Sushravya Raghunath

1.8k citations
27 papers · 822 indexed · h-index 12
Topics
Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (7 papers)Radiomics and Machine Learning in Medical Imaging (6 papers)Lung Cancer Diagnosis and Treatment (6 papers)

In The Last Decade

Sushravya Raghunath

23 papers receiving 810 citations

Peers

Sushravya Raghunath
Comparison fields: 5 of 63
  • Pulmonary and Respiratory Medicine 605
  • Radiology, Nuclear Medicine and Imaging 283
  • Physiology 131
  • Cardiology and Cardiovascular Medicine 107
  • Biomedical Engineering 89
Replace Lucio Calandriello with:
Lucio Calandriello Italy
Stephan Altmayer Brazil
Simon Walsh United Kingdom
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Sushravya Raghunath relative to Lucio Calandriello Italy Lucio Calandriello's profile →
Citations per field
00.5×3.5×
Lucio Calandriello · 1×
Citations per year

Countries citing papers authored by Sushravya Raghunath

Since Specialization
Citations

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

Fields of papers citing papers by Sushravya Raghunath

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sushravya Raghunath

This figure shows the co-authorship network connecting the top 25 collaborators of Sushravya Raghunath. A scholar is included among the top collaborators of Sushravya Raghunath 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 Sushravya Raghunath. Sushravya Raghunath 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
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Abstract 14425: Deep Neural Networks Can Predict 1-Year Mortality Directly From ECG Signal, Even When Clinically Interpreted as Normal
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A deep neural network predicts survival after heart imaging better than cardiologists.
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Validation of CALIPER (Computer-aided lung informatics for pathology evaluation and rating) for the non-invasive assessment of pulmonary nodules of the adenocarcinoma spectrum
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About Sushravya Raghunath

Sushravya Raghunath is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Cardiology and Cardiovascular Medicine, having authored 27 papers that have together received 822 indexed citations. Recurring topics across this work include Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (7 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and Lung Cancer Diagnosis and Treatment (6 papers). The work is most often cited by research in Pulmonary and Respiratory Medicine (605 citations), Health Informatics (18 citations) and Radiology, Nuclear Medicine and Imaging (283 citations). Sushravya Raghunath has collaborated with scholars based in United States, Czechia and Italy. Frequent co-authors include Brian J. Bartholmai, Ronald A. Karwoski, Fabien Maldonado, Richard A. Robb, Srinivasan Rajagopalan, Teng Moua, Paul Decker, Thomas E. Hartman, Srinivasan Rajagopalan and Jay H. Ryu. Their work appears in journals such as Circulation, PLoS ONE and American Journal of Respiratory and Critical Care Medicine.

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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