Publications

2025

  • O. Rainio, J. Hällilä, J. Teuho, R. Klén: Methods for estimating full width at half maximum. Signal Image Video P. 19 (2025) . https://doi.org/10.1007/s11760-025-03820-6
  • O. Rainio, R. Klén: Compartmental modeling for blood flow quantification from dynamic 15O-water PET images of humans: A systematic review. Ann Nucl Med (2025). https://doi.org/10.1007/s12149-025-02014-x

 

2024

  • M. Mahnoor, O. Rainio, R. Klén: Exploring Generative Adversarial Network-based Augmentation of Magnetic Resonance Brain Tumor Images. Appl. Sci. 2024, 14(24), 11822. https://doi.org/10.3390/app142411822
  • T. Rudroff, R. Klén, O. Rainio, J. Tuulari: The untapped potential of dimension reduction in neuroimaging: AI-driven multimodal analysis of Long COVID fatigue. Brain Sci. 2024, 14(12), 1209. https://doi.org/10.3390/brainsci14121209
  • T. Rudroff, O. Rainio, R. Klén: Neuroplasticity Meets Artificial Intelligence: A Hippocam-pus-Inspired Approach to the Stability–Plasticity Dilemma. Brain Sci. 2024, 14(11), 1111; https://doi.org/10.3390/brainsci14111111
  • J. Ottela, J. Huusko, R. Klen, S.V. Nesterov, A. Saraste, J. Knuuti: Short-term effects on sacubitril/valsartan therapy on right ventricle work and mechanics in patients with heart failure and reduced ejection fraction. Eur. Heart J., Volume 45, Issue Supplement_1, October 2024, ehae666.1093, https://doi.org/10.1093/eurheartj/ehae666.1093
  • O. Rainio, J. Liedes, S. Murtojärvi, S. Malaspina, J. Kemppainen, R. Klén: One-click annotation to improve segmentation by a convolutional neural network for PET images of head and neck cancer patients. Netw Model Anal Health Inform Bioinforma 13, 47 (2024). https://doi.org/10.1007/s13721-024-00483-0
  • T. Rudroff, O. Rainio, R. Klén: Leveraging Artificial Intelligence to Optimize Transcranial Direct Current Stimulation for Long COVID Management: A Forward-Looking Perspective. Brain Sci. 2024, 14(8), 831. https://doi.org//10.3390/brainsci14080831
  • A. Li, M.K. Jaakkola, T. Saaresranta, R. Klén, X.-G. Li: Analysis of sleep apnea research with a special focus on the use of positron emission tomography as a study tool. Sleep Med. Rev. 77 (2024). https://doi.org/10.1016/j.smrv.2024.101967
  • O. Rainio, J. Tamminen, M.S. Venäläinen, J. Liedes, J. Knuuti, J. Kemppainen, R. Klén: Comparison of thresholds for a convolutional neural network classifying medical images. Int. J. Data Sci. Anal. (2024). https://doi.org/10.1007/s41060-024-00584-z
  • T. Rudroff, O. Rainio, R. Klén: AI for the Prediction of Early Stages of Alzheimer’s Disease from Neuroimaging Biomarkers – A narrative review of a growing field. Neurol. Sci. (2024). https://doi.org/10.1007/s10072-024-07649-8, https://arxiv.org/abs/2406.17822
  • J. Teuho, J. Schultz, R. Klén, L.E. Juarez-Orozco, J. Knuuti, A. Saraste, N. Ono, S. Kanaya: Explainable deep learning-based ischemia detection using hybrid O-15 H2O perfusion PET/CT imaging and clinical data. J. Nucl. Cardiol. (2024). https://doi.org/10.1016/j.nuclcard.2024.101889
  • M. Jafaritadi, J. Teuho, E. Lehtonen, R. Klén, A. Saraste, C.S. Levin: Deep generative denoising networks enhance quality and accuracy of gated cardiac PET data. Ann. Nucl. Med. (2024). https://doi.org/10.1007/s12149-024-01945-1
  • O. Rainio, J. Teuho, R. Klén: Evaluation metrics and statistical tests for machine learning. Sci. Rep. 14 (2024), Article number: 6086. https://doi.org/10.1038/s41598-024-56706-x
  • O. Rainio, R. Klén: Comparison of Simple Augmentation Transformations for a Convolutional Neural Network Classifying Medical Images. Signal Image Video P. 18 (2024), 3353–3360. https://doi.org/10.1007/s11760-024-02998-5
  • E. Lehtonen*, I. Kujala*, J. Tamminen, T. Maaniitty, A. Saraste, J. Teuho, J. Knuuti, R. Klén: Incremental prognostic value of downstream positron emission tomography perfusion imaging after coronary computed tomography angiography: a study using machine learning. Eur. Heart J. Cardiovasc. Imaging 25 (2024). https://doi.org/10.1093/ehjci/jead246

