David B. Rosen

4.8k total citations · 2 hit papers
20 papers, 3.3k citations indexed

About

David B. Rosen is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Ophthalmology. According to data from OpenAlex, David B. Rosen has authored 20 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 8 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Ophthalmology. Recurrent topics in David B. Rosen's work include Neural Networks and Applications (8 papers), Corneal surgery and disorders (6 papers) and Corneal Surgery and Treatments (5 papers). David B. Rosen is often cited by papers focused on Neural Networks and Applications (8 papers), Corneal surgery and disorders (6 papers) and Corneal Surgery and Treatments (5 papers). David B. Rosen collaborates with scholars based in United States. David B. Rosen's co-authors include Gail A. Carpenter, Stephen Grossberg, John H. Reynolds, Philip H. Goodman, Harry Burke, Donald E. Henson, John N. Weinstein, David G. Bostwick, Jeffrey R. Marks and Frank E. Harrell and has published in prestigious journals such as Cancer, Neural Networks and Practical Radiation Oncology.

In The Last Decade

David B. Rosen

18 papers receiving 3.0k citations

Hit Papers

Fuzzy ARTMAP: A neural ne... 1991 2026 2002 2014 1992 1991 400 800 1.2k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
David B. Rosen United States 11 2.1k 731 429 316 252 20 3.3k
Tom Dietterich United States 11 2.1k 1.0× 890 1.2× 288 0.7× 238 0.8× 146 0.6× 20 3.3k
P. A. Estévez Chile 28 1.4k 0.7× 923 1.3× 243 0.6× 394 1.2× 358 1.4× 131 3.5k
Christian J. Darken United States 9 2.1k 1.0× 672 0.9× 823 1.9× 372 1.2× 258 1.0× 36 3.3k
S. Lecœuche France 20 1.5k 0.8× 855 1.2× 871 2.0× 321 1.0× 537 2.1× 73 4.1k
Jayadeva India 20 1.2k 0.6× 1.2k 1.6× 513 1.2× 160 0.5× 197 0.8× 75 2.6k
Mahesan Niranjan United Kingdom 26 1.4k 0.7× 496 0.7× 385 0.9× 397 1.3× 261 1.0× 206 2.8k
Tapani Raiko Finland 22 1.5k 0.7× 1.2k 1.6× 216 0.5× 350 1.1× 221 0.9× 61 3.2k
Alexander Binder Germany 16 3.4k 1.7× 1.2k 1.6× 200 0.5× 346 1.1× 212 0.8× 43 5.2k
Juan J. Rodríguez Spain 25 1.8k 0.9× 699 1.0× 141 0.3× 393 1.2× 281 1.1× 76 3.3k
Jim Austin United Kingdom 18 1.8k 0.9× 572 0.8× 411 1.0× 494 1.6× 207 0.8× 80 3.2k

Countries citing papers authored by David B. Rosen

Since Specialization
Citations

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

Fields of papers citing papers by David B. Rosen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David B. Rosen. 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 B. Rosen. The network helps show where David B. Rosen may publish in the future.

Co-authorship network of co-authors of David B. Rosen

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

All Works

20 of 20 papers shown
1.
Rosen, David B., et al.. (2024). Spontaneous Corneal Clearing after Descemet Membrane Rupture and Near-Total Detachment in Keratoglobus: A Case Report. Case Reports in Ophthalmology. 15(1). 189–195.
2.
Moshirfar, Majid, et al.. (2019). Comparative Analysis of LASIK Flap Diameter and its Centration Using Two Different Femtosecond Lasers.. PubMed. 8(3). 241–249. 9 indexed citations
3.
Moshirfar, Majid, et al.. (2019). Dyskeratosis Congenita and Corneal Refractive Surgery. Ophthalmology and Therapy. 8(3). 361–365. 3 indexed citations
4.
Rosen, David B., et al.. (2019). Should Patients with Hidradenitis Suppurativa Undergo LASIK?. Ophthalmology and Therapy. 8(3). 353–359. 1 indexed citations
5.
Moshirfar, Majid, et al.. (2019). Should I Get LASIK If I’m Breastfeeding?. Ophthalmology and Therapy. 8(3). 349–352. 4 indexed citations
6.
Moshirfar, Majid, et al.. (2019). Keratoconus Screening in Elementary School Children. Ophthalmology and Therapy. 8(3). 367–371. 14 indexed citations
7.
Moshirfar, Majid, et al.. (2019). Diagnosis and Management of Pseudoguttata: A Literature Review.. PubMed. 8(3). 156–162. 10 indexed citations
8.
Grant, Stephen R., Benjamin D. Smith, Shervin M. Shirvani, et al.. (2018). Provider variability in intensity modulated radiation therapy utilization among Medicare beneficiaries in the United States. Practical Radiation Oncology. 8(5). e329–e336. 8 indexed citations
9.
Rosen, David B., et al.. (2007). A Robotic Neural Net Based Visual-sensory Motor Control System that Reverse Engineers the Motor Control Functions of the Human Brain. IEEE International Conference on Neural Networks. 2629–2634.
10.
Carpenter, Gail A., et al.. (2003). Fuzzy ARTMAP: an adaptive resonance architecture for incremental learning of analog maps. 3. 309–314. 17 indexed citations
11.
Goodman, Philip H., Vassilis G. Kaburlasos, Gail A. Carpenter, et al.. (2003). Fuzzy ARTMAP neural network compared to linear discriminant analysis prediction of the length of hospital stay in patients with pneumonia. 748–753. 3 indexed citations
12.
Burke, Harry, David B. Rosen, & Philip H. Goodman. (2002). Comparing artificial neural networks to other statistical methods for medical outcome prediction. 4. 2213–2216. 21 indexed citations
13.
Carpenter, Gail A., Stephen Grossberg, & David B. Rosen. (2002). Fuzzy ART: an adaptive resonance algorithm for rapid, stable classification of analog patterns. ii. 411–416. 57 indexed citations
14.
Burke, Harry, Philip H. Goodman, David B. Rosen, et al.. (1997). Artificial neural networks improve the accuracy of cancer survival prediction. Cancer. 79(4). 857–862. 274 indexed citations
15.
Burke, Harry, David B. Rosen, & Philip H. Goodman. (1994). Comparing the prediction accuracy of artificial neural networks and other statistical models for breast cancer survival. Neural Information Processing Systems. 7. 1063–1067. 24 indexed citations
16.
Burke, Harry, et al.. (1994). Neural networks for measuring cancer outcomes. 157–159 vol.1. 4 indexed citations
17.
Carpenter, Gail A., et al.. (1992). Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps. IEEE Transactions on Neural Networks. 3(5). 698–713. 1387 indexed citations breakdown →
18.
Carpenter, Gail A., Stephen Grossberg, & David B. Rosen. (1991). Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system. Neural Networks. 4(6). 759–771. 1167 indexed citations breakdown →
19.
Carpenter, Gail A., Stephen Grossberg, & David B. Rosen. (1991). ART 2-A: An adaptive resonance algorithm for rapid category learning and recognition. Neural Networks. 4(4). 493–504. 299 indexed citations
20.
Carpenter, Gail A., Stephen Grossberg, & David B. Rosen. (1991). A Neural Network Realization of Fuzzy ART. OpenBU/Boston University Institutional Repository (Boston University). 11 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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