Saad Nadeem

891 total citations
45 papers, 490 citations indexed

About

Saad Nadeem is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Saad Nadeem has authored 45 papers receiving a total of 490 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Radiology, Nuclear Medicine and Imaging, 14 papers in Computer Vision and Pattern Recognition and 11 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Saad Nadeem's work include Radiomics and Machine Learning in Medical Imaging (11 papers), Lung Cancer Diagnosis and Treatment (10 papers) and Advanced Radiotherapy Techniques (8 papers). Saad Nadeem is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (11 papers), Lung Cancer Diagnosis and Treatment (10 papers) and Advanced Radiotherapy Techniques (8 papers). Saad Nadeem collaborates with scholars based in United States, China and Pakistan. Saad Nadeem's co-authors include Arie Kaufman, Allen Tannenbaum, Xianfeng Gu, Joseph O. Deasy, Rena Elkin, Helene Benveniste, Hedok Lee, R. Vanguri, Travis J. Hollmann and Pengpeng Zhang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Cancer Research and Scientific Reports.

In The Last Decade

Saad Nadeem

43 papers receiving 480 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Saad Nadeem United States 12 165 96 93 90 75 45 490
Michele Larobina Italy 16 423 2.6× 64 0.7× 22 0.2× 136 1.5× 85 1.1× 30 861
Ivan S. Klyuzhin Canada 14 333 2.0× 53 0.6× 34 0.4× 27 0.3× 69 0.9× 49 588
Evan McCreedy United States 13 127 0.8× 54 0.6× 34 0.4× 97 1.1× 106 1.4× 25 590
Qianjin Feng China 14 293 1.8× 146 1.5× 16 0.2× 133 1.5× 93 1.2× 51 689
Fernando Pérez‐García United Kingdom 9 226 1.4× 141 1.5× 27 0.3× 107 1.2× 48 0.6× 17 503
William C. Barker United States 12 247 1.5× 141 1.5× 56 0.6× 87 1.0× 42 0.6× 24 694
J. Zaers Germany 7 496 3.0× 21 0.2× 84 0.9× 93 1.0× 58 0.8× 13 763
Anders Garpebring Sweden 13 517 3.1× 55 0.6× 16 0.2× 66 0.7× 97 1.3× 37 723
William Gandler United States 16 698 4.2× 66 0.7× 38 0.4× 192 2.1× 159 2.1× 25 1.3k
Boklye Kim United States 10 490 3.0× 61 0.6× 24 0.3× 360 4.0× 53 0.7× 26 874