 

2023

  • S.M. Hosseini, R.M. Moghaddam, J. Schultz, A. Saraste, R. Klén, J. Teuho: Explainable AI and Transfer Learning in the Classification of PET Cardiac Perfusion Polar Maps. IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD), 2023. doi: https://doi.org/10.1109/NSSMICRTSD49126.2023.10338595
  • M.K. Jaakkola, M. Rantala, A. Jalo, T. Saari, J. Hentilä, J.S. Helin, T.A. Nissinen, O. Eskola, J. Rajander, K.A. Virtanen, J.C. Hannukainen, F. López-Picón, R. Klén: Segmentation of dynamic total-body [18F]-FDG PET images using unsupervised clustering. Int. J. Biomed. Imaging, vol. 2023 (2023), Article ID 3819587, 13 pages. https://doi.org/10.1155/2023/3819587
  • O. Rainio, M. Nasser, M. Vuorinen, R. Klén: Image augmentation with conformal mappings for a convolutional neural network. Comput. Appl. Math. Preprint 42, Article number: 361 (2023). https://doi.org/10.1007/s40314-023-02501-9
  • J. Knuuti, J. Tuisku, H. Kärpijoki, H. Iida, T. Maaniitty, A. Latva-Rasku, V. Oikonen, S. Nesterov, J. Teuho, M.K. Jaakkola, R Klén, H. Louhi, V. Saunavaara, P. Nuutila, A. Saraste, J. Rinne, L. Nummenmaa: Quantitative perfusion imaging with total body positron emission tomography. J. Nucl. Med. 2023 Nov;64(Suppl 2):11S-19S. https://doi.org/10.2967/jnumed.122.264870
  • O. Rainio, J. Lahti, M. Anttinen, O. Ettala, M. Seppänen, P. Boström, J. Kemppainen, R. Klén: New method of using a convolutional neural network for 2D intraprostatic tumor segmentation from PET images. Res. Biomed. Eng. (2023). https://doi.org/10.1007/s42600-023-00314-7
  • R. Klén*, I.A. Huespe*, F. Gregalio, A.L. Blanco, P.R. Valdez, M.A. Mirofsky, B. Boietti, R. Gómez-Huelgas, J.M. Casas-Rojo, J.M. Antón-Santos, J.A. Pollán, D. Gómez-Varela: Development and validation of COEWS (COVID-19 Early Warning Score) for hospitalized COVID-19 with laboratory features: A multicontinental retrospective study. eLife 2023, 12:e85618.
    https://doi.org/10.7554/eLife.85618
  • T. Maaniitty, R. Jukema, P. Van Diemen, W. Nammas, I. Stenstrom, M. Maenpaa, I. Kujala, P.G. Raijmakers, R. Sprengers, R.N. Planken, R. Klen, P. Knaapen, A. Saraste, J. Knuuti, I. Danad: The time-dependent prognostic value of coronary computed tomography angiography in symptomatic patients. Eur. Heart J. Cardiovasc. Imaging 24 (2023). https://doi.org/10.1093/ehjci/jead119.263
  • J. Liedes, H. Hellström, O. Rainio, S. Murtojärvi, S. Malaspina, J. Hirvonen, R. Klén, J. Kemppainen: Automatic segmentation of head and neck cancer from PET-MRI data using deep learning. J. Med. Biol. Eng. (2023). https://doi.org/10.1007/s40846-023-00818-8
