Renuka Uppaluri

1.2k citations
15 papers · 918 indexed · h-index 9

Renuka Uppaluri

15 papers receiving 884 citations

Peers

Renuka Uppaluri
Comparison fields: 5 of 85
  • Pulmonary and Respiratory Medicine 673
  • Radiology, Nuclear Medicine and Imaging 270
  • Physiology 137
  • Critical Care and Intensive Care Medicine 26
  • Atomic and Molecular Physics, and Optics 105
Replace Hyun J. Kim with:
Hyun J. Kim United States
Saher Burhan Shaker Denmark
Samuel Y. Ash United States
Sushravya Raghunath United States
Pechin Lo Denmark
Puneet Sharma United States
Lucio Calandriello Italy
J W Gurney United States
Mathieu Salaün France
Stephen Hobbs United States
Renuka Uppaluri relative to Hyun J. Kim United States Hyun J. Kim's profile →
Citations per field
00.5×2.7×
Hyun J. Kim · 1×
Citations per year

Countries citing papers authored by Renuka Uppaluri

Since Specialization
Citations

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

Fields of papers citing papers by Renuka Uppaluri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Renuka Uppaluri. 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 Renuka Uppaluri. The network helps show where Renuka Uppaluri may publish in the future.

Co-authorship network

The 20 scholars most cited alongside Renuka Uppaluri, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Renuka Uppaluri Line = papers co-authored together Renuka Uppaluri links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 200725
2 200612
3 20043
4 200414
5 20024
6 20029
7 1999179
8 1999417
9 19994
10
A Quantitative Study Using the Adaptive Multiple Feature Method
19991
11 19988
12 19985
13 1997213
14 19968
15 199516

About Renuka Uppaluri

Renuka Uppaluri is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Artificial Intelligence, having authored 15 papers that have together received 918 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (4 papers), Radiation Dose and Imaging (4 papers), Digital Radiography and Breast Imaging (4 papers), Medical Imaging Techniques and Applications (4 papers), Advanced X-ray and CT Imaging (4 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (3 papers), Lung Cancer Diagnosis and Treatment (3 papers) and Chronic Obstructive Pulmonary Disease (COPD) Research (3 papers). The work is most often cited by research in Pulmonary and Respiratory Medicine (673 citations), Radiology, Nuclear Medicine and Imaging (270 citations) and Physiology (137 citations). Renuka Uppaluri has collaborated with scholars based in United States and Germany. Frequent co-authors include Eric A. Hoffman, Geoffrey McLennan, Milan Sonka, Gary W. Hunninghake, Theophano Mitsa, Patrick G. Hartley, Gopal Avinash, Baojun Li, Jeffrey R. Galvin and Timothy W. Deller. Their work appears in journals such as American Journal of Respiratory and Critical Care Medicine, Academic Radiology and Pediatric Radiology.

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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