Prabhpreet Kaur

1.1k citations
43 papers · 501 · h-index 12

Impact in

Papers in

Prabhpreet Kaur

38 papers receiving 461 citations

Peers

Prabhpreet Kaur
Comparison fields: 5 of 95
  • Health Information Management 43
  • Neurology 73
  • Radiology, Nuclear Medicine and Imaging 185
  • Computer Vision and Pattern Recognition 158
  • Media Technology 61
Replace Alireza Norouzi with:
Alireza Norouzi Malaysia
Siti Raihanah Abdani Malaysia
Abdolvahab Ehsani Rad Malaysia
Shuyue Guan United States
Along He China
Saqib Qamar China
Xuebo Liu China
Tahir Mahmood South Korea
Liangliang Liu China
Jiho Choi South Korea
Prabhpreet Kaur relative to Alireza Norouzi Malaysia Alireza Norouzi's profile →
Citations per field
00.5×4.3×
Alireza Norouzi · 1×
Citations per year

Countries citing papers authored by Prabhpreet Kaur

Since Specialization
Citations

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

Fields of papers citing papers by Prabhpreet Kaur

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Prabhpreet Kaur, 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 Prabhpreet Kaur Line = papers co-authored together Prabhpreet Kaur links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201989
2 201782
3 201950
4 201949
5 201621
6 202221
7 201520
8 201518
9 202216
10 202114
11 201812
12 201512
13 202510
14 201410
15 20149
16 20169
17 20166
18 20215
19 20245
20 20145

About Prabhpreet Kaur

Prabhpreet Kaur is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Media Technology and Computer Networks and Communications, having authored 43 papers that have together received 501 indexed citations. Recurring topics across this work include AI in cancer detection (8 papers), Image Enhancement Techniques (6 papers), Retinal Imaging and Analysis (6 papers), Advanced Image Fusion Techniques (5 papers), Image and Signal Denoising Methods (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Digital Imaging for Blood Diseases (4 papers) and Brain Tumor Detection and Classification (4 papers). The work is most often cited by research in Health Information Management (43 citations), Neurology (73 citations), Radiology, Nuclear Medicine and Imaging (185 citations), Computer Vision and Pattern Recognition (158 citations) and Media Technology (61 citations). Prabhpreet Kaur has collaborated with scholars based in India and United States. Frequent co-authors include Parminder Kaur, Gurvinder Singh, Jaspreet Kaur, Madhusudan Astekar, Amanjot Kaur, Karandeep Singh Arora, Vinay Kumar, Simranpreet Kaur, Navneet Singh and A Tewari. Their work appears in journals such as Computers in Biology and Medicine, Egyptian Informatics Journal, Diagnostic Cytopathology, Archives of Computational Methods in Engineering and Biomedical Signal Processing and Control.

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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