Juha Pajula

633 total citations
23 papers, 394 citations indexed

About

Juha Pajula is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Juha Pajula has authored 23 papers receiving a total of 394 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Cognitive Neuroscience, 5 papers in Radiology, Nuclear Medicine and Imaging and 4 papers in Artificial Intelligence. Recurrent topics in Juha Pajula's work include Functional Brain Connectivity Studies (6 papers), Neural dynamics and brain function (4 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). Juha Pajula is often cited by papers focused on Functional Brain Connectivity Studies (6 papers), Neural dynamics and brain function (4 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). Juha Pajula collaborates with scholars based in Finland, Spain and United Kingdom. Juha Pajula's co-authors include Jussi Tohka, Mark van Gils, Jaakko Lähteenmäki, Mikko Niemi, Anna‐Leena Vuorinen, Mika Lehto, Kari Harno, Iiro P. Jääskeläinen, Wen‐Jui Kuo and Fa‐Hsuan Lin and has published in prestigious journals such as PLoS ONE, Scientific Reports and Human Brain Mapping.

In The Last Decade

Juha Pajula

20 papers receiving 389 citations

Peers

Juha Pajula

RNMI

ECP

CCM

Xuemin Wang China

Jens Madsen United States

Andrés Hoyos-Idrobo France

Eleanna Varangis United States

Fang Han China

Tim Hahn Germany

Babak Afshin‐Pour Canada

Grace Huckins United States

Ioannis Pappas United States

Xuemin Wang China

Juha Pajula

152 ×0.7

33 ×0.5

RNMI

50 ×0.8

36 ×0.7

ECP

13 ×0.4

CCM

Citations per year, relative to Juha Pajula Juha Pajula (= 1×) peers Xuemin Wang

Countries citing papers authored by Juha Pajula

Since Specialization

Citations

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

Fields of papers citing papers by Juha Pajula

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Juha Pajula

This figure shows the co-authorship network connecting the top 25 collaborators of Juha Pajula. A scholar is included among the top collaborators of Juha Pajula 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 Juha Pajula. Juha Pajula is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Sharma, Gaurav Kumar, et al.. (2025). Federated Learning for Predicting Mild Cognitive Impairment to Dementia Conversion. PubMed. 2025. 1–7.

Mäkinen, Johanna M., Paula Heikkilä, Juha Pajula, et al.. (2025). Screening for Celiac Disease in Childhood: Cost-effectiveness of Multiple Genetic and Serological Testing Approaches. Clinical Gastroenterology and Hepatology.

Degerli, Aysen, Pekka Jäkälä, Juha Pajula, Milla Immonen, & Miguel Bordallo López. (2024). MAMAF-Net: Motion-aware and multi-attention fusion network for stroke diagnosis. Biomedical Signal Processing and Control. 95. 106381–106381. 1 indexed citations

Pajula, Juha, et al.. (2024). Predictive modeling for identification of older adults with high utilization of health and social services. Scandinavian Journal of Primary Health Care. 42(4). 609–616. 1 indexed citations

Pahikkala, Tapio, Ileana Montoya Perez, Parisa Movahedi, et al.. (2024). Finnish perspective on using synthetic health data to protect privacy: the PRIVASA project. 4(2). 138–163.

Liedes, Hilkka, Juha Pajula, Anna‐Leena Vuorinen, et al.. (2023). CYP3A4*22 may increase bleeding risk in ticagrelor users. Basic & Clinical Pharmacology & Toxicology. 133(2). 202–207. 4 indexed citations

Lähteenmäki, Jaakko, et al.. (2022). Development of medical applications based on AI models and register data – regulatory considerations. Linköping electronic conference proceedings. 187. 141–146. 1 indexed citations

Black, Michaela, Debbie Rankin, Gorka Epelde, et al.. (2022). System Architecture of a European Platform for Health Policy Decision Making: MIDAS. Frontiers in Public Health. 10. 838438–838438. 4 indexed citations

Rabinovici‐Cohen, Simona, et al.. (2022). Multimodal Prediction of Five-Year Breast Cancer Recurrence in Women Who Receive Neoadjuvant Chemotherapy. Cancers. 14(16). 3848–3848. 20 indexed citations

10.

Paiho, Satu, et al.. (2022). Opportunities of collected city data for smart cities. 4(4). 275–291. 12 indexed citations

11.

Vuorinen, Anna‐Leena, Mika Lehto, Mikko Niemi, et al.. (2021). Pharmacogenetics of Anticoagulation and Clinical Events in Warfarin-Treated Patients: A Register-Based Cohort Study with Biobank Data and National Health Registries in Finland. Clinical Epidemiology. Volume 13. 183–195. 10 indexed citations

12.

Lähteenmäki, Jaakko, Anna‐Leena Vuorinen, Juha Pajula, et al.. (2021). Integrating data from multiple Finnish biobanks and national health-care registers for retrospective studies: Practical experiences. Scandinavian Journal of Public Health. 50(4). 482–489. 9 indexed citations

13.

Rabinovici‐Cohen, Simona, et al.. (2020). Radiomics for predicting response to neoadjuvant chemotherapy treatment in breast cancer. 45–45. 2 indexed citations

14.

Frank, Elisabeth, Dieter Maier, Juha Pajula, et al.. (2018). Platform for systems medicine research and diagnostic applications in psychotic disorders—The METSY project. European Psychiatry. 50. 40–46. 10 indexed citations

15.

Kauppi, Jukka‐Pekka, et al.. (2017). Functional brain segmentation using inter‐subject correlation in fMRI. Human Brain Mapping. 38(5). 2643–2665. 16 indexed citations

16.

Jääskeläinen, Iiro P., et al.. (2016). Brain hemodynamic activity during viewing and re-viewing of comedy movies explained by experienced humor. Scientific Reports. 6(1). 27741–27741. 37 indexed citations

17.

Pajula, Juha, et al.. (2014). A versatile software package for inter-subject correlation based analyses of fMRI. Frontiers in Neuroinformatics. 8. 2–2. 51 indexed citations

18.

Pajula, Juha & Jussi Tohka. (2014). Effects of spatial smoothing on inter-subject correlation based analysis of FMRI. Magnetic Resonance Imaging. 32(9). 1114–1124. 40 indexed citations

19.

Pajula, Juha, Jukka‐Pekka Kauppi, & Jussi Tohka. (2014). A versatile software package for inter-subject correlation based analyses of fMRI. 5. 6 indexed citations

20.

Pajula, Juha, et al.. (2012). Inter-Subject Correlation in fMRI: Method Validation against Stimulus-Model Based Analysis. PLoS ONE. 8(8). e41196–e41196. 70 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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