【摘要】 目的 旨在构建人体股骨颈骨折影像人工智能（artificial intelligence,AI）快速诊断方法，从而实现股骨颈骨折的自动化评估。方法 采集1 018例股骨颈骨折的病例作为研究样本，分为训练集（676例）、验证集（112例）和测试集（230例）。应用训练集和验证集样本通过自动化影像预处理、骨折诊断模型构建和模型评估三个步骤进行股骨颈骨折评估模型构建，应用测试集对模型进行测试。结果 建立了1 018例股骨颈骨折样本数据库。建立的智能评估模型识别股骨颈骨折精准率达到78.7%。结论 该模型将为股骨颈骨折自动化评估软件的研发提供技术支撑。更多还原

【Abstract】 Objective To develop an artificial intelligence(AI) method for the rapid imaging diagnosis of human femoral neck fractures and realize automatic evaluation. Methods A total of 1 018 cases of femoral neck fractures were collected and divided into training set(676 cases),validation set(112 cases),and test set(230 cases). The training set and validation set were used to construct the evaluation model of femoral neck fracture through three steps: automatic image pretreatment,fracture diagnosis model construction and model evaluation. The test set was used to validate the model. Results A database of 1 018 cases of femoral neck fracture was established. The accuracy of the established intelligent assessment model in identifying femoral neck fractures reached 78.7%. Conclusion The established intelligent evaluation model will provide technical support for the development of automatic evaluation software of femoral neck fractures.更多还原