Aaron N. Richter
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- Artificial Intelligence in Healthcare 2
- Information Systems top 2%
- Cloud Computing and Resource Management 2
- Health Informatics top 10%
- Artificial Intelligence top 5%
- AI in cancer detection 7
- Imbalanced Data Classification Techniques 5
- Machine Learning and Data Classification 4
- Machine Learning in Healthcare 3
- Data Stream Mining Techniques 2
- Management Information Systems top 10%
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- Cutaneous Melanoma Detection and Management 5
- Co-authors
- Taghi M. KhoshgoftaarTawfiq HasaninMike CrawfordJoseph D. PrusaRichard A. BauderMatthew HerlandJan BenickBernd Steinhauser
- Journals
- Computers in Biology and Medicine (1 paper)Artificial Intelligence in Medicine (1 paper)Journal Of Big Data (2 papers)
- Partner nations
- United States
In The Last Decade
Aaron N. Richter
16 papers receiving 768 citations
Hit Papers
Peers
Comparison fields: 5 of 120
- Health Information Management 73
- Information Systems 336
- Health Informatics 19
- Artificial Intelligence 449
- Management Information Systems 81
Countries citing papers authored by Aaron N. Richter
This map shows the geographic impact of Aaron N. Richter'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 Aaron N. Richter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aaron N. Richter more than expected).
Fields of papers citing papers by Aaron N. Richter
This network shows the impact of papers produced by Aaron N. Richter. 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 Aaron N. Richter. The network helps show where Aaron N. Richter may publish in the future.
Co-authorship network
The 20 scholars most cited alongside Aaron N. Richter, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 11 | |
| 2 | 2019 | 3 | |
| 3 | 2019 | 19 | |
| 4 | 2019 | 2 | |
| 5 | 2019 | 21 | |
| 6 | 2019 | 4 | |
| 7 | 2018 | 107 | |
| 8 | 2018 | 7 | |
| 9 | 2018 | 4 | |
| 10 | 2017 | 10 | |
| 11 | 2017 | 6 | |
| 12 | 2016 | 2 | |
| 13 | 2016 | 45 | |
| 14 | Survey of review spam detection using machine learning techniquesbreakdown → | 2015 | 295 |
| 15 | A survey of open source tools for machine learning with big data in the Hadoop ecosystembreakdown → | 2015 | 259 |
| 16 | 2015 | 25 |
About Aaron N. Richter
Aaron N. Richter is a scholar working on Health Information Management, Artificial Intelligence and Biophysics, having authored 16 papers that have together received 820 indexed citations. Recurring topics across this work include AI in cancer detection (7 papers), Imbalanced Data Classification Techniques (5 papers), Cutaneous Melanoma Detection and Management (5 papers), Machine Learning and Data Classification (4 papers), Machine Learning in Healthcare (3 papers), Artificial Intelligence in Healthcare (2 papers), Cloud Computing and Resource Management (2 papers) and Data Stream Mining Techniques (2 papers). The work is most often cited by research in Health Information Management (73 citations), Information Systems (336 citations) and Health Informatics (19 citations). Aaron N. Richter has collaborated with scholars based in United States. Frequent co-authors include Taghi M. Khoshgoftaar, Tawfiq Hasanin, Mike Crawford, Joseph D. Prusa, Richard A. Bauder, Matthew Herland, Jan Benick, Bernd Steinhauser, Martin Bivour and J. Rentsch. Their work appears in journals such as Computers in Biology and Medicine, Artificial Intelligence in Medicine and Journal Of Big Data.
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.