Fujita Kazuki, Katsuki Masahito, Takasu Ai, Kitajima Ayako, Shimazu Tomokazu, Maruki Yuichi
Department of Neurology Saitama Neuropsychiatric Institute Saitama City Saitama Japan.
Chichibu City Otaki National Health Insurance Clinic Chichibu Saitama Japan.
Aging Med (Milton). 2022 Sep 25;5(3):167-173. doi: 10.1002/agm2.12224. eCollection 2022 Sep.
The diagnosis of Alzheimer's disease (AD) is sometimes difficult for nonspecialists, resulting in misdiagnosis. A missed diagnosis can lead to improper management and poor outcomes. Moreover, nonspecialists lack a simple diagnostic model with high accuracy for AD diagnosis.
Randomly assigned data, including training data, of 6000 patients and test data of 1932 from 7932 patients who visited our memory clinic between 2009 and 2021 were introduced into the artificial intelligence (AI)-based AD diagnostic model, which we had developed.
The AI-based AD diagnostic model used age, sex, Hasegawa's Dementia Scale-Revised, the Mini-Mental State Examination, the educational level, and the voxel-based specific regional analysis system for Alzheimer's disease (VSRAD) score. It had a sensitivity, specificity, and c-static value of 0.954, 0.453, and 0.819, respectively. The other AI-based model that did not use the VSRAD had a sensitivity, specificity, and c-static value of 0.940, 0.504, and 0.817, respectively.
We created an AD diagnostic model with high sensitivity for AD diagnosis using only data acquired in daily clinical practice. By using these AI-based models, nonspecialists could reduce missed diagnoses and contribute to the appropriate use of medical resources.
对于非专科医生而言，阿尔茨海默病（AD）的诊断有时颇具难度，进而导致误诊。漏诊会致使管理不当及预后不佳。此外，非专科医生缺乏一种用于AD诊断的简单且准确率高的诊断模型。
将2009年至2021年间前来我们记忆门诊就诊的7932例患者中的6000例患者的随机分配数据（包括训练数据）以及1932例患者的测试数据引入我们所开发的基于人工智能（AI）的AD诊断模型。
基于AI的AD诊断模型采用了年龄、性别、修订版长谷川痴呆量表、简易精神状态检查表、教育程度以及基于体素的阿尔茨海默病特定区域分析系统（VSRAD）评分。其灵敏度、特异度和c统计值分别为0.954、0.453和0.819。另一个未使用VSRAD的基于AI的模型的灵敏度、特异度和c统计值分别为0.940、0.504和0.817。
我们仅使用日常临床实践中获取的数据创建了一个对AD诊断具有高灵敏度的AD诊断模型。通过使用这些基于AI的模型，非专科医生可以减少漏诊，并有助于合理使用医疗资源。
