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作 者:曾金坤 韦思炜 徐小林 章俊航 Zeng Jinkun;Wei Siwei;Xu Xiaolin;Zhang Junhang(Mental Health Center Affiliated to Zhejiang University School of Medicine/Geriatric Psychiatry Department 3,Hangzhou No.7 People’s Hospital,Hangzhou 310013,China;Information Department,Hangzhou No.7 People’s Hospital,Hangzhou 310013,China)
机构地区:[1]浙江大学医学院附属精神卫生中心/杭州市第七人民医院老年精神三科,杭州310013 [2]浙江大学医学院附属精神卫生中心/杭州市第七人民医院信息部,杭州310013
出 处:《中国数字医学》2022年第6期93-99,共7页China Digital Medicine
摘 要:目的:构建常见精神疾病智能大数据平台,助力临床辅助决策,提升精神疾病诊疗服务水平。方法:使用文本聚类等算法实现数据元的标准化,建立精神疾病多模态数据库,使用机器学习方法进行建模,实现临床辅助决策和智能预测。结果:建立了常见精神疾病标准数据库,记录了患者的人口学资料、伴随疾病及亲缘信息和症状评测等信息,结合AI算法对患者数据进行建模,实现常见精神疾病智能预测。结论:精神疾病智能大数据平台整合了精神疾病患者数据,运用数据资源进行智能预测,有助于有效降低对实体资源、医护资源的依赖,提升就医效率,促进医疗服务质量的提高。Objective To build an intelligent big data platform for common mental diseases to assist clinical decision-making and improve the level of diagnosis and treatment services for mental diseases.Methods Text clustering and other algorithms were used to standardize the data elements,a multi-modal database of mental disease was established,and machine learning method was used to build the model to realize clinical assisted decision making and intelligent prediction.Results The standard database of common mental diseases was established,which recorded the patient's demographic information,concomitant disease,relative information,symptom evaluation and other information of patients.Combined with AI algorithm,the patient data was modeled to realize the intelligent prediction of common mental diseases.Conclusion The intelligent big data platform for mental diseases integrates the data of patients with mental diseases,and makes intelligent predictions by using data resources,which can effectively reduce the dependence on physical resources and medical resources,improve the efficiency of medical treatment and promote the improvement of medical service quality.
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