Faisal Mahmood

7.8k citations
78 papers · 3.5k indexed · 10 hit papers · h-index 24
Topics
AI in cancer detection (32 papers)Radiomics and Machine Learning in Medical Imaging (20 papers)Artificial Intelligence in Healthcare and Education (10 papers)

In The Last Decade

Faisal Mahmood

71 papers receiving 3.4k citations

Hit Papers

Synthetic data in machine learning for medicine and healt...202120262022202420212022202420222022100200300400

Peers

Faisal Mahmood
Comparison fields: 5 of 180
  • Artificial Intelligence 1.9k
  • Radiology, Nuclear Medicine and Imaging 1.3k
  • Computer Vision and Pattern Recognition 683
  • Health Informatics 530
  • Molecular Biology 428
Replace Richard J. Chen with:
Richard J. Chen United States
Drew F. K. Williamson United States
Ming Y. Lu United States
Yun Liu United States
Narges Razavian United States
Tiffany Chen United States
Jason Hipp United States
Po-Hsuan Cameron Chen United States
Titus J. Brinker Germany
Ashish Sharma United States
Faisal Mahmood relative to Richard J. Chen United States Richard J. Chen's profile →
Citations per field
00.5×1.5×
Richard J. Chen · 1×
Citations per year

Countries citing papers authored by Faisal Mahmood

Since Specialization
Citations

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

Fields of papers citing papers by Faisal Mahmood

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Faisal Mahmood

This figure shows the co-authorship network connecting the top 25 collaborators of Faisal Mahmood. A scholar is included among the top collaborators of Faisal Mahmood based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Faisal Mahmood. Faisal Mahmood is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 7
3 9
4 1
5 6
6 27
7 6
8 16
9 2
10 7
11 18
12 6
13 8
14 12
15
Artificial intelligence for multimodal data integration in oncologybreakdown →
333
16 55
17 118
18
Synthetic data in machine learning for medicine and healthcarebreakdown →
414
19 23
20 23

About Faisal Mahmood

Faisal Mahmood is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 78 papers that have together received 3.5k indexed citations. Recurring topics across this work include AI in cancer detection (32 papers), Radiomics and Machine Learning in Medical Imaging (20 papers) and Artificial Intelligence in Healthcare and Education (10 papers). The work is most often cited by research in Health Informatics (530 citations), Artificial Intelligence (1.9k citations) and Radiology, Nuclear Medicine and Imaging (1.3k citations). Faisal Mahmood has collaborated with scholars based in United States, Pakistan and Japan. Frequent co-authors include Richard J. Chen, Ming Y. Lu, Drew F. K. Williamson, Tiffany Chen, Jana Lipková, Chengkuan Chen, Bowen Chen, Muhammad Shaban, Anurag Vaidya and Guillaume Jaume. Their work appears in journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

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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