Ravi K. Samala

4.0k citations
80 papers · 2.6k indexed · 1 hit paper · h-index 23
Topics
AI in cancer detection (36 papers)Radiomics and Machine Learning in Medical Imaging (34 papers)Digital Radiography and Breast Imaging (26 papers)
Journals
SHILAP Revista de lepidopterologíaScientific ReportsIEEE Transactions on Medical Imaging

In The Last Decade

Ravi K. Samala

76 papers receiving 2.5k citations

Hit Papers

Deep Learning in Medical Image Analysis20202026202220242020100200300400

Peers

Ravi K. Samala
Comparison fields: 5 of 147
  • Radiology, Nuclear Medicine and Imaging 1.6k
  • Artificial Intelligence 1.4k
  • Pulmonary and Respiratory Medicine 600
  • Computer Vision and Pattern Recognition 382
  • Biomedical Engineering 361
Replace Panagiotis Korfiatis with:
Panagiotis Korfiatis United States
Albert Gubern‐Mérida Netherlands
H. Kenny United States
Zeynettin Akkus United States
Yutong Xie China
Ashirbani Saha Canada
June‐Goo Lee South Korea
Adrien Depeursinge Switzerland
Yuchen Qiu United States
Ken Chang United States
Ravi K. Samala relative to Panagiotis Korfiatis United States Panagiotis Korfiatis's profile →
Citations per field
00.5×1.5×1.8×
Panagiotis Korfiatis · 1×
Citations per year

Countries citing papers authored by Ravi K. Samala

Since Specialization
Citations

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

Fields of papers citing papers by Ravi K. Samala

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ravi K. Samala. 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 Ravi K. Samala. The network helps show where Ravi K. Samala may publish in the future.

Co-authorship network of co-authors of Ravi K. Samala

This figure shows the co-authorship network connecting the top 25 collaborators of Ravi K. Samala. A scholar is included among the top collaborators of Ravi K. Samala 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 Ravi K. Samala. Ravi K. Samala 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
#WorkIndexed citations
1 1
2 0
3 2
4 77
5 1
6 16
7 1
8 2
9 14
10 2
11 17
12 1
13 13
14 76
15 48
16 156
17 210
18 23
19 28
20 22

About Ravi K. Samala

Ravi K. Samala is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 80 papers that have together received 2.6k indexed citations. Recurring topics across this work include AI in cancer detection (36 papers), Radiomics and Machine Learning in Medical Imaging (34 papers) and Digital Radiography and Breast Imaging (26 papers). The work is most often cited by research in Health Informatics (267 citations), Radiology, Nuclear Medicine and Imaging (1.6k citations) and Artificial Intelligence (1.4k citations). Ravi K. Samala has collaborated with scholars based in United States, China and Bulgaria. Frequent co-authors include Heang‐Ping Chan, Lubomir M. Hadjiiski, H. Kenny, Mark A. Helvie, Chuan Zhou, Caleb Richter, Jun Wei, Elaine M. Caoili, Richard H. Cohan and Yao Lu. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Transactions on Medical Imaging.

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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