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| 人工智能在脊柱畸形诊疗中的应用 | |
| 引用本文： | 吴南,仉建国,朱源棚,陈癸霖,陈泽夫.人工智能在脊柱畸形诊疗中的应用[J].山东大学学报(医学版),2023,61(3):14-20. |
| 作者姓名： | 吴南 仉建国 朱源棚 陈癸霖 陈泽夫 |
| 作者单位： | 1. 中国医学科学院北京协和医院骨科, 北京 100730 2. 骨骼畸形遗传学研究北京市重点实验室, 北京 100730 3. 疑难重症及罕见病国家重点实验室，北京协和医院, 北京 100730 4. 中国医学科学院脊柱畸形大数据研究与应用重点实验室, 北京 100730 |
| 基金项目： | 国家自然科学基金(82072391)；;北京自然科学基金(JQ20032)； |
| 摘 要： | 脊柱畸形是一种高致畸致残性疾病，其发病年龄可覆盖全生命周期。随着计算机技术的快速发展，人工智能有了显著的进步。目前人工智能在疾病的诊疗方面有着巨大的应用潜能，也逐渐被应用于脊柱畸形的筛查、诊治、手术决策、术中操作和并发症预测等多个方面。近年来，许多研究对此方向进行了探索，提出了很多具有优秀表现和广阔应用前景的方案与模型，本文就此做一综述。 |
| 关 键 词： | 人工智能 脊柱畸形 脊柱侧凸 神经网络 机器学习 |
| 收稿时间： | 2022-08-10 |
Application of artificial intelligence in the diagnosis and treatment of spinal deformity |
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| Nan WU,Jianguo ZHANG,Yuanpeng ZHU,Guilin CHEN,Zefu CHEN.Application of artificial intelligence in the diagnosis and treatment of spinal deformity[J].Journal of Shandong University:Health Sciences,2023,61(3):14-20. | |
| Authors: | Nan WU Jianguo ZHANG Yuanpeng ZHU Guilin CHEN Zefu CHEN |
| Institution: | 1. Department of Orthopedic Surgery, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China 2. Beijing Key Laboratory for Genetic Research of Skeletal Deformity, Beijing 100730, China 3. State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Beijing 100730, China 4. Key Laboratory of Spinal Deformity Research and Application of Big Data, Beijing 100730, China |
| Abstract: | Spinal deformity is a highly teratogenic and disabling disease, whose age of onset covers the entire life cycle. With the rapid development of computer technology, artificial intelligence has made remarkable progress, and has huge application potential in the diagnosis and treatment of diseases, especially in the screening, diagnosis and treatment, surgical decision-making, intraoperative operations and complication prediction of spinal deformities. In the past few years, a large number of researches have explored in the related fields and proposed plentiful well-working and promising projects and models. This paper will review the latest advances. |
| Keywords: | Artificial intelligence Spinal deformity Scoliosis Neural network Machine learning |
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