Nitin Singhal

726 citations
29 papers · 365 indexed · h-index 10

Impact in

Papers in

Nitin Singhal

27 papers receiving 336 citations

Peers

Nitin Singhal
Comparison fields: 5 of 75
  • Health Informatics 15
  • Computer Vision and Pattern Recognition 192
  • Computer Graphics and Computer-Aided Design 16
  • Hardware and Architecture 28
  • Radiology, Nuclear Medicine and Imaging 75
Replace Peter de With with:
Peter de With Netherlands
Guadalupe Canahuate United States
Luyang Luo Hong Kong
Hyunseok Seo South Korea
S.L. Lou United States
Xintong Li China
Guangyuan Li China
Nicolas Normand France
Deepak Gupta India
Nitin Singhal relative to Peter de With Netherlands Peter de With's profile →
Citations per field
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Citations per year

Countries citing papers authored by Nitin Singhal

Since Specialization
Citations

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

Fields of papers citing papers by Nitin Singhal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010101
2 202247
3 200939
4 201637
5 201033
6 202017
7 201713
8 201211
9 200710
10 20209
11 20106
12 20226
13 20095
14 20105
15 20114
16 20184
17 20163
18 20133
19 20242
20 20212

About Nitin Singhal

Nitin Singhal is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Molecular Biology, having authored 29 papers that have together received 365 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (8 papers), AI in cancer detection (7 papers), Advanced Vision and Imaging (7 papers), Digital Imaging for Blood Diseases (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Prostate Cancer Diagnosis and Treatment (3 papers), Robotics and Sensor-Based Localization (2 papers) and Advanced Steganography and Watermarking Techniques (2 papers). The work is most often cited by research in Health Informatics (15 citations), Computer Vision and Pattern Recognition (192 citations), Computer Graphics and Computer-Aided Design (16 citations), Hardware and Architecture (28 citations) and Radiology, Nuclear Medicine and Imaging (75 citations). Nitin Singhal has collaborated with scholars based in South Korea, India and United States. Frequent co-authors include Sungdae Cho, In Kyu Park, Chris Kim, In Kyu Park, Sang-Uk Lee, Young-Yoon Lee, Chang‐Su Kim, Vivek Vaidya, Hariharan Ravishankar and Mahesh Desai. Their work appears in journals such as JNCI Journal of the National Cancer Institute, Scientific Reports, IEEE Transactions on Parallel and Distributed Systems, Ultrasound in Obstetrics and Gynecology and Multimedia Tools and Applications.

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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