Daniel C. Elton

2.0k citations
28 papers · 1.1k · 1 hit paper · h-index 15

Impact in

Papers in

Daniel C. Elton

27 papers receiving 1.1k citations

Daniel C. Elton's Hit Papers

Deep learning for molecular design—a review of the state of the art 2019 · 431 citations
4310+2+4Years since publication100200300400

Peers

Daniel C. Elton
Comparison fields: 5 of 129
  • Computational Theory and Mathematics 308
  • Health Informatics 19
  • Materials Chemistry 349
  • Radiology, Nuclear Medicine and Imaging 141
  • Biophysics 39
Replace Kyungsoo Park with:
Kyungsoo Park South Korea
Abraham C. Stern United States
Hiroaki Satoh Japan
Kaname Matsue Japan
Peter J. Tandler United States
Sergey V. Matveev Russia
Janet M. Griffiths United States
Taewoo Lee United States
Ziping Li China
Yuzhi Zhang China
Daniel C. Elton relative to Kyungsoo Park South Korea Kyungsoo Park's profile →
Citations per field
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Kyungsoo Park · 1×
Citations per year

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-authors

The 25 scholars most cited alongside Daniel C. Elton, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel C. Elton Line = papers co-authored together Daniel C. Elton links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Deep learning for molecular design—a review of the state of the art
Hit paper breakdown →
2019431
2 202183
3 201678
4 202276
5 201868
6 201762
7 202047
8 202046
9 202036
10 202229
11 202026
12 202126
13 202226
14 201922
15 202219
16 201612
17
Deep learning for molecular generation and optimization - a review of the state of the art
20199
18 20238
19 20206
20 20234

About Daniel C. Elton

Daniel C. Elton is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Materials Chemistry, Pediatrics, Perinatology and Child Health and Epidemiology, having authored 28 papers that have together received 1.1k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (5 papers), Machine Learning in Materials Science (4 papers), Liver Disease Diagnosis and Treatment (3 papers), Kidney Stones and Urolithiasis Treatments (3 papers), Computational Drug Discovery Methods (3 papers), Radiation Dose and Imaging (3 papers), MRI in cancer diagnosis (2 papers) and Medical Imaging Techniques and Applications (2 papers). The work is most often cited by research in Computational Theory and Mathematics (308 citations), Health Informatics (19 citations), Materials Chemistry (349 citations), Radiology, Nuclear Medicine and Imaging (141 citations) and Biophysics (39 citations). Daniel C. Elton has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include Peter W. Chung, Mark Fuge, Zois Boukouvalas, Ronald M. Summers, Perry J. Pickhardt, Mariví Fernández-Serra, Alberto A. Perez, Peter M. Graffy, Meghan G. Lubner and Evrim Türkbey. Their work appears in journals such as Abdominal Radiology, Radiology, Medical Physics, Journal of the American College of Radiology and Tomography.

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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