CN115438040A - Pathological archive information management method and system - Google Patents
Pathological archive information management method and system Download PDFInfo
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Abstract
The invention provides a pathological archive information management method and system, and relates to the technical field of public health services, wherein the method comprises the following steps: building a pathological archive classification decision tree based on pathological archive information of a plurality of patients, classifying the pathological archive information of the plurality of patients, setting different completion adjustment rules based on classification results, and performing completion adjustment on the pathological archive information in the classification results to obtain standard pathological archive information; according to the classification result, presetting abnormal identification features to perform traversal retrieval on the standard pathological file information to obtain an abnormal retrieval pathological file set; and performing specificity analysis on the abnormal retrieval pathological file set, removing the corresponding pathological files, obtaining pathological file information to be stored, and performing chain storage according to classification results of the pathological file classification decision tree. The pathological archive management system solves the technical problems of inaccuracy and low efficiency of pathological archive management in the prior art.
Description
Technical Field
The invention relates to the technical field of public health services, in particular to a pathological archive information management method and system.
Background
The pathological file information is an important basis for doctors to diagnose the disease state of patients in modern medicine, is an important scientific research material for medical teaching and medical research, and is an effective evidence for division of responsibility when medical disputes occur. Due to the special status and importance of the pathological archive information in medical treatment, hospitals at all levels gradually invest a large amount of resources to keep the pathological archive information properly.
At present, the pathological archive information management mode generally performs filing and warehousing management of text data and non-text data by the archive management department of hospitals at all levels, and some hospitals introduce an electronic archive management system to improve the pathological archive management efficiency.
Due to the complexity of the pathological file data, the pathological file information management method in the prior art has the technical problems that the pathological file management of patients is not accurate enough and the efficiency is low, and the pathological file information of patients cannot be kept properly.
Disclosure of Invention
The application provides a pathological file information management method and a pathological file information management system, which are used for solving the technical problems that the pathological file management of patients is not accurate enough and the efficiency is low, and the pathological file information of the patients cannot be stored properly in the pathological file information management method in the prior art.
In view of the above problems, the present application provides a method and a system for managing pathological profile information.
In a first aspect of the present application, a pathological profile information management method is provided, where the method includes: acquiring pathological file information of a plurality of patients, and building a pathological file classification decision tree based on the pathological file information of the plurality of patients; classifying the pathological archive information of the plurality of patients according to the pathological archive classification decision tree to obtain a first classification result; setting different completion adjustment rules based on the first classification result, and performing completion adjustment on the pathological file information in the first classification result to obtain standard pathological file information; presetting an abnormal identification feature according to the first classification result, and performing traversal retrieval on the standard pathology archive information based on the abnormal identification feature to obtain a first abnormal retrieval pathology archive set; performing specificity analysis on the first abnormal retrieval pathology archive set to obtain a first removal instruction; removing the corresponding pathological archive based on the first removing instruction, and then obtaining pathological archive information to be stored; and performing chain storage on the pathological archive information to be stored according to the first classification result.
In a second aspect of the present application, there is provided a pathology archive information management system, the system including: the system comprises a first construction unit, a second construction unit and a third construction unit, wherein the first construction unit is used for acquiring pathological file information of a plurality of patients and building a pathological file classification decision tree based on the pathological file information of the plurality of patients; the first execution unit is used for classifying the pathological archive information of the plurality of patients according to the pathological archive classification decision tree to obtain a first classification result; the second execution unit is used for setting different completion adjustment rules based on the first classification result, and performing completion adjustment on the pathological archive information in the first classification result to obtain standard pathological archive information; the third execution unit is used for presetting an abnormal identification feature according to the first classification result, and performing traversal retrieval on the standard pathology archive information based on the abnormal identification feature to obtain a first abnormal retrieval pathology archive set; the first analysis unit is used for performing specificity analysis on the first abnormal retrieval pathology archive set to obtain a first removal instruction; the fourth execution unit is used for removing the corresponding pathological file based on the first removing instruction and then obtaining pathological file information to be stored; and the fifth execution unit is used for performing chain storage on the pathological archive information to be stored according to the first classification result.
In a third aspect of the present application, there is provided a pathology archive information management system including: a processor coupled to a memory, the memory storing a program that, when executed by the processor, causes a system to perform the steps of the method according to the first aspect.
