Mark J. Gooding

2.4k citations
64 papers · 1.6k · h-index 20

Impact in

Papers in

Mark J. Gooding

62 papers receiving 1.6k citations

Peers

Mark J. Gooding
Comparison fields: 5 of 91
  • Radiation 684
  • Health Informatics 97
  • Radiology, Nuclear Medicine and Imaging 669
  • Otorhinolaryngology 60
  • Biophysics 56
Replace Neelam Tyagi with:
Neelam Tyagi United States
Hidetaka Arimura Japan
Yong Yin China
Linghong Zhou China
Geoffrey Zhang United States
Kuo Men China
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Avishek Chatterjee Netherlands
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Citations per field
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Citations per year

Countries citing papers authored by Mark J. Gooding

Since Specialization
Citations

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

Fields of papers citing papers by Mark J. Gooding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark J. Gooding. 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 Mark J. Gooding. The network helps show where Mark J. Gooding may publish in the future.

Co-authors

The 25 scholars most cited alongside Mark J. Gooding, 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 Mark J. Gooding Line = papers co-authored together Mark J. Gooding links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 64 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017264
2 2018180
3 2019154
4 2019129
5 2019106
6 201864
7 201260
8 202047
9 201143
10 202039
11 202034
12 200931
13 200527
14 202026
15 201925
16 200825
17 201624
18 201023
19 201822
20 202220

About Mark J. Gooding

Mark J. Gooding is a scholar working on Radiation, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Biomedical Engineering and Artificial Intelligence, having authored 64 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced Radiotherapy Techniques (26 papers), Radiomics and Machine Learning in Medical Imaging (12 papers), Medical Imaging Techniques and Applications (7 papers), Ultrasound Imaging and Elastography (6 papers), Medical Image Segmentation Techniques (6 papers), Lung Cancer Diagnosis and Treatment (4 papers), AI in cancer detection (4 papers) and Advanced X-ray and CT Imaging (3 papers). The work is most often cited by research in Radiation (684 citations), Health Informatics (97 citations), Radiology, Nuclear Medicine and Imaging (669 citations), Otorhinolaryngology (60 citations) and Biophysics (56 citations). Mark J. Gooding has collaborated with scholars based in United Kingdom, Netherlands and United States. Frequent co-authors include Wouter van Elmpt, Paul Aljabar, Devis Peressutti, André Dekker, Tim Lustberg, Johan van Soest, J. van der Stoep, Katherine A. Vallis, Eleanor Stride and Charlotte L. Brouwer. Their work appears in journals such as Radiotherapy and Oncology, Medical Physics, Physics and Imaging in Radiation Oncology, IEEE Transactions on Medical Imaging and Ultrasound in Medicine & Biology.

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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