Mark J. Gooding

62 papers receiving 1.6k citations

Hit Papers

Clinical evaluation of atlas and deep learning based auto...2017202620202023201750100150200250

Peers

Mark J. Gooding
Comparison fields: 5 of 103
  • Radiology, Nuclear Medicine and Imaging 1.1k
  • Radiation 781
  • Biomedical Engineering 453
  • Pulmonary and Respiratory Medicine 378
  • Artificial Intelligence 252
Replace Bulat Ibragimov with:
Bulat Ibragimov Denmark
Pretesh Patel United States
Liyuan Chen China
Hossein Arabi Switzerland
Annette Haworth Australia
Gilmer Valdés United States
Yong Yin China
Hidetaka Arimura Japan
Linghong Zhou China
Neelam Tyagi United States
Mark J. Gooding relative to Bulat Ibragimov Denmark Bulat Ibragimov's profile →
Citations per field
00.5×1.5×1.9×
Bulat Ibragimov · 1×
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-authorship network of co-authors of Mark J. Gooding

This figure shows the co-authorship network connecting the top 25 collaborators of Mark J. Gooding. A scholar is included among the top collaborators of Mark J. Gooding 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 Mark J. Gooding. Mark J. Gooding 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
#WorkIndexed citations
1 1
2 5
3 4
4 1
5 1
6 2
7 20
8 47
9 153
10 25
11 127
12 22
13
Validation Of 4 Models To Estimate The Probability Of Malignancy In Patients With Sub-Centimeter Pulmonary Nodules
1
14 13
15 23
16 31
17 14
18 5
19 2
20 23

About Mark J. Gooding

Mark J. Gooding is a scholar working on Radiation, Radiology, Nuclear Medicine and Imaging and Otorhinolaryngology, having authored 64 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced Radiotherapy Techniques (32 papers), Radiomics and Machine Learning in Medical Imaging (23 papers) and Medical Imaging Techniques and Applications (14 papers). The work is most often cited by research in Radiation (781 citations), Health Informatics (118 citations) and Radiology, Nuclear Medicine and Imaging (1.1k 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, Johan van Soest, Tim Lustberg, J. van der Stoep, Eleanor Stride, Katherine A. Vallis and Charlotte L. Brouwer. Their work appears in journals such as American Journal of Respiratory and Critical Care Medicine, International Journal of Radiation Oncology*Biology*Physics and IEEE Transactions on Medical Imaging.

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

Rankless by CCL
2026