Peter Pinto

529 citations
26 papers · 382 · h-index 8

Impact in

Papers in

Peter Pinto

24 papers receiving 376 citations

Peers

Peter Pinto
Comparison fields: 5 of 38
  • Health Informatics 31
  • Radiology, Nuclear Medicine and Imaging 147
  • Pulmonary and Respiratory Medicine 155
  • Computer Vision and Pattern Recognition 70
  • Artificial Intelligence 61
Replace Helen Hong with:
Helen Hong South Korea
Bogdan Maris Italy
Kaiming Kuang China
Marcus Pfister Germany
Sascha Zelzer Germany
Ricardo S. Avila United States
Ashis Kumar Dhara India
Bernhard E. H. Claus United States
Matin Hosseinzadeh Netherlands
Ashley Mercado Canada
Peter Pinto relative to Helen Hong South Korea Helen Hong's profile →
Citations per field
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Helen Hong · 1×
Citations per year

Countries citing papers authored by Peter Pinto

Since Specialization
Citations

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

Fields of papers citing papers by Peter Pinto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020137
2 201650
3 201639
4 201735
5 201726
6 202417
7 201410
8 20189
9 20188
10 20246
11 20185
12 20245
13 20245
14 20245
15 20124
16 20244
17 20243
18 20243
19 20253
20 20253

About Peter Pinto

Peter Pinto is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Artificial Intelligence, Computer Vision and Pattern Recognition and Health Informatics, having authored 26 papers that have together received 382 indexed citations. Recurring topics across this work include Prostate Cancer Diagnosis and Treatment (13 papers), AI in cancer detection (12 papers), Radiomics and Machine Learning in Medical Imaging (11 papers), Medical Image Segmentation Techniques (5 papers), Medical Imaging Techniques and Applications (3 papers), Ultrasound Imaging and Elastography (3 papers), Artificial Intelligence in Healthcare and Education (2 papers) and Advanced Radiotherapy Techniques (2 papers). The work is most often cited by research in Health Informatics (31 citations), Radiology, Nuclear Medicine and Imaging (147 citations), Pulmonary and Respiratory Medicine (155 citations), Computer Vision and Pattern Recognition (70 citations) and Artificial Intelligence (61 citations). Peter Pinto has collaborated with scholars based in United States, Canada and South Korea. Frequent co-authors include Peter L. Choyke, Bradford J. Wood, Sheng Xu, Barış Türkbey, Reza Seifabadi, Yue Chen, Zion Tsz Ho Tse, Amir M. Tahmasebi, Parvin Mousavi and Purang Abolmaesumi. Their work appears in journals such as Academic Radiology, International Journal of Computer Assisted Radiology and Surgery, Journal of Vascular and Interventional Radiology, IEEE Transactions on Biomedical Engineering and Oncotarget.

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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