Niels Olson

1.6k citations
9 papers · 734 · 1 hit paper · h-index 6

Impact in

Papers in

Niels Olson

9 papers receiving 712 citations

Hit Papers

Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer 2019 · 302 citations
3020+2+4Years since publication100200300

Peers

Niels Olson
Comparison fields: 5 of 115
  • Health Informatics 137
  • Radiology, Nuclear Medicine and Imaging 370
  • Artificial Intelligence 467
  • Biophysics 62
  • Health Information Management 25
Replace Lily H. Peng with:
Lily H. Peng United States
Arash Mohtashamian United States
Kunal Nagpal United States
Norman Zerbe Germany
Judy J. Wang United States
Sharifa Sahai United States
Harshita Sharma United Kingdom
Oliver Díaz Spain
Christoph Haarburger Germany
Gregory Patrick Veldhuizen Germany
Niels Olson relative to Lily H. Peng United States Lily H. Peng's profile →
Citations per field
00.5×1.5×
Lily H. Peng · 1×
Citations per year

Countries citing papers authored by Niels Olson

Since Specialization
Citations

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

Fields of papers citing papers by Niels Olson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

9 of 9 papers shown
#Work
1
Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer
Hit paper breakdown →
2019302
2 2018246
3 202186
4 202145
5 202233
6 202117
7 20222
8 20182
9 20241

About Niels Olson

Niels Olson is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Oncology, Pulmonary and Respiratory Medicine and Infectious Diseases, having authored 9 papers that have together received 734 indexed citations. Recurring topics across this work include AI in cancer detection (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Infection Control and Ventilation (1 paper), Antifungal resistance and susceptibility (1 paper), Artificial Intelligence in Healthcare and Education (1 paper), Image Retrieval and Classification Techniques (1 paper), Human-Automation Interaction and Safety (1 paper) and Spaceflight effects on biology (1 paper). The work is most often cited by research in Health Informatics (137 citations), Radiology, Nuclear Medicine and Imaging (370 citations), Artificial Intelligence (467 citations), Biophysics (62 citations) and Health Information Management (25 citations). Niels Olson has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Lily H. Peng, Yun Liu, Arash Mohtashamian, Jason Hipp, Martin C. Stumpe, Jenny L. Smith, Timo Kohlberger, George E. Dahl, Mohammad Norouzi and Craig H. Mermel. Their work appears in journals such as Archives of Pathology & Laboratory Medicine, Scientific Reports, npj Digital Medicine, Journal of Pathology Informatics and SLEEP.

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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