Aaron N. Richter

1.3k total citations · 2 hit papers
16 papers, 820 citations indexed

About

Aaron N. Richter is a scholar working on Artificial Intelligence, Oncology and Health Information Management. According to data from OpenAlex, Aaron N. Richter has authored 16 papers receiving a total of 820 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 5 papers in Oncology and 3 papers in Health Information Management. Recurrent topics in Aaron N. Richter's work include AI in cancer detection (7 papers), Imbalanced Data Classification Techniques (5 papers) and Cutaneous Melanoma Detection and Management (5 papers). Aaron N. Richter is often cited by papers focused on AI in cancer detection (7 papers), Imbalanced Data Classification Techniques (5 papers) and Cutaneous Melanoma Detection and Management (5 papers). Aaron N. Richter collaborates with scholars based in United States. Aaron N. Richter's 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 and has published in prestigious journals such as Computers in Biology and Medicine, Artificial Intelligence in Medicine and Journal Of Big Data.

In The Last Decade

Aaron N. Richter

16 papers receiving 768 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Survey of review spam detection using machine learning techniques

2015 295 citations Mike Crawford, Taghi M. Khoshgoftaar et al. Journal Of Big Data profile →
A survey of open source tools for machine learning with big data in the Hadoop ecosystem

2015 259 citations Taghi M. Khoshgoftaar, Aaron N. Richter et al. Journal Of Big Data profile →

Peers

Aaron N. Richter

AI

IS

CNC

SPS

SP

Karim Abouelmehdi Morocco

Arnold Adimabua Ojugo Nigeria

Tehmina Amjad Pakistan

Zon‐Yin Shae United States

Adebayọ Olusọla Adetunmbi Nigeria

Hoda Mashayekhi Iran

Manasi Gyanchandani India

Fabio Stella Italy

A.K. Majumdar India

Qusai Y. Shambour Jordan

Karim Abouelmehdi Morocco

Aaron N. Richter

285 ×0.6

AI

263 ×0.8

IS

164 ×0.9

CNC

86 ×0.9

SPS

41 ×0.5

SP

Citations per year, relative to Aaron N. Richter Aaron N. Richter (= 1×) peers Karim Abouelmehdi

Countries citing papers authored by Aaron N. Richter

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Aaron N. Richter

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

All Works

Sort: Min cites: Since: Top N: Style:

16 of 16 papers shown

1.

Richter, Aaron N. & Taghi M. Khoshgoftaar. (2020). Sample size determination for biomedical big data with limited labels. Network Modeling Analysis in Health Informatics and Bioinformatics. 9(1). 11 indexed citations

2.

Richter, Aaron N. & Taghi M. Khoshgoftaar. (2019). Melanoma risk modeling from limited positive samples. Network Modeling Analysis in Health Informatics and Bioinformatics. 8(1). 3 indexed citations

3.

Richter, Aaron N. & Taghi M. Khoshgoftaar. (2019). Efficient learning from big data for cancer risk modeling: A case study with melanoma. Computers in Biology and Medicine. 110. 29–39. 19 indexed citations

4.

Richter, Aaron N. & Taghi M. Khoshgoftaar. (2019). Approximating Learning Curves for Imbalanced Big Data with Limited Labels. 237–242. 2 indexed citations

5.

Feldmann, Frank, Tobias Fellmeth, Bernd Steinhauser, et al.. (2019). Large Area TOPCon Cells Realized by a PECVD Tube Process. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 304–308. 21 indexed citations

6.

Richter, Aaron N. & Taghi M. Khoshgoftaar. (2019). Learning Curve Estimation with Large Imbalanced Datasets. 763–768. 4 indexed citations

7.

Richter, Aaron N. & Taghi M. Khoshgoftaar. (2018). A review of statistical and machine learning methods for modeling cancer risk using structured clinical data. Artificial Intelligence in Medicine. 90. 1–14. 107 indexed citations

8.

Richter, Aaron N. & Taghi M. Khoshgoftaar. (2018). Melanoma Risk Prediction with Structured Electronic Health Records. 194–199. 7 indexed citations

9.

Richter, Aaron N. & Taghi M. Khoshgoftaar. (2018). Building and Interpreting Risk Models from Imbalanced Clinical Data. 4 indexed citations

10.

Richter, Aaron N. & Taghi M. Khoshgoftaar. (2017). Modernizing Analytics for Melanoma with a Large-Scale Research Dataset. 551–558. 10 indexed citations

11.

Richter, Aaron N. & Taghi M. Khoshgoftaar. (2017). Predicting sentinel node status in melanoma from a real-world EHR dataset. 1872–1878. 6 indexed citations

12.

Richter, Aaron N. & Taghi M. Khoshgoftaar. (2016). Predicting Cancer Relapse with Clinical Data: A Survey of Current Techniques. 369–376. 2 indexed citations

13.

Bauder, Richard A., Taghi M. Khoshgoftaar, Aaron N. Richter, & Matthew Herland. (2016). Predicting Medical Provider Specialties to Detect Anomalous Insurance Claims. 784–790. 45 indexed citations

14.

Crawford, Mike, et al.. (2015). Survey of review spam detection using machine learning techniques. Journal Of Big Data. 2(1). 295 indexed citations breakdown →

15.

Khoshgoftaar, Taghi M., et al.. (2015). A survey of open source tools for machine learning with big data in the Hadoop ecosystem. Journal Of Big Data. 2(1). 259 indexed citations breakdown →

16.

Richter, Aaron N., et al.. (2015). A Multi-dimensional Comparison of Toolkits for Machine Learning with Big Data. 1–8. 25 indexed citations

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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