Nicholas Heller

895 total citations
24 papers, 141 citations indexed

About

Nicholas Heller is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Biomedical Engineering. According to data from OpenAlex, Nicholas Heller has authored 24 papers receiving a total of 141 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Radiology, Nuclear Medicine and Imaging, 8 papers in Pulmonary and Respiratory Medicine and 6 papers in Biomedical Engineering. Recurrent topics in Nicholas Heller's work include Radiomics and Machine Learning in Medical Imaging (9 papers), Renal cell carcinoma treatment (6 papers) and Advanced X-ray and CT Imaging (5 papers). Nicholas Heller is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (9 papers), Renal cell carcinoma treatment (6 papers) and Advanced X-ray and CT Imaging (5 papers). Nicholas Heller collaborates with scholars based in United States, Germany and Thailand. Nicholas Heller's co-authors include Nikolaos Papanikolopoulos, Christopher Weight, Resha Tejpaul, Paul Blake, Joel Rosenberg, Arveen Kalapara, Ranveer Vasdev, Subodh Regmi, Sean McSweeney and Yiming Xiao and has published in prestigious journals such as Journal of Clinical Oncology, Cancer Research and The Journal of Urology.

In The Last Decade

Nicholas Heller

19 papers receiving 137 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nicholas Heller United States 6 41 36 36 26 22 24 141
Ranveer Vasdev United States 6 47 1.1× 21 0.6× 24 0.7× 11 0.4× 24 1.1× 22 120
Paul Blake United States 6 38 0.9× 28 0.8× 60 1.7× 13 0.5× 23 1.0× 13 165
Sonish Sivarajkumar United States 7 77 1.9× 84 2.3× 30 0.8× 10 0.4× 25 1.1× 14 276
Rachel Lea Draelos United States 7 41 1.0× 109 3.0× 59 1.6× 14 0.5× 9 0.4× 9 227
Liangyuan Na United States 3 82 2.0× 101 2.8× 49 1.4× 7 0.3× 41 1.9× 4 246
Swaminathan Ramasubramanian India 8 55 1.3× 31 0.9× 26 0.7× 4 0.2× 23 1.0× 59 262
Philip Rothschild Australia 3 117 2.9× 29 0.8× 86 2.4× 6 0.2× 34 1.5× 6 207
Luis Filipe Nakayama Brazil 11 78 1.9× 32 0.9× 147 4.1× 9 0.3× 37 1.7× 54 348
Sean McSweeney United States 5 39 1.0× 16 0.4× 16 0.4× 5 0.2× 21 1.0× 10 124
Zongming Zhang China 6 128 3.1× 53 1.5× 65 1.8× 4 0.2× 42 1.9× 15 252

Countries citing papers authored by Nicholas Heller

Since Specialization
Citations

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

Fields of papers citing papers by Nicholas Heller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nicholas Heller

