Samuel G. Armato
- Radiology, Nuclear Medicine and Imaging top 0.2%
- Pulmonary and Respiratory Medicine top 0.5%
- Artificial Intelligence top 1%
- Biomedical Engineering top 5%
- Computer Vision and Pattern Recognition top 2%
- Co-authors
- Heber MacMahonMaryellen L. GigerKunio DoiFeng LiWilliam F. SensakovicShusuke SoneHedy L. KindlerAnna K. Nowak
- Topics
- Radiomics and Machine Learning in Medical Imaging (97 papers)Lung Cancer Diagnosis and Treatment (56 papers)Occupational and environmental lung diseases (49 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingPulmonary and Respiratory MedicineHealth Informatics
- Partner nations
- United StatesAustraliaUnited Kingdom
In The Last Decade
Samuel G. Armato
171 papers receiving 5.0k citations
Hit Papers
Peers
Comparison fields: 5 of 130
- Radiology, Nuclear Medicine and Imaging 3.6k
- Pulmonary and Respiratory Medicine 3.5k
- Artificial Intelligence 943
- Biomedical Engineering 697
- Computer Vision and Pattern Recognition 572
Countries citing papers authored by Samuel G. Armato
This map shows the geographic impact of Samuel G. Armato'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 Samuel G. Armato with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Samuel G. Armato more than expected).
Fields of papers citing papers by Samuel G. Armato
This network shows the impact of papers produced by Samuel G. Armato. 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 Samuel G. Armato. The network helps show where Samuel G. Armato may publish in the future.
Co-authorship network of co-authors of Samuel G. Armato
This figure shows the co-authorship network connecting the top 25 collaborators of Samuel G. Armato. A scholar is included among the top collaborators of Samuel G. Armato 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 Samuel G. Armato. Samuel G. Armato 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 | 1 | |
| 6 | 5 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | Treatment of Malignant Pleural Mesothelioma: American Society of Clinical Oncology Clinical Practice Guidelinebreakdown → | 260 |
| 10 | 3 | |
| 11 | An Integrated Database and Smart Search Tool for Medical Knowledge Extraction from Radiology Teaching Files | 6 |
| 12 | 2 | |
| 13 | 13 | |
| 14 | 22 | |
| 15 | 28 | |
| 16 | 7 | |
| 17 | 3 | |
| 18 | 55 | |
| 19 | 69 | |
| 20 | 64 |
About Samuel G. Armato
Samuel G. Armato is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Health Informatics, having authored 176 papers that have together received 5.2k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (97 papers), Lung Cancer Diagnosis and Treatment (56 papers) and Occupational and environmental lung diseases (49 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (3.6k citations), Pulmonary and Respiratory Medicine (3.5k citations) and Health Informatics (74 citations). Samuel G. Armato has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Heber MacMahon, Maryellen L. Giger, Kunio Doi, Feng Li, William F. Sensakovic, Shusuke Sone, Hedy L. Kindler, Heber MacMahon, Anna K. Nowak and Hania Al‐Hallaq. Their work appears in journals such as Journal of Clinical Oncology, Radiology and CHEST Journal.
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.