Daniel C. Elton

1.9k total citations · 1 hit paper
26 papers, 1.1k citations indexed

About

Daniel C. Elton is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Epidemiology. According to data from OpenAlex, Daniel C. Elton has authored 26 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Pulmonary and Respiratory Medicine and 4 papers in Epidemiology. Recurrent topics in Daniel C. Elton's work include Radiomics and Machine Learning in Medical Imaging (6 papers), Machine Learning in Materials Science (4 papers) and Liver Disease Diagnosis and Treatment (4 papers). Daniel C. Elton is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (6 papers), Machine Learning in Materials Science (4 papers) and Liver Disease Diagnosis and Treatment (4 papers). Daniel C. Elton collaborates with scholars based in United States, United Kingdom and Australia. Daniel C. Elton's co-authors include Peter W. Chung, Zois Boukouvalas, Mark Fuge, Ronald M. Summers, Perry J. Pickhardt, Mariví Fernández-Serra, Alberto A. Perez, Peter M. Graffy, Meghan G. Lubner and Veit Sandfort and has published in prestigious journals such as Nature Communications, Radiology and International Journal of Molecular Sciences.

In The Last Decade

Daniel C. Elton

26 papers receiving 1.0k citations

Hit Papers

align trajectories

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.

Deep learning for molecular design—a review of the state of the art

2019 416 citations Daniel C. Elton, Zois Boukouvalas et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel C. Elton United States	15	345	302	213	209	201	26	1.1k
Kyungsoo Park South Korea	23	167 0.5×	138 0.5×	370 1.7×	40 0.2×	50 0.2×	104	1.5k
Mark A. McCoy United States	28	273 0.8×	98 0.3×	1.1k 4.9×	363 1.7×	273 1.4×	67	2.0k
Anuroop Sriram United States	10	582 1.7×	138 0.5×	45 0.2×	183 0.9×	95 0.5×	14	1.2k
Jianping Song China	22	62 0.2×	200 0.7×	235 1.1×	41 0.2×	79 0.4×	96	1.6k
Andrea Rizzi Italy	17	259 0.8×	351 1.2×	589 2.8×	17 0.1×	36 0.2×	46	1.2k
William K. Thompson United States	17	224 0.6×	31 0.1×	239 1.1×	46 0.2×	112 0.6×	50	1.2k
Yoshio Yamada Japan	28	403 1.2×	312 1.0×	146 0.7×	142 0.7×	198 1.0×	189	2.9k
Giovanni Villani Italy	25	118 0.3×	35 0.1×	355 1.7×	103 0.5×	62 0.3×	130	2.3k
‪Zhehui Wang United States	21	309 0.9×	43 0.1×	86 0.4×	110 0.5×	285 1.4×	135	1.7k
Pengyuan Chen China	15	156 0.5×	33 0.1×	39 0.2×	44 0.2×	95 0.5×	67	754

Countries citing papers authored by Daniel C. Elton

Since Specialization

Citations

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

Fields of papers citing papers by Daniel C. Elton

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel C. Elton. 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 Daniel C. Elton. The network helps show where Daniel C. Elton may publish in the future.

Co-authorship network of co-authors of Daniel C. Elton

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Yatim, Karim, Daniel C. Elton, Marcio Aloísio Bezerra Cavalcanti Rockenbach, et al.. (2025). Applying Artificial Intelligence to Quantify Body Composition on Abdominal CTs and Better Predict Kidney Transplantation Wait-List Mortality. Journal of the American College of Radiology. 22(3). 332–341. 4 indexed citations

Shen, Thomas C., et al.. (2024). Detection of abdominopelvic lymph nodes in multi-parametric MRI. Computerized Medical Imaging and Graphics. 114. 102363–102363. 2 indexed citations

Lee, Sungwon, et al.. (2023). Universal detection and segmentation of lymph nodes in multi-parametric MRI. International Journal of Computer Assisted Radiology and Surgery. 19(1). 163–170. 4 indexed citations

Mukherjee, Pritam, Sungwon Lee, Daniel C. Elton, et al.. (2023). Fully Automated Longitudinal Assessment of Renal Stone Burden on Serial CT Imaging Using Deep Learning. Journal of Endourology. 37(8). 948–955. 7 indexed citations

