Mika E. Mononen

2.2k total citations
70 papers, 1.7k citations indexed

About

Mika E. Mononen is a scholar working on Surgery, Rheumatology and Biomedical Engineering. According to data from OpenAlex, Mika E. Mononen has authored 70 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Surgery, 52 papers in Rheumatology and 38 papers in Biomedical Engineering. Recurrent topics in Mika E. Mononen's work include Osteoarthritis Treatment and Mechanisms (52 papers), Total Knee Arthroplasty Outcomes (43 papers) and Knee injuries and reconstruction techniques (33 papers). Mika E. Mononen is often cited by papers focused on Osteoarthritis Treatment and Mechanisms (52 papers), Total Knee Arthroplasty Outcomes (43 papers) and Knee injuries and reconstruction techniques (33 papers). Mika E. Mononen collaborates with scholars based in Finland, Australia and Denmark. Mika E. Mononen's co-authors include Rami K. Korhonen, Jukka S. Jurvelin, Petri Tanska, Juha Töyräs, Kimmo Halonen, Miika T. Nieminen, Petro Julkunen, Hanna Isaksson, Simo Saarakkala and Jari Salo and has published in prestigious journals such as PLoS ONE, Scientific Reports and Journal of Biomechanics.

In The Last Decade

Mika E. Mononen

66 papers receiving 1.6k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mika E. Mononen Finland 26 1.3k 1.0k 873 163 49 70 1.7k
Chiara Giulia Fontanella Italy 26 628 0.5× 582 0.6× 747 0.9× 361 2.2× 40 0.8× 78 1.5k
Petri Tanska Finland 20 800 0.6× 798 0.8× 544 0.6× 163 1.0× 45 0.9× 77 1.2k
Tobias Stammberger Germany 20 1.2k 1.0× 853 0.8× 690 0.8× 230 1.4× 109 2.2× 31 1.7k
Panu Kiviranta Finland 11 402 0.3× 622 0.6× 390 0.4× 107 0.7× 68 1.4× 22 846
F. Dubrana France 22 1.4k 1.1× 436 0.4× 281 0.3× 475 2.9× 56 1.1× 87 1.8k
Gangadhar M. Utturkar United States 20 1.0k 0.8× 473 0.5× 564 0.6× 508 3.1× 18 0.4× 29 1.3k
Jessica E. Goetz United States 19 801 0.6× 243 0.2× 247 0.3× 594 3.6× 55 1.1× 90 1.2k
Deva D. Chan United States 19 318 0.2× 371 0.4× 335 0.4× 96 0.6× 77 1.6× 42 777
Ian D. Hutchinson United States 17 622 0.5× 149 0.1× 196 0.2× 228 1.4× 11 0.2× 40 843
Svea Faber Germany 12 478 0.4× 529 0.5× 328 0.4× 97 0.6× 43 0.9× 35 756

Countries citing papers authored by Mika E. Mononen

Since Specialization
Citations

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

Fields of papers citing papers by Mika E. Mononen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mika E. Mononen. 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 Mika E. Mononen. The network helps show where Mika E. Mononen may publish in the future.

