ping Zhang, Jeffrey L. Jorgensen, Rajendra Kumar, & Behrang Amini. (2014). Adhesive Capsulitis Mimicking Metastasis on 18F-FDG-PET/CT. Clinical Nuclear Medicine. 40(2). e145–e147. 7 indexed citations
18.
Salem, Usama, et al.. (2014). Hematopoietic tumors of the female genital system: imaging features with pathologic correlation. Abdominal Imaging. 39(4). 922–934. 5 indexed citations
19.
Ganeshan, Dhakshina Moorthy, Usama Salem, Chitra Viswanathan, et al.. (2012). Complications of oncologic therapy in the abdomen and pelvis: a review. Abdominal Imaging. 38(1). 1–21. 16 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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