Michael Milne

471 citations
19 papers · 311 · h-index 12

Impact in

Papers in

Michael Milne

17 papers receiving 300 citations

Peers

Michael Milne
Comparison fields: 5 of 80
  • Health Informatics 28
  • Insect Science 122
  • Behavioral Neuroscience 13
  • Ecology, Evolution, Behavior and Systematics 67
  • Radiology, Nuclear Medicine and Imaging 75
Replace M. Hirai with:
M. Hirai Japan
Sandra Hope United States
H. Vogt United States
Zia J. Penefsky United States
Alexandra Dainis United States
Ryan Sprissler United States
Limin Yan China
Maria Cristina Grò Italy
Moon Young Kim South Korea
Tsuyoshi Ando Japan
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Citations per field
00.5×4.8×
M. Hirai · 1×
Citations per year

Countries citing papers authored by Michael Milne

Since Specialization
Citations

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

Fields of papers citing papers by Michael Milne

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

19 of 19 papers shown
#Work
1 200046
2 201633
3 200230
4 202128
5 201424
6 199821
7 202320
8 202219
9 202119
10 199819
11 200715
12 201714
13 20219
14 20166
15 20234
16 20073
17 19981
18 20240
19 20230

About Michael Milne

Michael Milne is a scholar working on Radiology, Nuclear Medicine and Imaging, Insect Science, Plant Science, Ecology, Evolution, Behavior and Systematics and Biomedical Engineering, having authored 19 papers that have together received 311 indexed citations. Recurring topics across this work include Insect-Plant Interactions and Control (6 papers), Radiology practices and education (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), COVID-19 diagnosis using AI (3 papers), Agronomic Practices and Intercropping Systems (2 papers), Artificial Intelligence in Healthcare and Education (2 papers), Advanced X-ray and CT Imaging (2 papers) and Plant Virus Research Studies (2 papers). The work is most often cited by research in Health Informatics (28 citations), Insect Science (122 citations), Behavioral Neuroscience (13 citations), Ecology, Evolution, Behavior and Systematics (67 citations) and Radiology, Nuclear Medicine and Imaging (75 citations). Michael Milne has collaborated with scholars based in Australia, New Zealand and Thailand. Frequent co-authors include Gimme H. Walter, G. H. Walter, J. R. Milne, Andrea Kwakowsky, Quinlan D. Buchlak, Nazanin Esmaili, Jarrel Seah, Catherine M Jones, Henry J. Waldvogel and Richard L. M. Faull. Their work appears in journals such as BMJ Open, Journal of Insect Behavior, Endocrinology, Development and Diversity and Distributions.

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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