Christopher A. Lovejoy

1.5k citations
14 papers · 844 indexed · 1 hit paper · h-index 9
Topics
Artificial Intelligence in Healthcare and Education (4 papers)Radiomics and Machine Learning in Medical Imaging (2 papers)Fibromyalgia and Chronic Fatigue Syndrome Research (2 papers)

In The Last Decade

Christopher A. Lovejoy

13 papers receiving 821 citations

Hit Papers

Artificial intelligence versus clinicians: systematic rev...20202026202220242020200400600

Peers

Christopher A. Lovejoy
Comparison fields: 5 of 116
  • Health Informatics 335
  • Radiology, Nuclear Medicine and Imaging 306
  • Artificial Intelligence 238
  • Health Information Management 77
  • Public Health, Environmental and Occupational Health 72
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Citations per field
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Countries citing papers authored by Christopher A. Lovejoy

Since Specialization
Citations

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

Fields of papers citing papers by Christopher A. Lovejoy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christopher A. Lovejoy. 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 Christopher A. Lovejoy. The network helps show where Christopher A. Lovejoy may publish in the future.

Co-authorship network of co-authors of Christopher A. Lovejoy

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

All Works

14 of 14 papers shown
#WorkIndexed citations
1 2
2 1
3 8
4 16
5 14
6 6
7 1
8
Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studiesbreakdown →
641
9
Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies in medical imaging.
23
10 9
11 44
12 14
13 0
14 65

About Christopher A. Lovejoy

Christopher A. Lovejoy is a scholar working on Health Informatics, Issues, ethics and legal aspects and Health Information Management, having authored 14 papers that have together received 844 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (4 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Fibromyalgia and Chronic Fatigue Syndrome Research (2 papers). The work is most often cited by research in Health Informatics (335 citations), Health Information Management (77 citations) and Radiology, Nuclear Medicine and Imaging (306 citations). Christopher A. Lovejoy has collaborated with scholars based in United Kingdom, United States and Switzerland. Frequent co-authors include Mahiben Maruthappu, Myura Nagendran, Matthieu Komorowski, Eric J. Topol, Gary S. Collins, Yang Chen, Hugh Harvey, John P. A. Ioannidis, Anthony Gordon and Sarah Cassidy. Their work appears in journals such as PLoS ONE, BMJ and IEEE Access.

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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