Evan Minty

19 papers receiving 312 citations

Peers

Evan Minty
Comparison fields: 5 of 85
  • Health Information Management 44
  • Health Informatics 12
  • Artificial Intelligence 84
  • Radiology, Nuclear Medicine and Imaging 48
  • Toxicology 6
Replace Marc Heimann with:
Marc Heimann Germany
Andrew J. Zimolzak United States
Scott Halgrim United States
Peter Speltz United States
Preethi Raghavan United States
Farah E. Shamout United Arab Emirates
Alireza Atashi Iran
Piotr Jaroslaw Chmura Denmark
Fateme Moghbeli Iran
Fanis Kalatzis Greece
Evan Minty relative to Marc Heimann Germany Marc Heimann's profile →
Citations per field
00.5×1.5×
Marc Heimann · 1×
Citations per year

Countries citing papers authored by Evan Minty

Since Specialization
Citations

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

Fields of papers citing papers by Evan Minty

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016104
2 201448
3 200942
4 202023
5 201817
6 202012
7 202312
8 201310
9 20219
10 20228
11 20246
12 20166
13 20215
14 20184
15
Characterizing database granularity using SNOMED-CT hierarchy.
20204
16
Predicting patients who are likely to develop Lupus Nephritis of those newly diagnosed with Systemic Lupus Erythematosus.
20223
17 20232
18 20182
19
Visualization of Publication Timelines using 4K Monitors.
20141
20 20250

About Evan Minty

Evan Minty is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology, Health Information Management, Epidemiology and Artificial Intelligence, having authored 22 papers that have together received 318 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (3 papers), Medical Coding and Health Information (3 papers), Diabetic Foot Ulcer Assessment and Management (3 papers), Vaccine Coverage and Hesitancy (2 papers), Machine Learning in Healthcare (2 papers), Influenza Virus Research Studies (2 papers), Acute Kidney Injury Research (2 papers) and AI in cancer detection (2 papers). The work is most often cited by research in Health Information Management (44 citations), Health Informatics (12 citations), Artificial Intelligence (84 citations), Radiology, Nuclear Medicine and Imaging (48 citations) and Toxicology (6 citations). Evan Minty has collaborated with scholars based in Canada, United States and Australia. Frequent co-authors include Timothy E. Sweeney, Nigam H. Shah, Tiffany I. Leung, Juan M. Banda, Vibhu Agarwal, Veena Goel, Tanya Podchiyska, Alex L. MacKay, Thorarin A. Bjarnason and Cornelia Laule. Their work appears in journals such as Journal of the American Medical Informatics Association, Frontiers in Pharmacology, Sensors, JMIR mhealth and uhealth and BMC Medical Informatics and Decision Making.

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