Letter to the editor concerning "A multimodal machine learning model integrating clinical and MRI data for predicting neurological outcomes following surgical treatment for cervical spinal cord injury" by T.Shimizu, et al. (Eur Spine J [2025]: doi: 10.1007/s00586-025-08873-2).
作者信息
Yu Weijie, Chen Yujing
机构信息
First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China.
Kunming City Maternal and Child Health Hospital, Kunming, China.
出版信息
Eur Spine J. 2025 Jun 9. doi: 10.1007/s00586-025-09017-2.
PMID:40488871
Abstract
摘要
相似文献
1
Letter to the editor concerning "A multimodal machine learning model integrating clinical and MRI data for predicting neurological outcomes following surgical treatment for cervical spinal cord injury" by T.Shimizu, et al. (Eur Spine J [2025]: doi: 10.1007/s00586-025-08873-2).
Eur Spine J. 2025 Jun 9. doi: 10.1007/s00586-025-09017-2.
2
Letter to the Editor concerning "A multimodal machine learning model integrating clinical and MRI data for predicting neurological outcomes following surgical treatment for cervical spinal cord injury" by Shimizu T, et al. (Eur Spine J [2025]: doi: 10.1007/s00586-025-08873-2).
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Answer to the Letter to the Editor of H. Daungsupawong, et al. concerning "A multimodal machine learning model integrating clinical and MRI data for predicting neurological outcomes following surgical treatment for cervical spinal cord injury" by Shimizu T, et al. (Eur Spine J [2025]: doi: 10.1007/s00586-025-08873-2).
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PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods.
BMJ. 2025 Mar 24;388:e082505. doi: 10.1136/bmj-2024-082505.
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TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods.
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