In a fourth aspect of the present application, a computer-readable storage medium is provided, having stored thereon a computer program which, when being executed by a processor, carries out the steps of the method according to the first aspect.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
the method provided by the embodiment of the application builds the classification decision tree of the pathological files by acquiring the pathological file information of a plurality of patients; classifying the pathological archive information of the plurality of patients according to the pathological archive classification decision tree to obtain a first classification result; setting different completion adjustment rules based on the first classification result, and performing completion adjustment on the pathological archive information in the first classification result to obtain standard pathological archive information; presetting an abnormal identification feature according to the first classification result, and performing traversal retrieval on the standard pathology archive information based on the abnormal identification feature to obtain a first abnormal retrieval pathology archive set; performing specificity analysis on the first abnormal retrieval pathology archive set to obtain a first removal instruction; removing the corresponding pathological archive based on the first removing instruction, and then obtaining pathological archive information to be stored; and performing chain storage on the pathological archive information to be stored according to the first classification result. The pathological archive information classification method and the pathological archive classification system have the advantages that the pathological archive information of a plurality of patients is classified and divided by building the pathological archive classification decision tree, and the first classification result is obtained, so that pathological archives are clearly divided by taking disease types as the division principle. And by setting different completion adjustment rules, the pathological archive information in the first classification result is subjected to completion adjustment to obtain standard pathological archive information, so that the condition that the pathological archive content is invalid due to content deletion is avoided, and the defects of pathological archives are overcome. According to the first classification result, the abnormal identification features are preset, the standard pathological archive information is subjected to traversal retrieval based on the abnormal identification features, a first abnormal retrieval pathological archive set is obtained, abnormal items of the pathological archive information with complete contents are screened out, and the problem that the scientific value of the pathological archive is reduced when the abnormal items are extracted and used in subsequent pathological archives is avoided. Carry out the specificity analysis to first unusual retrieval pathology archives set, get rid of after corresponding pathology archives, obtain to wait to store pathology archives information and carry out the chain storage according to first classification result, the inquiry and the change of the data of being convenient for, and the pathology archives information of this pathology type that the morbidity is high and the fatality rate is high can be stored in comparatively node in the front, when the relevant pathology archives information of inquiry or modification disease, efficiency is very fast, can promote this application pathology archives information management system's work efficiency. The method avoids the wrong removal of difficult and complicated diseases and the privacy information of the patients, ensures the protection of the pathological archive information on the privacy of the patients, perfects and efficiently manages the difficult and complicated disease information, and improves the retrieval efficiency through chain storage. The technical effects of scientifically and efficiently performing content improvement and accurate management on the pathological file information and realizing proper storage of the pathological file information of patients are achieved.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Drawings
Fig. 1 is a schematic flow chart of a pathological profile information management method according to the present application;
fig. 2 is a schematic flow chart illustrating a first removing instruction obtained in the method for managing pathological profile information according to the present application;
fig. 3 is a schematic view illustrating a process for obtaining reference pathology file information in a pathology file information management method according to the present application;
FIG. 4 is a schematic diagram of a pathological profile information management system according to the present application;
fig. 5 is a schematic structural diagram of an exemplary electronic device of the present application.
Description of the reference numerals: the device comprises a first construction unit 11, a first execution unit 12, a second execution unit 13, a third execution unit 14, a first analysis unit 15, a fourth execution unit 16, a fifth execution unit 17, an electronic device 300, a memory 301, a processor 302, a communication interface 303 and a bus architecture 304.
Detailed Description
The application provides a pathological file information management method and system, which are used for solving the technical problems that the pathological file management of patients is not accurate enough and the efficiency is low, and the pathological file information of the patients cannot be kept properly in the pathological file information management method in the prior art.
Summary of the application
The pathological archive information has extremely high complexity, not only has the characteristics of large number, multiple categories and strong specialization, but also needs to consider the principles of filing and archiving modes, storage years and privacy when filing and storing, and also needs to consider the high-quality storage of non-literal data such as human tissues and the like.
