The invention relates to the technical field of maternal and fetal
medicine, in particular to a regional maternal and fetal
medicine congenital structure anomaly
risk assessment system based on
big data. A regional feature quantification module; a
risk assessment model module; an
interpretability analysis module; and a streaming update module. According to the scheme,
deep integration and unified representation of individual information and regional macroscopic attributes of pregnant and
lying-in women are realized by constructing a multi-source heterogeneous data fusion and regional feature quantification mechanism. The
system adopts a multi-protocol interface to access a
hospital information system, an environment monitoring platform and a health statistics
database, completes standardized cleaning and
integrated processing of cross-domain data, and converts multi-dimensional indexes such as regional environment, medical resources, social economy and the like into low-dimensional dense feature vectors through a macroscopic data aggregation and
ridge regression coding technology. The feature expression ability and the regional adaptability of the model are significantly enhanced, and effective data are provided for evaluating the risk of the innate structure anomaly of pregnant and
lying-in women under different geographical backgrounds.