Deepa Sheth

926 citations
22 papers · 497 · h-index 10

Impact in

Papers in

Deepa Sheth

19 papers receiving 490 citations

Peers

Deepa Sheth
Comparison fields: 5 of 54
  • Health Informatics 35
  • Radiology, Nuclear Medicine and Imaging 272
  • Artificial Intelligence 181
  • Neurology 25
  • Genetics 27
Replace Isaac Daimiel Naranjo with:
Isaac Daimiel Naranjo United States
Isabel Schobert Germany
Adrian Levine Canada
Adrian Ion‐Mărgineanu Belgium
Norio Shinkai Japan
Brian Hrycushko United States
Martijn P. A. Starmans Netherlands
Stefan Schulz Germany
Deepa Sheth relative to Isaac Daimiel Naranjo United States Isaac Daimiel Naranjo's profile →
Citations per field
00.5×4.6×
Isaac Daimiel Naranjo · 1×
Citations per year

Countries citing papers authored by Deepa Sheth

Since Specialization
Citations

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

Fields of papers citing papers by Deepa Sheth

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Deepa Sheth, 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 Deepa Sheth Line = papers co-authored together Deepa Sheth links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019151
2 201883
3 201979
4 201230
5 201828
6 201721
7 202019
8 201716
9 201715
10 201913
11
Circumdural decompression by posterior vertebrectomy for relief of cord compression due to metastatic disease of thoracic and lumbar spine.
19929
12 20177
13 20217
14 20205
15 20233
16 20203
17 20093
18 20183
19 20072
20 20210

About Deepa Sheth

Deepa Sheth is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Artificial Intelligence, Surgery and Genetics, having authored 22 papers that have together received 497 indexed citations. Recurring topics across this work include MRI in cancer diagnosis (9 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), AI in cancer detection (5 papers), Digital Radiography and Breast Imaging (4 papers), Medical Imaging Techniques and Applications (2 papers), Advanced MRI Techniques and Applications (2 papers), Sarcoma Diagnosis and Treatment (1 paper) and Amoebic Infections and Treatments (1 paper). The work is most often cited by research in Health Informatics (35 citations), Radiology, Nuclear Medicine and Imaging (272 citations), Artificial Intelligence (181 citations), Neurology (25 citations) and Genetics (27 citations). Deepa Sheth has collaborated with scholars based in United States, Japan and Germany. Frequent co-authors include Maryellen L. Giger, Hui Li, Hiroyuki Abé, Lan Li, Naoko Mori, Jonathan M. Lorenz, Jay Patel, Gregory S. Karczmar, Keiko Tsuchiya and David Schacht. Their work appears in journals such as Journal of Magnetic Resonance Imaging, Annals of Allergy Asthma & Immunology, American Journal of Roentgenology, British Journal of Radiology and Journal of Vascular and Interventional 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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