Co-authorship network of co-authors of Mika E. Mononen

This figure shows the co-authorship network connecting the top 25 collaborators of Mika E. Mononen. A scholar is included among the top collaborators of Mika E. Mononen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mika E. Mononen. Mika E. Mononen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Mononen, Mika E., et al.. (2024). Machine Learning Model Trained with Finite Element Modeling Can Predict the Risk of Osteoarthritis: Data from the Osteoarthritis Initiative. Applied Sciences. 14(20). 9538–9538. 2 indexed citations
2.
3.
Turunen, Mikael J., et al.. (2024). Two-Stage Classification of Future Knee Osteoarthritis Severity After 8 Years Using MRI: Data from the Osteoarthritis Initiative. Annals of Biomedical Engineering. 52(12). 3172–3183. 4 indexed citations
4.
Stenroth, Lauri, Tine Alkjær, Pasi A. Karjalainen, et al.. (2024). Predicting Knee Joint Contact Force Peaks During Gait Using a Video Camera or Wearable Sensors. Annals of Biomedical Engineering. 52(12). 3280–3294. 1 indexed citations
6.
Orozco, Gustavo A., et al.. (2023). Comparison of constitutive models for meniscus and their effect on the knee joint biomechanics during gait. Computer Methods in Biomechanics & Biomedical Engineering. 26(16). 2008–2021. 5 indexed citations
7.
Stenroth, Lauri, et al.. (2023). Prediction of Knee Joint Compartmental Loading Maxima Utilizing Simple Subject Characteristics and Neural Networks. Annals of Biomedical Engineering. 51(11). 2479–2489. 6 indexed citations
8.
Esrafilian, Amir, Lauri Stenroth, Tine Alkjær, et al.. (2023). Sensitivity of simulated knee joint mechanics to selected human and bovine fibril-reinforced poroelastic material properties. Journal of Biomechanics. 160. 111800–111800. 3 indexed citations
9.
Esrafilian, Amir, Kimmo Halonen, Christine Mary Dzialo, et al.. (2023). Effects of gait modifications on tissue‐level knee mechanics in individuals with medial tibiofemoral osteoarthritis: A proof‐of‐concept study towards personalized interventions. Journal of Orthopaedic Research®. 42(2). 326–338. 7 indexed citations
10.
Tanska, Petri, Jaakko K. Sarin, Ervin Nippolainen, et al.. (2023). Visible and Near-Infrared Spectroscopy Enables Differentiation of Normal and Early Osteoarthritic Human Knee Joint Articular Cartilage. Annals of Biomedical Engineering. 51(10). 2245–2257. 8 indexed citations
11.
Esrafilian, Amir, Lauri Stenroth, Mika E. Mononen, et al.. (2022). An EMG-Assisted Muscle-Force Driven Finite Element Analysis Pipeline to Investigate Joint- and Tissue-Level Mechanical Responses in Functional Activities: Towards a Rapid Assessment Toolbox. IEEE Transactions on Biomedical Engineering. 69(9). 2860–2871. 21 indexed citations
12.
Esrafilian, Amir, Lauri Stenroth, Mika E. Mononen, et al.. (2022). Toward Tailored Rehabilitation by Implementation of a Novel Musculoskeletal Finite Element Analysis Pipeline. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 30. 789–802. 9 indexed citations
13.
Mohammadi, Ali, Mika E. Mononen, Jukka Hirvasniemi, et al.. (2022). Rapid X-Ray-Based 3-D Finite Element Modeling of Medial Knee Joint Cartilage Biomechanics During Walking. Annals of Biomedical Engineering. 50(6). 666–679. 10 indexed citations
15.
Mononen, Mika E., Matthew S. Tanaka, Santtu Mikkonen, et al.. (2021). Subject‐specific biomechanical analysis to estimate locations susceptible to osteoarthritis—Finite element modeling and MRI follow‐up of ACL reconstructed patients. Journal of Orthopaedic Research®. 40(8). 1744–1755. 12 indexed citations
16.
Mononen, Mika E., Matthew S. Tanaka, Mingrui Yang, et al.. (2019). Identification of locations susceptible to osteoarthritis in patients with anterior cruciate ligament reconstruction: Combining knee joint computational modelling with follow-up T1ρ and T2 imaging. Clinical Biomechanics. 79. 104844–104844. 19 indexed citations
17.
Mononen, Mika E., Ali Mohammadi, Matthew S. Tanaka, et al.. (2018). Comparison between kinetic and kinetic-kinematic driven knee joint finite element models. Scientific Reports. 8(1). 17351–17351. 32 indexed citations
18.
Mononen, Mika E., Petri Tanska, Hanna Isaksson, & Rami K. Korhonen. (2017). New algorithm for simulation of proteoglycan loss and collagen degeneration in the knee joint: Data from the osteoarthritis initiative. Journal of Orthopaedic Research®. 36(6). 1673–1683. 39 indexed citations
19.
Kokkola, Harri, Tero Mielonen, Mika E. Mononen, et al.. (2016). Retrieval of aerosol optical depth from surface solar radiation measurementsusing machine learning algorithms, non-linear regression and a radiativetransfer-based look-up table. Atmospheric chemistry and physics. 16(13). 8181–8191. 28 indexed citations
20.
Tanska, Petri, Mika E. Mononen, Chengjuan Qu, et al.. (2016). A combined experimental atomic force microscopy-based nanoindentation and computational modeling approach to unravel the key contributors to the time-dependent mechanical behavior of single cells. Biomechanics and Modeling in Mechanobiology. 16(1). 297–311. 12 indexed citations

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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