This figure shows the co-authorship network connecting the top 25 collaborators of Nicholas Heller. A scholar is included among the top collaborators of Nicholas Heller 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 Nicholas Heller. Nicholas Heller 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.
Heller, Nicholas, Betty Wang, Rebecca A. Campbell, et al.. (2025). AUTOMATING RENAL CANCER CHART REVIEW USING LARGE LANGUAGE MODELS. Urologic Oncology Seminars and Original Investigations. 43(3). 57–58. 1 indexed citations
2.
Muñoz-López, Carlos, Nityam Rathi, Anne Wong, et al.. (2025). Renal parenchymal volume analysis: Clinical and research applications. BJUI Compass. 6(3). e70013–e70013. 5 indexed citations
3.
Raman, A., David R. Fisher, Christopher Weight, et al.. (2025). Evaluation of nnU-Net for kidney tumor segmentation on a large external patient cohort. 3. 100035–100035. 2 indexed citations
4.
Pawan, S. J., Shahin Nazarian, Nicholas Heller, et al.. (2025). A Study on Energy Consumption in AI-Driven Medical Image Segmentation. Journal of Imaging. 11(6). 174–174.
5.
Wood, Andrew M., Nicholas Heller, Fabian Isensee, et al.. (2024). Fully Automated Versions of Clinically Validated Nephrometry Scores Demonstrate Superior Predictive Utility versus Human Scores. British Journal of Urology. 133(6). 690–698.
6.
Heller, Nicholas, et al.. (2023). Demonstration of Convolutional Neural Networks to Determine Patch Test Reactivity. Dermatitis. 35(2). 144–148. 2 indexed citations
7.
Heller, Nicholas, et al.. (2023). Abstract 191: CTC-derived organoids from liver and pancreatic cancer patients for personalized therapy. Cancer Research. 83(7_Supplement). 191–191. 2 indexed citations
8.
Heller, Nicholas, Andrew Wood, Fabian Isensee, et al.. (2023). Accuracy of fully automated, AI-generated models compared with validated clinical model to predict post-operative glomerular filtration rate after renal surgery.. Journal of Clinical Oncology. 41(6_suppl). 693–693. 2 indexed citations
9.
Kowalewski, Timothy M., Anna French, Nicholas Heller, et al.. (2021). Virtual Reality Warm-up Before Robot-assisted Surgery: A Randomized Controlled Trial. Journal of Surgical Research. 264. 107–116. 4 indexed citations
10.
Heller, Nicholas, Matthew Peterson, Stephanie Peterson, et al.. (2020). An international challenge to use artificial intelligence to define the state of the art in kidney and kidney tumor segmentation in CT imaging. European Urology Open Science. 19. e738–e738. 5 indexed citations
11.
Heller, Nicholas, Sean McSweeney, Paul Blake, et al.. (2020). Public Perceptions of Artificial Intelligence and Robotics in Medicine. Journal of Endourology. 34(10). 1041–1048. 66 indexed citations
12.
Heller, Nicholas, et al.. (2020). Temporal variability of surgical technical skill perception in real robotic surgery. International Journal of Computer Assisted Radiology and Surgery. 15(12). 2101–2107. 1 indexed citations
13.
Heller, Nicholas, Sean McSweeney, Matthew Peterson, et al.. (2020). MP42-11 AN INTERNATIONAL CHALLENGE TO USE ARTIFICIAL INTELLIGENCE TO DEFINE THE STATE OF THE ART IN KIDNEY AND KIDNEY TUMOR SEGMENTATION IN CT IMAGING. The Journal of Urology. 203(Supplement 4).
14.
Kleeman, Sam O., Kathrine S Rallis, Resha Tejpaul, et al.. (2020). CT-based radiomic classifier of primary renal tumors to distinguish between metastatic and non-metastatic disease.. Journal of Clinical Oncology. 38(15_suppl). 5074–5074. 1 indexed citations
15.
Heller, Nicholas, Sean McSweeney, Matthew Peterson, et al.. (2020). An international challenge to use artificial intelligence to define the state-of-the-art in kidney and kidney tumor segmentation in CT imaging.. Journal of Clinical Oncology. 38(6_suppl). 626–626. 10 indexed citations
16.
Masterson, Thomas A., Michael B. Tradewell, Sirpi Nackeeran, et al.. (2020). Using Artificial Intelligence to Predict Surgical Shunts in Men with Ischemic Priapism. The Journal of Urology. 204(5). 1033–1038. 4 indexed citations
17.
Heller, Nicholas, Nikolaos Papanikolopoulos, & Christopher Weight. (2020). 2021 Kidney and Kidney Tumor Segmentation Challenge. Zenodo (CERN European Organization for Nuclear Research). 2 indexed citations
18.
Heller, Nicholas, Sean McSweeney, Paul A. Blake, et al.. (2020). PD23-03 PUBLIC PERCEPTIONS OF AI IN MEDICINE. The Journal of Urology. 203(Supplement 4). 1 indexed citations
19.
Zhou, Luping, Nicholas Heller, Yiyu Shi, et al.. (2019). Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention. Lecture notes in computer science. 15 indexed citations
20.
Heller, Nicholas, et al.. (2018). Computer Aided Diagnosis of Skin Lesions from Morphological Features. University of Minnesota Digital Conservancy (University of Minnesota). 8 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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