Lauren Pantalone
- Radiology, Nuclear Medicine and Imaging top 5%
- Artificial Intelligence top 5%
- Pulmonary and Respiratory Medicine top 10%
- Oncology
- Cancer Research
- Co-authors
- Despina KontosEmily F. ConantAimilia GastouniotiM. Ani HsiehEric A. CohenAnne Marie McCarthyBrad M. KellerMarie Synnestvedt
- Topics
- Radiomics and Machine Learning in Medical Imaging (27 papers)Digital Radiography and Breast Imaging (24 papers)AI in cancer detection (22 papers)
- Partner nations
- United StatesSwedenBelarus
In The Last Decade
Lauren Pantalone
39 papers receiving 505 citations
Peers
Comparison fields: 5 of 49
- Radiology, Nuclear Medicine and Imaging 335
- Artificial Intelligence 323
- Pulmonary and Respiratory Medicine 259
- Oncology 161
- Cancer Research 65
Countries citing papers authored by Lauren Pantalone
This map shows the geographic impact of Lauren Pantalone'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 Lauren Pantalone with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lauren Pantalone more than expected).
Fields of papers citing papers by Lauren Pantalone
This network shows the impact of papers produced by Lauren Pantalone. 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 Lauren Pantalone. The network helps show where Lauren Pantalone may publish in the future.
Co-authorship network of co-authors of Lauren Pantalone
This figure shows the co-authorship network connecting the top 25 collaborators of Lauren Pantalone. A scholar is included among the top collaborators of Lauren Pantalone 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 Lauren Pantalone. Lauren Pantalone is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 5 | |
| 8 | 1 | |
| 9 | 10 | |
| 10 | 21 | |
| 11 | 41 | |
| 12 | 2 | |
| 13 | 54 | |
| 14 | 30 | |
| 15 | 56 | |
| 16 | 12 | |
| 17 | 31 | |
| 18 | 13 | |
| 19 | 24 | |
| 20 | 69 |
About Lauren Pantalone
Lauren Pantalone is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Artificial Intelligence, having authored 39 papers that have together received 510 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (27 papers), Digital Radiography and Breast Imaging (24 papers) and AI in cancer detection (22 papers). The work is most often cited by research in Health Informatics (21 citations), Radiology, Nuclear Medicine and Imaging (335 citations) and Artificial Intelligence (323 citations). Lauren Pantalone has collaborated with scholars based in United States, Sweden and Belarus. Frequent co-authors include Despina Kontos, Emily F. Conant, Aimilia Gastounioti, M. Ani Hsieh, Eric A. Cohen, Anne Marie McCarthy, Brad M. Keller, Marie Synnestvedt, Andrew Oustimov and Stacey J. Winham. Their work appears in journals such as Journal of Clinical Oncology, JNCI Journal of the National Cancer Institute and Cancer Research.
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.