Oona Rainio

38 papers receiving 806 citations

Oona Rainio's Hit Papers

Evaluation metrics and statistical tests for machine learning 2024 · 611 citations
6110+1Years since publication200400600

Peers

Oona Rainio
Comparison fields: 5 of 157
  • Health Informatics 17
  • Geometry and Topology 50
  • Radiology, Nuclear Medicine and Imaging 94
  • Applied Mathematics 44
  • Artificial Intelligence 142
Replace Riku Klén with:
Riku Klén Finland
Rishabh Sharma India
Pengfei Yan China
Maria Antonietta Pascali Italy
Richard B. Sowers United States
Solveig Badillo France
Ana‐Maria Staicu United States
Rémi Dubois France
Mohammad Jafari Jozani Canada
Oona Rainio relative to Riku Klén Finland Riku Klén's profile →
Citations per field
00.5×1.5×
Riku Klén · 1×
Citations per year

Countries citing papers authored by Oona Rainio

Since Specialization
Citations

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

Fields of papers citing papers by Oona Rainio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Evaluation metrics and statistical tests for machine learning
Hit paper breakdown →
2024611
2 202331
3 202423
4 202317
5 202310
6 202110
7 20249
8 20228
9 20228
10 20248
11 20218
12 20228
13 20227
14 20227
15 20256
16 20236
17 20245
18 20254
19 20253
20 20243

About Oona Rainio

Oona Rainio is a scholar working on Geometry and Topology, Applied Mathematics, Radiology, Nuclear Medicine and Imaging, Neurology and Computer Vision and Pattern Recognition, having authored 43 papers that have together received 822 indexed citations. Recurring topics across this work include Analytic and geometric function theory (14 papers), Medical Imaging Techniques and Applications (9 papers), Radiomics and Machine Learning in Medical Imaging (8 papers), Holomorphic and Operator Theory (6 papers), Algebraic and Geometric Analysis (5 papers), Geometric Analysis and Curvature Flows (4 papers), Brain Tumor Detection and Classification (4 papers) and AI in cancer detection (4 papers). The work is most often cited by research in Health Informatics (17 citations), Geometry and Topology (50 citations), Radiology, Nuclear Medicine and Imaging (94 citations), Applied Mathematics (44 citations) and Artificial Intelligence (142 citations). Oona Rainio has collaborated with scholars based in Finland, Qatar and United States. Frequent co-authors include Riku Klén, Jarmo Teuho, Матти Вуоринен, Thorsten Rudroff, Juhani M. Knuuti, Mohamed M. S. Nasser, Simona Malaspina, Jukka Kemppainen, Chunlei Han and Vesa Oikonen. Their work appears in journals such as Annals of Nuclear Medicine, European Radiology Experimental, Scientific Reports, Journal of Imaging Informatics in Medicine and Results in Mathematics.

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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