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Validation of Knee KL-classifying Deep Neural Network with Finnish Patient Data (2022)

Niinimäki, E., Paloneva, J., Pölönen, I., Heinonen, A., & Äyrämö, S. (2022). Validation of Knee KL-classifying Deep Neural Network with Finnish Patient Data. In T. T. Tuovinen, J. Periaux, & P. Neittaanmäki (Eds.), Computational Sciences and Artificial Intelligence in Industry : New Digital Technologies for Solving Future Societal and Economical Challenges (pp. 177-188). Springer. Intelligent Systems, Control and Automation: Science and Engineering, 76. https://doi.org/10.1007/978-3-030-70787-3_12

JYU-tekijät tai -toimittajat

Julkaisun tiedot

Julkaisun kaikki tekijät tai toimittajat: Niinimäki, Esko; Paloneva, Juha; Pölönen, Ilkka; Heinonen, Ari; Äyrämö, Sami

Emojulkaisu: Computational Sciences and Artificial Intelligence in Industry : New Digital Technologies for Solving Future Societal and Economical Challenges

Emojulkaisun toimittajat: Tuovinen, Tero T.; Periaux, Jacques; Neittaanmäki, Pekka

ISBN: 978-3-030-70786-6

eISBN: 978-3-030-70787-3

Lehti tai sarja: Intelligent Systems, Control and Automation: Science and Engineering

ISSN: 2213-8986

eISSN: 2213-8994

Julkaisuvuosi: 2022

Sarjan numero: 76

Artikkelin sivunumerot: 177-188

Kirjan kokonaissivumäärä: 275

Kustantaja: Springer

Kustannuspaikka: Cham

Julkaisumaa: Sveitsi

Julkaisun kieli: englanti

DOI: https://doi.org/10.1007/978-3-030-70787-3_12

Julkaisun avoin saatavuus: Ei avoin

Julkaisukanavan avoin saatavuus:

Lisätietoja: The CSAI 2019 Conference (Computational Science and AI in Industry: New Digital Technologies for Solving Future Societal and Economical Challenges) took place at Jyväskylä, Finland, on June 12–14, 2019.

Tiivistelmä

Osteoarthritis (OA) is the most common form of joint disease in the world. The diagnosis of OA is currently made by human experts and suffers from subjectivity, but recently new promising detection algorithms have been developed. We validated the current state-of-the-art KL-classifying neural network model for knee OA using knee X-rays taken from postmenopausal women suffering from knee pain attributable to OA. The performance of the model on the clinical data was considerably lower compared to the previous results on population-based test data. This suggests that the performance of the current grading methods is not yet adequate to be applied in clinical settings. The present results also emphasize the importance of using clinical data for performance evaluation before deploying medical machine learning models.

YSO-asiasanat: nivelrikko; polvet; diagnostiikka; röntgenkuvaus; koneoppiminen; neuroverkot; validointi

Vapaat asiasanat: deep learning; neural network; convolution; osteoarthritis; validation

Liittyvät organisaatiot

OKM-raportointi: Kyllä

Raportointivuosi: 2022

JUFO-taso: 2