Method and system for automatic classification of medical data elements based on depth map matching
A technology of medical data and classification methods, applied in other database clustering/classification, file management systems, other database retrieval, etc., can solve problems such as difficult maintenance and long data interface development time
Active Publication Date: 2022-04-08
ZHEJIANG LAB
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Problems solved by technology
[0007] During the construction of the medical big data center, problems such as local data swamps in medical institutions generally exist, resulting in long data interface development time and difficult maintenance
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[0075] In order to make the above objects, features and advantages of the present invention more comprehensible, specific implementations of the present invention will be described in detail below in conjunction with the accompanying drawings.
[0076] In the following description, a lot of specific details are set forth in order to fully understand the present invention, but the present invention can also be implemented in other ways different from those described here, and those skilled in the art can do it without departing from the meaning of the present invention. By analogy, the present invention is therefore not limited to the specific examples disclosed below.
[0077] The terms involved in the present invention are first described below:
[0078] Metadata: Data that describes other data. Metadata is data about data. Sometimes it does not specifically refer to a single data. It can be understood as a set of information groups / data groups used to describe data. All dat...
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The invention discloses a method and system for automatically classifying medical data elements based on depth map matching. The invention defines a medical data element map data model based on minimum metadata information, so that the effect of the depth map matching model is also applicable to extremely low elements. The local data swamp of data information achieves the purpose of using the least metadata information to complete the automatic classification of data elements, and at the same time ensures that the graph structure data collected under the graph data model standard is suitable for the training of the deep graph matching model; based on the representation learning method Calculate the vector representation of medical data elements, and quickly and automatically screen effective data elements that may be mapped to the standard data model through the classification of vector representations; calculate the vector representation of column vertices based on the graph attention mechanism, and build a deep graph matching model to complete the medical data Automated classification of meta. The method and system of the present invention have good expandability, and can be applied to the processing of converting various data swamps into data lakes.
Description
technical field [0001] The invention belongs to the field of regional medical big data centers and data production platforms, and in particular relates to an automatic classification method and system for medical data elements based on depth map matching. Background technique [0002] With the construction and development of medical informatization, the combination of big data and medical services has promoted the continuous improvement of smart medical technology. At present, smart medical care has begun to take shape. Regional medical institutions form a medical consortium or a medical community and build a unified medical big data center, which has become an inevitable trend in the development of the subsequent smart medical data governance system. However, the information platforms, software, and systems with complex structures in different forms of medical institutions make it impossible to realize data sharing and interaction between different institutional platforms, ...
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IPC IPC(8): G06F16/906G06F16/901G06F16/93
CPCG06F16/906G06F16/9024G06F16/93
Inventor 李劲松辛然杨宗峰李玉格孙慧瑶周天舒田雨
Owner ZHEJIANG LAB