Peter Bult

116 papers receiving 5.1k citations

Peter Bult's Hit Papers

Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis 2016 · 722 citations
7220+3+6Years since publication200400600

Peers

Peter Bult
Comparison fields: 5 of 150
  • Cancer Research 1.9k
  • Health Informatics 116
  • Pathology and Forensic Medicine 1.5k
  • Radiology, Nuclear Medicine and Imaging 1.6k
  • Oncology 1.3k
Replace Craig H. Mermel with:
Craig H. Mermel United States
Navneet Narula United States
Julien Caldéraro France
Moritz Gerstung United Kingdom
Dirk Jäger Germany
Edi Brogi United States
Mikael Lundin Finland
Hannah Gilmore United States
Timo Gaiser Germany
Niels Halama Germany
Peter Bult relative to Craig H. Mermel United States Craig H. Mermel's profile →
Citations per field
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Craig H. Mermel · 1×
Citations per year

Countries citing papers authored by Peter Bult

Since Specialization
Citations

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

Fields of papers citing papers by Peter Bult

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 120 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis
Hit paper breakdown →
2016722
2 2009381
3 2020241
4 2001224
5 2018216
6
Three dimensional imaging of mammary ductal carcinoma in situ: clinical implications.
1994192
7 2010179
8 2012176
9 2009159
10 2017130
11 200494
12 200294
13 201992
14 200686
15 200885
16 201181
17 201777
18 201973
19 200968
20 199767

About Peter Bult

Peter Bult is a scholar working on Cancer Research, Pathology and Forensic Medicine, Oncology, Radiology, Nuclear Medicine and Imaging and Surgery, having authored 120 papers that have together received 5.3k indexed citations. Recurring topics across this work include Breast Cancer Treatment Studies (64 papers), Breast Lesions and Carcinomas (45 papers), AI in cancer detection (17 papers), MRI in cancer diagnosis (16 papers), BRCA gene mutations in cancer (13 papers), Breast Implant and Reconstruction (13 papers), Radiomics and Machine Learning in Medical Imaging (13 papers) and Cancer Genomics and Diagnostics (11 papers). The work is most often cited by research in Cancer Research (1.9k citations), Health Informatics (116 citations), Pathology and Forensic Medicine (1.5k citations), Radiology, Nuclear Medicine and Imaging (1.6k citations) and Oncology (1.3k citations). Peter Bult has collaborated with scholars based in Netherlands, United States and Germany. Frequent co-authors include Jeroen van der Laak, Vivianne C. G. Tjan‐Heijnen, C. Boetes, Theo Wobbes, Geert Litjens, Meyke Hermsen, Maaike de Boer, Bram van Ginneken, Ritse M. Mann and P. J. van Diest. Their work appears in journals such as Breast Cancer Research and Treatment, Cellular Oncology, European Journal of Surgical Oncology, JNCI Journal of the National Cancer Institute and Annals of Surgical Oncology.

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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