  • L.E. Juarez-Orozco, M. Niemi, M.W. Yeung, J.W. Benjamins, T. Maaniitty, J. Teuho, A. Saraste, J. Knuuti, P. van der Harst, R. Klén: Hybridizing machine learning in survival analysis of cardiac PET/CT imaging. J. Nucl. Cardiol. (2023). https://doi.org/10.1007/s12350-023-03359-4
  • H. Hellström, J. Liedes, O. Rainio, S. Malaspina, J. Kemppainen, R. Klén: Classification of head and neck cancer from PET images using convolutional neural networks. Sci. Rep. 13 (2023), Article number: 10528. https://doi.org/10.1038/s41598-023-37603-1
  • P. Harjulehto, R. Klén, M. Koskenoja: Analyysiä reaaliluvuilla, 6th edition, Unigrafia, Helsinki, 2023, 370 pages, ISBN 978-952-34-5249-7; 978-952-34-5423-1. (A calculus textbook for the first year students.)
  • I.A. Huespe, A. Ferraris, A.L. Blanco, P.R. Valdez, L. Peroni, L.A. Cayetti, M.A. Mirofsky, B. Boietti, R. Gómez-Huelgas, J.M. Casas-Rojo, J.M. Antón-Santos, J.M. Núñez-Cortés, C. Lumbreras, J.M. Ramos-Rincón, N.G. Barrio, M. Pedrera-Jiménez, M.D. Martin-Escalante, F. Rivas Ruiz, M.A. Onieva-García, C.R. Toso, M.R. Risk, R. Klén, J.A. Pollán, D. Gómez-Varela: COVID-19 vaccines reduce mortality in hospitalized patients with oxygen requirements: Differences between vaccine subtypes. Multicontinental cohort Study. J. Med. Virol. 95:5 (2023), e28786. https://doi.org/10.1002/jmv.28786
  • H. Keemu, K.J. Alakylä, R. Klén, V.J. Panula, M.S. Venäläinen, J.J. Haapakoski, A.P. Eskelinen, K. Pamilo, J.S. Kettunen, A.-P. Puhto, A.I. Vasara, L.L. Elo, K.T. Mäkelä: Risk factors for prosthetic joint infection revision following total knee arthroplasty based on 62,087 knees in the Finnish Arthroplasty Register from 2014 to 2020. Acta Orthop. 94 (2023), 215–223. https://doi.org/10.2340/17453674.2023.12307
  • O. Rainio, C. Han, J. Teuho, S.V. Nesterov, V. Oikonen, S. Piirola, T. Laitinen, M. Tättäläinen, J. Knuuti, R. Klén: Carimas: An extensive medical imaging data processing tool for research. J. Digit. Imaging (2023). doi: https://doi.org/10.1007/s10278-023-00812-1
  • I. Kujala, W. Nammas, T. Maaniitty, I. Stenström, R. Klén, J. J Bax, J. Knuuti, Antti Saraste: Prognostic value of combined coronary CT angiography and myocardial perfusion imaging in women and men. Eur. Heart J. Cardiovasc. Imaging (2023), jead072. doi: https://doi.org/10.1093/ehjci/jead072
  • I. Huespe, J. Pollan, A. Khalid, A. Ferraris, A. Blanco, R. Gómez-Huelgas, A. Miguel, J. Nuñes-Cortes, C. Lumbreras, J. Rincon, N. Barrio, J. Casas-Rojo, P. Valdez, M. Mirofsky, B. Boietti, R. Klén, L. Cayetti, F. Ruiz, J. Sinner, D. Varela: 907: COVID-19 Vaccine Protection Against Mortality In Patients With Oxygen: A Multicontinental Study. Crit. Care Med. 51 (2023), 446-446. doi: https://doi.org/10.1097/01.ccm.0000909356.97905.63

