Kim L. Sandler
- Pulmonary and Respiratory Medicine top 5%
- Oncology top 10%
- Radiology, Nuclear Medicine and Imaging top 5%
- Otorhinolaryngology top 5%
- Cardiology and Cardiovascular Medicine
- Co-authors
- Melinda C. AldrichEric L. GroganDiane N. HaddadSarah MercaldoWilliam J. BlotJeffrey D. BlumeM. Patricia RiveraLouise M. Henderson
- Topics
- Lung Cancer Diagnosis and Treatment (35 papers)Radiomics and Machine Learning in Medical Imaging (22 papers)Global Cancer Incidence and Screening (13 papers)
- Partner nations
- United StatesIndiaFrance
In The Last Decade
Kim L. Sandler
46 papers receiving 810 citations
Peers
Comparison fields: 5 of 82
- Pulmonary and Respiratory Medicine 566
- Oncology 262
- Radiology, Nuclear Medicine and Imaging 253
- Otorhinolaryngology 81
- Cardiology and Cardiovascular Medicine 59
Countries citing papers authored by Kim L. Sandler
This map shows the geographic impact of Kim L. Sandler'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 Kim L. Sandler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kim L. Sandler more than expected).
Fields of papers citing papers by Kim L. Sandler
This network shows the impact of papers produced by Kim L. Sandler. 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 Kim L. Sandler. The network helps show where Kim L. Sandler may publish in the future.
Co-authorship network of co-authors of Kim L. Sandler
This figure shows the co-authorship network connecting the top 25 collaborators of Kim L. Sandler. A scholar is included among the top collaborators of Kim L. Sandler 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 Kim L. Sandler. Kim L. Sandler is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 6 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 33 | |
| 6 | 11 | |
| 7 | 8 | |
| 8 | 9 | |
| 9 | 0 | |
| 10 | 9 | |
| 11 | 7 | |
| 12 | 6 | |
| 13 | 11 | |
| 14 | 12 | |
| 15 | 6 | |
| 16 | 128 | |
| 17 | 5 | |
| 18 | 4 | |
| 19 | 38 | |
| 20 | 0 |
About Kim L. Sandler
Kim L. Sandler is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Otorhinolaryngology, having authored 56 papers that have together received 832 indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (35 papers), Radiomics and Machine Learning in Medical Imaging (22 papers) and Global Cancer Incidence and Screening (13 papers). The work is most often cited by research in Otorhinolaryngology (81 citations), Pulmonary and Respiratory Medicine (566 citations) and Health Informatics (18 citations). Kim L. Sandler has collaborated with scholars based in United States, India and France. Frequent co-authors include Melinda C. Aldrich, Eric L. Grogan, Diane N. Haddad, Sarah Mercaldo, William J. Blot, Jeffrey D. Blume, M. Patricia Rivera, Louise M. Henderson, Pierre P. Massion and Bennett A. Landman. Their work appears in journals such as Circulation, American Journal of Respiratory and Critical Care Medicine and Cancer.
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.