David Manning

1.5k citations
64 papers · 1.3k · h-index 18

Impact in

Papers in

David Manning

59 papers receiving 1.2k citations

Peers

David Manning
Comparison fields: 5 of 92
  • Family Practice 90
  • Radiology, Nuclear Medicine and Imaging 662
  • Human-Computer Interaction 134
  • Health Informatics 26
  • Computer Vision and Pattern Recognition 170
Replace Harold L. Kundel with:
Harold L. Kundel United States
Lawrence C. Toto United States
Robert T. Caldwell United States
Ellen M. Kok Netherlands
Jan P. J. van Schaik Netherlands
Stephen Waite United States
Kevin M. Schartz United States
Warren Michael Reed Australia
Anouk van der Gijp Netherlands
William F. Auffermann United States
David Manning relative to Harold L. Kundel United States Harold L. Kundel's profile →
Citations per field
00.5×2×3×3.6×
Harold L. Kundel · 1×
Citations per year

Countries citing papers authored by David Manning

Since Specialization
Citations

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

Fields of papers citing papers by David Manning

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside David Manning, 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 David Manning Line = papers co-authored together David Manning 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 2005174
2 2010123
3 2004113
4 200797
5 201070
6 201455
7 200549
8 200639
9 200532
10 199931
11 201331
12 200528
13 200624
14 200824
15 200722
16 200822
17 201422
18 201321
19 199918
20 201218

About David Manning

David Manning is a scholar working on Radiology, Nuclear Medicine and Imaging, Human-Computer Interaction, Artificial Intelligence, Computer Vision and Pattern Recognition and Health Informatics, having authored 64 papers that have together received 1.3k indexed citations. Recurring topics across this work include Radiology practices and education (43 papers), AI in cancer detection (11 papers), Radiation Dose and Imaging (10 papers), Radiomics and Machine Learning in Medical Imaging (7 papers), Lung Cancer Diagnosis and Treatment (6 papers), Gaze Tracking and Assistive Technology (5 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Image and Video Quality Assessment (3 papers). The work is most often cited by research in Family Practice (90 citations), Radiology, Nuclear Medicine and Imaging (662 citations), Human-Computer Interaction (134 citations), Health Informatics (26 citations) and Computer Vision and Pattern Recognition (170 citations). David Manning has collaborated with scholars based in United Kingdom, United States and Ireland. Frequent co-authors include Tim Donovan, Trevor J. Crawford, Susan C. Ethell, Peter W. Phillips, Patrick Brennan, Mark F. McEntee, Alastair G. Gale, Damien Litchfield, Linden J. Ball and Michael G. Evanoff. Their work appears in journals such as British Journal of Radiology, Academic Radiology, American Journal of Roentgenology, Radiology and Radiography.

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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