Qaiser Chaudry

1.0k citations
22 papers · 724 indexed · h-index 11

Impact in

Papers in

Qaiser Chaudry

21 papers receiving 706 citations

Peers

Qaiser Chaudry
Comparison fields: 5 of 95
  • Biophysics 117
  • Computer Vision and Pattern Recognition 207
  • Artificial Intelligence 204
  • Media Technology 42
  • Radiology, Nuclear Medicine and Imaging 104
Replace Christian Matek with:
Christian Matek Germany
Libo Zeng China
Mary Brady United States
Ting Zhou China
Tomáš Vičar Czechia
Ting Song China
Yijun Su China
Nicolas Jaccard United Kingdom
Chin‐Tu Chen United States
Qaiser Chaudry relative to Christian Matek Germany Christian Matek's profile →
Citations per field
00.5×1.5×2.2×
Christian Matek · 1×
Citations per year

Countries citing papers authored by Qaiser Chaudry

Since Specialization
Citations

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

Fields of papers citing papers by Qaiser Chaudry

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20216
2 20200
3 20175
4 201712
5 201617
6 20142
7 20127
8 201175
9 201013
10 200994
11 200910
12 20094
13 200911
14 20087
15 200815
16 2007400
17 200719
18 20071
19 200616
20 20061

About Qaiser Chaudry

Qaiser Chaudry is a scholar working on Computer Vision and Pattern Recognition, Biophysics, Computer Science Applications, Artificial Intelligence and Media Technology, having authored 22 papers that have together received 724 indexed citations. Recurring topics across this work include AI in cancer detection (10 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Medical Image Segmentation Techniques (4 papers), Advanced Neural Network Applications (3 papers), Cell Image Analysis Techniques (3 papers), Online Learning and Analytics (2 papers), Quantum Dots Synthesis And Properties (2 papers) and Molecular Biology Techniques and Applications (2 papers). The work is most often cited by research in Biophysics (117 citations), Computer Vision and Pattern Recognition (207 citations), Artificial Intelligence (204 citations), Media Technology (42 citations) and Radiology, Nuclear Medicine and Imaging (104 citations). Qaiser Chaudry has collaborated with scholars based in United States, Pakistan and United Kingdom. Frequent co-authors include May D. Wang, Sonal Kothari, Koon Yin Kong, John A. Petros, Shuming Nie, Yun Xing, Leland W.K. Chung, Jonathan W. Simons, Ruth O’Regan and Haiyen E. Zhau. Their work appears in journals such as IEEE Access, Journal of Pathology Informatics, Nature Protocols, Journal of Signal Processing Systems and Conference proceedings.

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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