Rizwan Qureshi

80 papers receiving 1.4k citations

Rizwan Qureshi's Hit Papers

A Comprehensive Systematic Review of YOLO for Medical Object Detection (2018 to 2023) 2024 · 118 citations
1180+1+2Years since publication4080120

Peers

Rizwan Qureshi
Comparison fields: 5 of 161
  • Health Informatics 38
  • Oral Surgery 174
  • Computer Vision and Pattern Recognition 186
  • Periodontics 37
  • Medical Laboratory Technology 11
Replace Meng Yang with:
Meng Yang China
Yaqi Wang China
Piotr M. Szczypiński Poland
Ali Madani United States
L. Rodney Long United States
Mohammed Elmusrati Finland
Yong‐Deok Kim South Korea
Joseph A. Cruz Canada
Marcelo Zanchetta do Nascimento Brazil
Zafer Cömert Türkiye
Rizwan Qureshi relative to Meng Yang China Meng Yang's profile →
Citations per field
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Citations per year

Countries citing papers authored by Rizwan Qureshi

Since Specialization
Citations

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

Fields of papers citing papers by Rizwan Qureshi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 93 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004188
2
AI in drug discovery and its clinical relevance
Hit paper breakdown →
2023135
3
A Comprehensive Systematic Review of YOLO for Medical Object Detection (2018 to 2023)
Hit paper breakdown →
2024118
4 2022105
5 202382
6 201976
7 202366
8 202250
9 200248
10 202236
11 202335
12 202234
13 201931
14 200025
15 202220
16 201219
17 202418
18 201917
19 201717
20 202216

About Rizwan Qureshi

Rizwan Qureshi is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Molecular Biology, Pulmonary and Respiratory Medicine and Artificial Intelligence, having authored 93 papers that have together received 1.5k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (9 papers), COVID-19 diagnosis using AI (9 papers), Lung Cancer Treatments and Mutations (8 papers), Cancer therapeutics and mechanisms (7 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), ECG Monitoring and Analysis (5 papers), IoT and Edge/Fog Computing (4 papers) and Advanced Image and Video Retrieval Techniques (4 papers). The work is most often cited by research in Health Informatics (38 citations), Oral Surgery (174 citations), Computer Vision and Pattern Recognition (186 citations), Periodontics (37 citations) and Medical Laboratory Technology (11 citations). Rizwan Qureshi has collaborated with scholars based in Pakistan, Hong Kong and United States. Frequent co-authors include Hong Yan, Tanvir Alam, Jia Wu, Muhammad Uzair, Taimoor Muzaffar Gondal, A. J. E. Qualtrough, D.B. Drucker, Helen V Worthington, Khurram Khurshid and Sheheryar Khan. Their work appears in journals such as IEEE Access, Expert Systems with Applications, Diseases of the Esophagus, IEEE/ACM Transactions on Computational Biology and Bioinformatics and Scientific Reports.

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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