Countries citing papers authored by Saad Nadeem

Since Specialization
Citations

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

Fields of papers citing papers by Saad Nadeem

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Saad Nadeem

This figure shows the co-authorship network connecting the top 25 collaborators of Saad Nadeem. A scholar is included among the top collaborators of Saad Nadeem 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 Saad Nadeem. Saad Nadeem 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.
Riaz, Ahsun, et al.. (2025). Emerging nanostructure-based strategies for breast cancer therapy: innovations, challenges, and future directions. Medical Oncology. 42(6). 188–188. 1 indexed citations
2.
Marino, Joseph P., et al.. (2024). Rethinking Histology Slide Digitization Workflows for Low-Resource Settings. Lecture notes in computer science. 15004. 427–436. 1 indexed citations
3.
Nadeem, Saad, et al.. (2024). Neuropharmacology of Neuropathic Pain: A Systematic Review. Cureus. 16(9). e69028–e69028.
4.
Marino, Joseph P., et al.. (2023). An AI-Ready Multiplex Staining Dataset for Reproducible and Accurate Characterization of Tumor Immune Microenvironment. Lecture notes in computer science. 14225. 704–713. 3 indexed citations
5.
Vanguri, R., James W. Smithy, Yanyun Li, et al.. (2023). Integration of peripheral blood‐ and tissue‐based biomarkers of response to immune checkpoint blockade in urothelial carcinoma. The Journal of Pathology. 261(3). 349–360. 6 indexed citations
6.
Thor, Maria, Kelly Fitzgerald, Aditya Apte, et al.. (2023). Exploring published and novel pre-treatment CT and PET radiomics to stratify risk of progression among early-stage non-small cell lung cancer patients treated with stereotactic radiation. Radiotherapy and Oncology. 190. 109983–109983. 3 indexed citations
7.
Choi, Wookjin, Navdeep Dahiya, & Saad Nadeem. (2022). CIRDataset: A Large-Scale Dataset for Clinically-Interpretable Lung Nodule Radiomics and Malignancy Prediction. Lecture notes in computer science. 2022. 13–22. 8 indexed citations
8.
Dahiya, Navdeep, et al.. (2022). Domain knowledge driven 3D dose prediction using moment-based loss function. Physics in Medicine and Biology. 67(18). 185017–185017. 16 indexed citations
9.
Li, Yanyun, Arie Kaufman, R. Vanguri, et al.. (2022). Deep learning-inferred multiplex immunofluorescence for immunohistochemical image quantification. Nature Machine Intelligence. 4(4). 401–412. 65 indexed citations
10.
Vanguri, R., Kathleen Fenn, Qi Wang, et al.. (2022). Tumor Immune Microenvironment and Response to Neoadjuvant Chemotherapy in Hormone Receptor/HER2+ Early Stage Breast Cancer. Clinical Breast Cancer. 22(6). 538–546. 10 indexed citations
11.
Li, Tianfang, et al.. (2021). Generalizable cone beam CT esophagus segmentation using physics-based data augmentation. Physics in Medicine and Biology. 66(6). 65008–65008. 14 indexed citations
12.
Nadeem, Saad, et al.. (2020). Functional network analysis reveals an immune tolerance mechanism in cancer. Proceedings of the National Academy of Sciences. 117(28). 16339–16345. 9 indexed citations
13.
Zhang, Pengpeng, Saad Nadeem, Jue Jiang, et al.. (2020). Predictive dose accumulation for HN adaptive radiotherapy. Physics in Medicine and Biology. 65(23). 235011–235011. 7 indexed citations
14.
Choi, Wookjin, et al.. (2020). Reproducible and Interpretable Spiculation Quantification for Lung Cancer Screening. Computer Methods and Programs in Biomedicine. 200. 105839–105839. 11 indexed citations
15.
Carpenter, Kimberly L. H., Saad Nadeem, Joanne Kurtzberg, et al.. (2020). Measuring robustness of brain networks in autism spectrum disorder with Ricci curvature. Scientific Reports. 10(1). 10819–10819. 10 indexed citations
16.
Koundal, Sunil, Rena Elkin, Saad Nadeem, et al.. (2020). Optimal Mass Transport with Lagrangian Workflow Reveals Advective and Diffusion Driven Solute Transport in the Glymphatic System. Scientific Reports. 10(1). 1990–1990. 88 indexed citations
17.
Koundal, Sunil, Rena Elkin, Saad Nadeem, et al.. (2020). Publisher Correction: Optimal Mass Transport with Lagrangian Workflow Reveals Advective and Diffusion Driven Solute Transport in the Glymphatic System. Scientific Reports. 10(1). 3934–3934. 7 indexed citations
18.
Wang, Chuang, Siyuan Zhang, Yu‐Chi Hu, et al.. (2020). Predicting spatial esophageal changes in a multimodal longitudinal imaging study via a convolutional recurrent neural network. Physics in Medicine and Biology. 65(23). 235027–235027. 13 indexed citations
19.
Elkin, Rena, Saad Nadeem, Eldad Haber, et al.. (2018). GlymphVIS: Visualizing Glymphatic Transport Pathways Using Regularized Optimal Transport. Lecture notes in computer science. 11070. 844–852. 18 indexed citations
20.
Nadeem, Saad & Arie Kaufman. (2016). Computer-aided detection of polyps in optical colonoscopy images. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9785. 978525–978525. 14 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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