Jonathan Mayer

7 papers receiving 208 citations

Jonathan Mayer's Hit Papers

SMOTE vs. SMOTEENN: A Study on the Performance of Resampling Algorithms for Addressing Class Imbalance in Regression Models 2025 · 25 citations
250+1Years since publication50100150

Peers

Jonathan Mayer
Comparison fields: 5 of 81
  • Health Informatics 80
  • Health Information Management 23
  • Radiology, Nuclear Medicine and Imaging 34
  • Artificial Intelligence 44
  • Family Practice 2
Replace Molly Bekbolatova with:
Molly Bekbolatova United States
Mohammad Reza Afrash Iran
Songxiang Liu China
Eva Weicken Germany
Shirly Wang United States
Pranjal Kumar Bora India
Hajira Fatima Pakistan
Zhouyu Guan China
Ciro Mennella Italy
Zongming Zhang China
Jonathan Mayer relative to Molly Bekbolatova United States Molly Bekbolatova's profile →
Citations per field
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Molly Bekbolatova · 1×
Citations per year

Countries citing papers authored by Jonathan Mayer

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan Mayer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 9 scholars most cited alongside Jonathan Mayer, 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 Jonathan Mayer Line = papers co-authored together Jonathan Mayer links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1
Transformative Potential of AI in Healthcare: Definitions, Applications, and Navigating the Ethical Landscape and Public Perspectives
Hit paper breakdown →
2024189
2
SMOTE vs. SMOTEENN: A Study on the Performance of Resampling Algorithms for Addressing Class Imbalance in Regression Models
Hit paper breakdown →
202525
3 20243
4 20242
5 20231
6 20241
7 20241
8 20240
9 20240
10 20240
11 20250

About Jonathan Mayer

Jonathan Mayer is a scholar working on Surgery, Computer Vision and Pattern Recognition, Artificial Intelligence, Biomedical Engineering and Neurology, having authored 11 papers that have together received 222 indexed citations. Recurring topics across this work include Healthcare Technology and Patient Monitoring (3 papers), Context-Aware Activity Recognition Systems (3 papers), Non-Invasive Vital Sign Monitoring (3 papers), Brain Tumor Detection and Classification (2 papers), AI in cancer detection (2 papers), Imbalanced Data Classification Techniques (1 paper), Artificial Intelligence in Healthcare (1 paper) and Electricity Theft Detection Techniques (1 paper). The work is most often cited by research in Health Informatics (80 citations), Health Information Management (23 citations), Radiology, Nuclear Medicine and Imaging (34 citations), Artificial Intelligence (44 citations) and Family Practice (2 citations). Jonathan Mayer has collaborated with scholars based in United States, Sint Maarten and Singapore. Frequent co-authors include Milan Toma, Molly Bekbolatova, Chi Wei Ong, Jawad Ahmad, Paramvir Singh, Rosalyn Chan-Akeley, Hallie Zwibel, Paul Joseph and Husnain Mansoor Ali. Their work appears in journals such as Applied Sciences, International Journal for Numerical Methods in Biomedical Engineering, Brain Sciences, Algorithms and Healthcare.

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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