 

2022

  • R. Klén, D. Purohit, R. Gómez-Huelgas, J.M. Casas-Rojo, J.M.A. Santos, J.M. Núñez-Cortés, C. Lumbreras, J.M. Ramos-Rincón, P. Young, J.I. Ramírez, E.E.T. Omonte, R.G. Artega, M.T.C. Beltrán, P. Valdez, F. Pugliese, R. Castagna, N. Funke, B. Leiding, D. Gómez-Varela: Development and evaluation of a machine learning-based in-hospital COvid-19 Disease Outcome Predictor (CODOP): a multicontinental retrospective study. eLife 2022, 11:e75985. doi: https://doi.org/10.7554/eLife.75985
  • J. Lindén*, J. Teuho*, R. Klén, M. Teräs: Are quantitative errors reduced with time-of-flight reconstruction when using imperfect MR-based attenuation maps for 18F-FDG PET/MR neuroimaging?. Appl. Sci. 2022, 12(9), 4605. doi: https://doi.org/10.3390/app12094605
  • A. Subasi, S.S. Panigrahi, B.S. Patil, M.A. Canbaz, R. Klén: Chapter 8 – Advanced pattern recognition tools for disease diagnosis. Chapter in book In 5G IoT and Edge Computing for Smart Healthcare, Intelligent Data-Centric Systems, Academic Press, 2022, Pages 195-229, ISBN 9780323905480. https://doi.org/10.1016/B978-0-323-90548-0.00011-5
  • J. Lindén*, J. Teuho*, M. Teräs, R. Klén: Evaluation of three methods for delineation and attenuation estimation of the sinus region in MR-based attenuation correction for brain PET-MR imaging. BMC Medical Imaging volume 22, Article number: 48 (2022). https://doi.org/10.1186/s12880-022-00770-0
  • J. Teuho, J. Schultz, R. Klén, J. Knuuti, A. Saraste, N. Ono, S. Kanaya: Novel Classification of ischemia from myocardial polar maps in 15O–H2O cardiac perfusion imaging using a convolutional neural network. Sci. Rep. 12 (2022), Article number: 2839. doi: https://doi.org/10.1038/s41598-022-06604-x
  • L.E. Juarez-Orozco, R. Klén, M. Niemi, B. Ruijsink, G. Daquarti, R. van Es, J.-W. Benjamins, M. Yeung, P. van der Harst, J. Knuuti: Artificial Intelligence to Improve Risk Prediction with Nuclear Cardiac Studies. Curr. Cardiol. Rep. (2022). doi: https://doi.org/10.1007/s11886-022-01649-w
  • S. Laurila, E. Rebelos, M. Lahesmaa, L. Sun, K. Schnabl, T.-M. Peltomaa, R. Klén, M. U-Din, M.-J. Honka, O. Eskola, A.K. Kirjavainen, L. Nummenmaa, M. Klingenspor, K.A. Virtanen, P. Nuutila: Novel Effects of the Gastrointestinal Hormone Secretin on Cardiac Metabolism and Renal Function. Am. J. Physiol. Endocrinol. Metab. 322:1 (2022), E54-E62. doi: https://doi.org/10.1152/ajpendo.00260.2021
  • J. Schultz, R. Siekkinen, M.J. Tadi, M. Teräs, R. Klén, E. Lehtonen, A. Saraste, J. Teuho: Effect of respiratory motion correction and CT-based attenuation correction on dual-gated cardiac PET image quality and quantification. J. Nucl. Cardiol. 29, pages 2423–2433 (2022). doi: https://doi.org/10.1007/s12350-021-02769-6

 

