David J. Dittman
- Artificial Intelligence top 5%
- Molecular Biology
- Information Systems top 5%
- Computer Vision and Pattern Recognition top 10%
- Health Information Management top 5%
- Co-authors
- Taghi M. KhoshgoftaarAmri NapolitanoRandall WaldJoseph D. PrusaJason Van HulseHuanjing WangAndrew G. RothShantel Olivares
- Topics
- Gene expression and cancer classification (25 papers)Machine Learning and Data Classification (16 papers)Imbalanced Data Classification Techniques (15 papers)
- Journals
- The American Journal of Surgical PathologyActa Neuropathologica CommunicationsJournal of Cutaneous Pathology
- Partner nations
- United States
In The Last Decade
David J. Dittman
37 papers receiving 600 citations
Peers
Comparison fields: 5 of 102
- Artificial Intelligence 422
- Molecular Biology 197
- Information Systems 137
- Computer Vision and Pattern Recognition 108
- Health Information Management 40
Countries citing papers authored by David J. Dittman
This map shows the geographic impact of David J. Dittman'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 David J. Dittman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David J. Dittman more than expected).
Fields of papers citing papers by David J. Dittman
This network shows the impact of papers produced by David J. Dittman. 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 David J. Dittman. The network helps show where David J. Dittman may publish in the future.
Co-authorship network of co-authors of David J. Dittman
This figure shows the co-authorship network connecting the top 25 collaborators of David J. Dittman. A scholar is included among the top collaborators of David J. Dittman 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 David J. Dittman. David J. Dittman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | Selecting the Appropriate Ensemble Learning Approach for Balanced Bioinformatics Data | 5 |
| 4 | Impact of Feature Selection Techniques for Tweet Sentiment Classification. | 38 |
| 5 | 104 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 32 | |
| 9 | Comparison of Data Sampling Approaches for Imbalanced Bioinformatics Data | 29 |
| 10 | 5 | |
| 11 | 3 | |
| 12 | 11 | |
| 13 | Ensemble Gene Selection Versus Single Gene Selection: Which Is Better? | 3 |
| 14 | Classification Performance of Rank Aggregation Techniques for Ensemble Gene Selection. | 12 |
| 15 | 87 | |
| 16 | 29 | |
| 17 | 4 | |
| 18 | 33 | |
| 19 | 19 | |
| 20 | 42 |
About David J. Dittman
David J. Dittman is a scholar working on Artificial Intelligence, Information Systems and Molecular Biology, having authored 38 papers that have together received 612 indexed citations. Recurring topics across this work include Gene expression and cancer classification (25 papers), Machine Learning and Data Classification (16 papers) and Imbalanced Data Classification Techniques (15 papers). The work is most often cited by research in Artificial Intelligence (422 citations), Health Information Management (40 citations) and Information Systems (137 citations). David J. Dittman has collaborated with scholars based in United States. Frequent co-authors include Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, Joseph D. Prusa, Jason Van Hulse, Huanjing Wang, Andrew G. Roth, Shantel Olivares, Lawrence J. Jennings and Klaus J. Busam. Their work appears in journals such as The American Journal of Surgical Pathology, Acta Neuropathologica Communications and Journal of Cutaneous Pathology.
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.