Development of a Machine-Learning Model of Short-Term Prognostic Prediction for Spinal Stenosis Surgery in Korean Patients

Kim, Kyeong-Rae; Kim, Hyeun Sung; Park, Jae-Eun; Kang, Seung-Yeon; Lim, So-Young; Jang, Il-Tae

doi:10.3390/brainsci10110764

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Development of a Machine-Learning Model of Short-Term Prognostic Prediction for Spinal Stenosis Surgery in Korean Patients

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Nanoori Medical Research Institute, Nanoori Hospital Gangnam, Seoul 06048, Korea

Department of Neurosurgery, Nanoori Hospital Gangnam, Seoul 06048, Korea

Department of Anesthesia and Pain Medicine, Nanoori Hospital Gangnam, Seoul 06048, Korea

Author to whom correspondence should be addressed.

Brain Sci. 2020, 10(11), 764; https://doi.org/10.3390/brainsci10110764

Received: 28 August 2020 / Revised: 19 October 2020 / Accepted: 20 October 2020 / Published: 22 October 2020

(This article belongs to the Special Issue Degenerative Spinal Disease)

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Abstract

Background: In this study, based on machine-learning technology, we aim to develop a predictive model of the short-term prognosis of Korean patients who received spinal stenosis surgery. Methods: Using the data obtained from 112 patients with spinal stenosis admitted at N hospital from February to November, 2019, a predictive analysis was conducted for the pain index, reoperation, and surgery time. Results: Results show that the predicted area under the curve was 0.803, 0.887, and 0.896 for the pain index, reoperation, and surgery time, respectively, thereby indicating the accuracy of the model. Conclusion: This study verified that the individual characteristics of the patient and treatment characteristics during surgery enable a prediction of the patient prognosis and validate the accuracy of the approach. Further studies should be conducted to extend the scope of this research by incorporating a larger and more accurate dataset. View Full-Text

Keywords: machine learning; prediction; pilot study; spinal surgery; Korean

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Kim, K.-R.; Kim, H.S.; Park, J.-E.; Kang, S.-Y.; Lim, S.-Y.; Jang, I.-T. Development of a Machine-Learning Model of Short-Term Prognostic Prediction for Spinal Stenosis Surgery in Korean Patients. Brain Sci. 2020, 10, 764. https://doi.org/10.3390/brainsci10110764

AMA Style

Kim K-R, Kim HS, Park J-E, Kang S-Y, Lim S-Y, Jang I-T. Development of a Machine-Learning Model of Short-Term Prognostic Prediction for Spinal Stenosis Surgery in Korean Patients. Brain Sciences. 2020; 10(11):764. https://doi.org/10.3390/brainsci10110764

Chicago/Turabian Style

Kim, Kyeong-Rae, Hyeun S. Kim, Jae-Eun Park, Seung-Yeon Kang, So-Young Lim, and Il-Tae Jang. 2020. "Development of a Machine-Learning Model of Short-Term Prognostic Prediction for Spinal Stenosis Surgery in Korean Patients" Brain Sciences 10, no. 11: 764. https://doi.org/10.3390/brainsci10110764

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Development of a Machine-Learning Model of Short-Term Prognostic Prediction for Spinal Stenosis Surgery in Korean Patients

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