2021

  • M. Venäläinen, V. Panula, R. Klén, J. Haapakoski, A. Eskelinen, M. Manninen, J. Kettunen, A.-P. Puhto, A. Vasara, K. Mäkelä, L. Elo: Riskilaskurimallit tyypillisimmille lyhyen aikavälin komplikaatioille sekä kuolemalle ensivaiheen lonkan kokotekonivelleikkauksen jälkeen perustuen Suomen Endoproteesirekisterin tietokantaan. Suomen ortopedia ja traumatologia (2021)
  • J. Rives Gambin, M.J. Tadi, J. Teuho, R. Klén, J. Knuuti, J. Koskinen, A. Saraste, E. Lehtonen: Learning to Denoise Gated Cardiac PET Images Using Convolutional Neural Networks. IEEE Access (2021). doi: 10.1109/ACCESS.2021.3122194
  • V.J. Panula, E.M. Ekman, M.S. Venäläinen, I. Laaksonen, R. Klén, J.J. Haapakoski, A.P. Eskelinen, L.L. Elo, K.T. Mäkelä: Posterior approach, fracture diagnosis and ASA class III-IV are associated with increased risk of revision for dislocation after total hip arthroplasty: An analysis of 33,337 operations from the Finnish Arthroplasty Register. Scand. J. Surg. 110 (2021), 351-358. doi: 10.1177/1457496920930617
  • J. Schultz, R. Siekkinen, M.J. Tadi, M. Teräs, R. Klén, E. Lehtonen, A. Saraste, J. Teuho: Effect of respiratory motion correction and CT-based attenuation correction on dual-gated cardiac PET image quality and quantification. Published online 3rd September 2021 in J. Nucl. Cardiol. doi: 10.1007/s12350-021-02769-6
  • M. Mahmoudian, M.S. Venäläinen, R. Klén, L.L. Elo: Stable Iterative Variable Selection. Bioinformatics 2021, btab501.
  • S. Laurila, L. Sun, M. Lahesmaa, K. Schnabl, K. Laitinen, R. Klén, Y. Li, M. Balaz, C. Wolfrum, K. Steiger, T. Niemi, M. Taittonen, M. U-Din, T. Välikangas, L.L. Elo, O. Eskola, A.K. Kirjavainen, L. Nummenmaa, K.A. Virtanen, M. Klingenspor, P. Nuutila: Secretin Activates Brown Fat and Induces Satiation. Nat. Metab. 3 (2021), 798-809.
  • R. Siekkinen, A.K. Kirjavainen, K. Koskensalo, N.A.S. Smith, A. Fenwick, V. Saunavaara, T. Tolvanen, H. Iida, A. Saraste, M. Teräs, J. Teuho: Assessment of a digital and an analog PET/CT system for accurate myocardial perfusion imaging with a flow phantom. J Nucl Cardiol, online 2021 May 4, doi: 10.1007/s12350-021-02631-9
  • E. Lehtonen, J. Teuho, J. Koskinen, M.J. Tadi, R. Klén, R. Siekkinen, J. Rives Gambin, T. Vasankari, A. Saraste: A Respiratory Motion Estimation Method Based on Inertial Measurement Units for Gated Positron Emission Tomography. Sensors 2021, 21, 3983.
  • J.W. Benjamins, M.W. Yeung, T. Maaniitty, A. Saraste, R. Klén, P. van der Harst, J. Knuuti, L. Eduardo Juarez-Orozco: Improving patient identification for advanced cardiac imaging through machine learning-integration of clinical and coronary CT angiography data. Int. J. Cardiol. 335 (2021), 130-136.
  • S. Sieberts, J. Schaff, M. Duda, B. Pataki, M. Sun, P. Snyder, J.-F. Daneault, F. Parisi, G. Costante, U. Rubin, P. Banda, Y. Chae, E. Neto, E. Dorsey, Z. Aydin, A. Chen, L. Elo, C. Espino, E. Glaab, E. Goan, F. Golabchi, Y. Görmez, M. Jaakkola, J. Jonnagaddala, R. Klén, D. Li, C. McDaniel, D. Perrin, N. Rad, T. Perumal, E. Rainaldi, S. Sapienza, P. Schwab, N. Shokhirev, M. Venäläinen, G. Vergara-Diaz, Y. Zhang, Y. Wang, The Parkinson’s Disease Digital Biomarker Challenge Consortium, Y. Guan, D. Brunner, P. Bonato, L. Mangravite, L. Omberg: Crowdsourcing digital health measures to predict Parkinson’s disease severity: the Parkinson’s Disease Digital Biomarker DREAM Challenge. NPJ Digit. Med. 4, Article number: 53 (2021).
  • M. Venäläinen, S. Mikko, V. Panula, R. Klén, J. Haapakoski, A.P. Eskelinen, M.J. Manninen, J. Kettunen, A.-P. Puhto, A. Vasara, K. Mäkelä, L.L. Elo, Laura: Preoperative Risk Prediction Models for Short-Term Revision and Death After Total Hip Arthroplasty. JBJS Open Access: January-March 2021 – Volume 6 – Issue 1 – p e20.00091 doi: 10.2106/JBJS.OA.20.00091
  • E. Harmaala, R. Klén: Ptolemy constant and uniformity. Publ. Math. Debrecen 98/1-2 (2021), 15-42.

 

