Artificial intelligence facilitates decision-making in the treatment of lumbar disc herniations
- PDF / 870,861 Bytes
- 9 Pages / 595.276 x 790.866 pts Page_size
- 104 Downloads / 187 Views
ORIGINAL ARTICLE
Artificial intelligence facilitates decision‑making in the treatment of lumbar disc herniations André Wirries1 · Florian Geiger1 · Ahmed Hammad1 · Ludwig Oberkircher2 · Ingmar Blümcke3 · Samir Jabari3 Received: 25 April 2020 / Revised: 5 September 2020 / Accepted: 22 September 2020 © The Author(s) 2020
Abstract Purpose Apart from patients with severe neurological deficits, it is not clear whether surgical or conservative treatment of lumbar disc herniations is superior for the individual patient. We investigated whether deep learning techniques can predict the outcome of patients with lumbar disc herniation after 6 months of treatment. Methods The data of 60 patients were used to train and test a deep learning algorithm with the aim to achieve an accurate prediction of the ODI 6 months after surgery or the start of conservative therapy. We developed an algorithm that predicts the ODI of 6 randomly selected test patients in tenfold cross-validation. Results A 100% accurate prediction of an ODI range could be achieved by dividing the ODI scale into 12% sections. A maximum absolute difference of only 3.4% between individually predicted and actual ODI after 6 months of a given therapy was achieved with our most powerful model. The application of artificial intelligence as shown in this work also allowed to compare the actual patient values after 6 months with the prediction for the alternative therapy, showing deviations up to 18.8%. Conclusion Deep learning in the supervised form applied here can identify patients at an early stage who would benefit from conservative therapy, and on the contrary avoid painful and unnecessary delays for patients who would profit from surgical therapy. In addition, this approach can be used in many other areas of medicine as an effective tool for decision-making when choosing between opposing treatment options, despite small patient groups. Keywords Artificial intelligence · Lumbar disc herniation · Supervised machine learning · Outcome prediction · Conservative vs. Operative
Introduction The decision for operative or conservative treatment of spinal disorders is often difficult as the evidence for treatment options is insufficient. Particularly in the case of lumbar disc Electronic supplementary material The online version of this article (https://doi.org/10.1007/s00586-020-06613-2) contains supplementary material, which is available to authorized users. * André Wirries Andre.Wirries@Hessing‑Stiftung.de 1
Spine Center, Hessing Foundation, Hessingstrasse 17, 86199 Augsburg, Germany
2
Center of Orthopaedic and Trauma Surgery, Philipps University of Marburg, Baldingerstrasse, 35043 Marburg, Germany
3
Neuropathological Institute, University Hospitals Erlangen, Schwabachanlage 6, 91054 Erlangen, Germany
herniations, the decision between surgical and conservative therapy is often a challenging and physician-dependent decision. If the patients do not suffer from neurological deficits, usually a conservative therapy is started for at least 6 weeks
Data Loading...
