Pingfu Fu

278 papers receiving 9.1k citations

Pingfu Fu's Hit Papers

Deep learning informed multimodal fusion of radiology and pathology to predict outcomes in HPV-associated oropharyngeal squamous cell carcinoma 2025 · 27 citations
270+2+4Years since publication50100150200

Peers

Pingfu Fu
Comparison fields: 5 of 137
  • Oncology 1.2k
  • Radiology, Nuclear Medicine and Imaging 1.2k
  • Hematology 722
  • Health Informatics 113
  • Pulmonary and Respiratory Medicine 1.2k
Replace Brad H. Rovin with:
Brad H. Rovin United States
Valérie Paradis France
Myron Schwartz United States
Alastair D. Burt United Kingdom
Massimo Pinzani Italy
Philip F. Halloran Canada
Joel K. Greenson United States
Pietro Invernizzi Italy
Kwang‐Hyub Han South Korea
Anthony Jake Demetris United States
Pingfu Fu relative to Brad H. Rovin United States Brad H. Rovin's profile →
Citations per field
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Brad H. Rovin · 1×
Citations per year

Countries citing papers authored by Pingfu Fu

Since Specialization
Citations

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

Fields of papers citing papers by Pingfu Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 293 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007270
2 2003252
3 2010228
4
Changes in CT Radiomic Features Associated with Lymphocyte Distribution Predict Overall Survival and Response to Immunotherapy in Non–Small Cell Lung Cancer
Hit paper breakdown →
2019226
5 2018203
6 2011193
7 2004186
8 2012182
9 2013173
10 2009164
11 2004157
12 2017134
13 2010130
14 2013130
15 2006127
16 2011124
17 2009123
18 2002121
19 2008119
20 2020115

About Pingfu Fu

Pingfu Fu is a scholar working on Hematology, Radiology, Nuclear Medicine and Imaging, Oncology, Pulmonary and Respiratory Medicine and Cancer Research, having authored 293 papers that have together received 9.4k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (37 papers), AI in cancer detection (27 papers), Hematopoietic Stem Cell Transplantation (23 papers), Lung Cancer Research Studies (21 papers), Prostate Cancer Diagnosis and Treatment (17 papers), Lung Cancer Treatments and Mutations (13 papers), Cancer Immunotherapy and Biomarkers (12 papers) and Breast Cancer Treatment Studies (11 papers). The work is most often cited by research in Oncology (1.2k citations), Radiology, Nuclear Medicine and Imaging (1.2k citations), Hematology (722 citations), Health Informatics (113 citations) and Pulmonary and Respiratory Medicine (1.2k citations). Pingfu Fu has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Sanjay Gupta, Gregory T. MacLennan, Sanjeev Shukla, Afshin Dowlati, Anant Madabhushi, Vamsidhar Velcheti, Martin I. Resnick, Michael Yang, Kaustav Bera and Seunghee Park Margevicius. Their work appears in journals such as Transplantation and Cellular Therapy, Clinical Cancer Research, Blood, Journal of Clinical Oncology and International Journal of Radiation Oncology*Biology*Physics.

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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