2020

  • R. Siekkinen, J. Teuho, N.A.S. Smith, A. Fenwick, A.K. Kirjavainen, K. Koskensalo, et al. Study of the Effect of Reconstruction Parameters for Myocardial Perfusion Imaging in PET With a Novel Flow Phantom. Front Phys. 2020;8.
  • X .Xiao Liang, J. Jing Li, E. Antonecchia, Y. Ling, Z. Li, W. Xiao, Q. Chu, L. Wan, X. Hu, S. Han, J. Teuho, et al. NEMA-2008 and In-Vivo animal and plant imaging Performance of the large FOV preclinical digital PET/CT system Discoverist 180. IEEE Transactions on Radiation and Plasma Medical Sciences. 2020 Sep;4(5):622–9
  • M. Husso, I.O. Afara, M.J. Nissi, A. Kuivanen, P. Halonen, M. Tarkia, J. Teuho, et al. Quantification of Myocardial Blood Flow by Machine Learning Analysis of Modified Dual Bolus MRI Examination. Ann Biomed Eng. 2020 Aug 20;1–10.
  • P. Dadson, E. Rebelos, H. Honka, L.E. Juárez-Orozco, K.K. Kalliokoski, P. Iozzo, J. Teuho, et al. Change in abdominal, but not femoral subcutaneous fat CT-radiodensity is associated with improved metabolic profile after bariatric surgery. Nutrition, Metabolism and Cardiovascular Diseases. 2020 Nov 27;30(12):2363–71.
  • P. Movahedi, H. Merisaari, I.M. Perez, P. Taimen, J. Kemppainen, A. Kuisma, O. Eskola, J. Teuho, et al. Prediction of prostate cancer aggressiveness using 18 F-Fluciclovine (FACBC) PET and multisequence multiparametric MRI. Scientific Reports. 2020 Jun 10;10(1):9407.
  • J. Päivärinta, K. Metsärinne, E. Löyttyniemi, J. Teuho, T. Tolvanen, J. Knuuti, et al. Myocardial perfusion reserve of kidney transplant patients is well preserved. EJNMMI Research. 2020 Feb 10;10(1):9.
  • J. Teuho, L. Riehakainen, A. Honkaniemi, O. Moisio, C. Han, M. Tirri, S. Liu, T.J. Grönroos, J. Liu, L. Wan, X. Liang, Y. Ling, Y. Hua, A. Roivainen, J. Knuuti, Q. Xie, M. Teräs, N. D’Ascenzo, R. Klén: Evaluation of Image Quality with Four Positron Emitters and Three Preclinical PET/CT Systems. EJNMMI Research volume 10, Article number: 155 (2020).
  • R. Klén, J. Teuho, T. Noponen, K. Thielemnas, E. Hoppela, E. Lehtonen, H.T. Sipila, M. Teräs, J. Knuuti: Estimation of Optimal Number of Gates in Dual Gated 18F-FDG Cardiac PET. Sci. Rep. 10 (2020), Article number: 19362.
  • V.J. Panula, E.M. Ekman, M.S. Venäläinen, I. Laaksonen, R. Klén, J.J. Haapakoski, A.P. Eskelinen, L.L. Elo, K.T. Mäkelä: Posterior approach, fracture diagnosis and ASA class III-IV are associated with increased risk of revision for dislocation after total hip arthroplasty: An analysis of 33,337 operations from the Finnish Arthroplasty Register. Scand. J. Surg., published June 5, 2020.
  • I. Ranta, J. Teuho, J. Linden, R. Klén, M. Teräs, M. Kapanen, J. Keyriläinen: Assessment of MRI-Based Attenuation Correction for MRI-Only Radiotherapy Treatment Planning of the Brain. Diagnostics 10 (2020), 299.
  • P. Hariri, R. Klén, M. Vuorinen: Conformally Invariant Metrics and Quasiconformal Mappings, Springer Monographs in Mathematics. Springer, 2020. xix+502 pages, ISBN 978-3-030-32068-3; 978-3-030-32067-6.
  • R. Klén, M.-J. Honka, J.C. Hannukainen, V. Huovinen, M. Bucci, A. Latva-Rasku, M.S. Venäläinen, K.K. Kalliokoski, K.A. Virtanen, R. Lautamäki, P. Iozzo, L.L. Elo, P. Nuutila: Predicting skeletal muscle and whole-body insulin sensitivity using NMR-metabolomic profiling. J. Endocr. Soc. (2020), bvaa026.
  • M.S. Venäläinen, R. Klén, M. Mahmoudian, O.T. Raitakari, L.L. Elo: Easy-to-use tool for evaluating the elevated acute kidney injury risk against reduced cardiovascular disease risk during intensive blood pressure control. J. Hypertens. 38 (2020), 511-518.
  • R. Klén, M. Karhunen, L.L. Elo, Laura: Likelihood contrasts: a machine learning algorithm for binary classification of longitudinal data. Sci. Rep. 10 (2020), Article number: 1016.
  • J. Teuho, A. Torrado-Carvaja, H. Herzog, U. Anazodo, R. Klén, H. Iida, M. Teräs: Magnetic Resonance-Based Attenuation Correction and Scatter Correction in Neurological Positron Emission Tomography/Magnetic Resonance Imaging-Current Status With Emerging Applications.. Front. Phys. 7 (2020).