Lee, Sungwon, Daniel C. Elton, Alexander H. Yang, et al.. (2022). Fully Automated and Explainable Liver Segmental Volume Ratio and Spleen Segmentation at CT for Diagnosing Cirrhosis. Radiology Artificial Intelligence. 4(5). e210268–e210268. 23 indexed citations

Lee, Sung Won, Daniel C. Elton, James L. Gulley, et al.. (2022). Assessment of Aortoiliac Atherosclerotic Plaque on CT in Prostate Cancer Patients Undergoing Treatment. Tomography. 8(2). 607–616. 1 indexed citations

Wang, Shuai, Yingying Zhu, Sung Won Lee, et al.. (2022). Global-Local attention network with multi-task uncertainty loss for abnormal lymph node detection in MR images. Medical Image Analysis. 77. 102345–102345. 19 indexed citations

Elton, Daniel C., et al.. (2022). Fully Automated Abdominal CT Biomarkers for Type 2 Diabetes Using Deep Learning. Radiology. 304(1). 85–95. 27 indexed citations

Perez, Alberto A., Meghan G. Lubner, Peter M. Graffy, et al.. (2021). Deep Learning CT-based Quantitative Visualization Tool for Liver Volume Estimation: Defining Normal and Hepatomegaly. Radiology. 302(2). 336–342. 25 indexed citations

10.

Pickhardt, Perry J., Peter M. Graffy, Alberto A. Perez, et al.. (2021). Opportunistic Screening at Abdominal CT: Use of Automated Body Composition Biomarkers for Added Cardiometabolic Value. Radiographics. 41(2). 524–542. 78 indexed citations

11.

Elton, Daniel C.. (2020). Self-explainability as an alternative to interpretability for judging the trustworthiness of artificial intelligences.. arXiv (Cornell University). 1 indexed citations

12.

Perez, Alberto A., Perry J. Pickhardt, Daniel C. Elton, Veit Sandfort, & Ronald M. Summers. (2020). Fully automated CT imaging biomarkers of bone, muscle, and fat: correcting for the effect of intravenous contrast. Abdominal Radiology. 46(3). 1229–1235. 45 indexed citations

13.

Summers, Ronald M., Daniel C. Elton, Sungwon Lee, et al.. (2020). Atherosclerotic Plaque Burden on Abdominal CT: Automated Assessment With Deep Learning on Noncontrast and Contrast-enhanced Scans. Academic Radiology. 28(11). 1491–1499. 32 indexed citations

14.

Pickhardt, Perry J., Glen M. Blake, Peter M. Graffy, et al.. (2020). Liver Steatosis Categorization on Contrast-Enhanced CT Using a Fully Automated Deep Learning Volumetric Segmentation Tool: Evaluation in 1204 Healthy Adults Using Unenhanced CT as a Reference Standard. American Journal of Roentgenology. 217(2). 359–367. 44 indexed citations

15.

Peng, Yifan, Daniel C. Elton, Thomas C. Shen, et al.. (2020). Automatic recognition of abdominal lymph nodes from clinical text. 101–110. 3 indexed citations

16.

Elton, Daniel C., et al.. (2020). Exclusion Zone Phenomena in Water—A Critical Review of Experimental Findings and Theories. International Journal of Molecular Sciences. 21(14). 5041–5041. 25 indexed citations

17.

Boukouvalas, Zois, et al.. (2020). Independent Vector Analysis for Molecular Data Fusion: Application to Property Prediction and Knowledge Discovery of Energetic Materials. 1030–1034. 6 indexed citations

18.

Elton, Daniel C., Zois Boukouvalas, Mark Fuge, & Peter W. Chung. (2019). Deep learning for molecular generation and optimization - a review of the state of the art. arXiv (Cornell University). 9 indexed citations

19.

Elton, Daniel C., et al.. (2019). Phonon Lifetimes and Thermal Conductivity of the Molecular Crystal α-RDX. MRS Advances. 4(40). 2191–2199. 20 indexed citations

20.

Elton, Daniel C. & Mariví Fernández-Serra. (2016). The hydrogen-bond network of water supports propagating optical phonon-like modes. Nature Communications. 7(1). 10193–10193. 75 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.

Explore authors with similar magnitude of impact