In view of the above technical problems, the technical solution provided by the present application has the following general idea:
the method provided by the application builds a pathological archive classification decision tree by acquiring pathological archive information of a plurality of patients; classifying the pathological archive information of the plurality of patients according to the pathological archive classification decision tree to obtain a first classification result; setting different completion adjustment rules based on the first classification result, and performing completion adjustment on the pathological archive information in the first classification result to obtain standard pathological archive information; presetting an abnormal identification feature according to the first classification result, and performing traversal retrieval on the standard pathology archive information based on the abnormal identification feature to obtain a first abnormal retrieval pathology archive set; performing specificity analysis on the first abnormal retrieval pathology archive set to obtain a first removal instruction; based on the first removal instruction, removing the corresponding pathological file, and then obtaining pathological file information to be stored; and performing chain storage on the pathological archive information to be stored according to the first classification result.
Having described the basic principles of the present application, the following detailed description will be made in a clear and complete manner with reference to the accompanying drawings, and it is to be understood that the described embodiments are only a part of the embodiments of the present application, and not all embodiments of the present application, and that the present application is not limited by the exemplary embodiments described herein. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application. It should be further noted that, for the convenience of description, only some but not all of the elements relevant to the present application are shown in the drawings.
Example one
As shown in fig. 1, the present application provides a pathological profile information management method, including:
s100: acquiring pathological archive information of a plurality of patients, and building a pathological archive classification decision tree based on the pathological archive information of the plurality of patients;
specifically, the pathological archive information is literal and non-literal archive data such as characters, images, tissue sections, smears, wax lumps and the like which have legal effectiveness and have preservation value and are formed in the process of pathological diagnosis in a pathology department. Semantic analysis is carried out on the literal archive data in the pathological archive information to capture keywords, medical discipline features in the pathological archive information of the patients are obtained and serve as root node features, and the pathological archive classification decision tree is built according to the root node features and the pathological archive information of the patients. The pathological archive classification decision tree is a tree structure for classifying the pathological archive information of the patients, and comprises nodes and directed edges, the nodes are also divided into two types, namely internal nodes and leaf nodes, the internal nodes represent a feature and an attribute, the leaf nodes represent a specific classification, the root nodes are used for analyzing the character information parts of the pathological archive information of the patients to obtain a feature text with medical subject classification directivity, and the feature text can be used for classifying and storing medical subjects to which corresponding pathologies of the patients belong.
S200: classifying the pathological archive information of the plurality of patients according to the pathological archive classification decision tree to obtain a first classification result;
specifically, the first classification result is obtained by inputting the pathological profile information of the plurality of patients into the pathological profile classification decision tree for classification. The pathological archive information of a plurality of unordered patients can be preliminarily summarized and sorted according to the first classification result, so that the archive information in each classified pathological archive can be conveniently and directionally searched for missing and filled, and other pathological archive information of the same category is referred to or information of patients is directly acquired to complete the missing part in a jigsaw mode.
S300: setting different completion adjustment rules based on the first classification result, and performing completion adjustment on the pathological file information in the first classification result to obtain standard pathological file information;
specifically, the completion adjustment is to complete the text or non-text content missing part of the pathological profile information of several patients in each classification result. The completion adjustment rule is a specific listed project which needs to be subjected to missing completion. Analyzing whether the pathological archive information of each patient in the first classification result needs archive missing completion or not, determining a project needing information supplement as a completion adjustment rule, performing tissue extraction and inspection or direct inspection on the body of the patient by medical workers according to the completion adjustment rule to obtain a literal or non-literal pathological detection result, performing completion adjustment on the pathological archive information in the first classification result, and obtaining the pathological archive information after content missing completion, namely standard pathological archive information.
For example, after analyzing the first classification result, it is found that thyroid hormone information is missing in the pathological profile information of a hyperthyroidism patient in the medical discipline of endocrine, the completion adjustment rule set by the system is completion thyroid hormone detection result information, after obtaining the completion adjustment rule, the medical staff performs blood test according to the blood sample weight of the patient or extracts the blood sample of the patient to observe the patient in the hospital, and completes the missing pathological profile information of the patient according to the blood test result.
Specifically, the missing detection items can be obtained by establishing pathological detection items of various medical disciplines and traversing the actual pathological archive information of the patient through the pathological detection items, and the missing detection items can be used as completion adjustment rules, or the completion adjustment rules can be obtained in a modeling mode. In the specific implementation process, the method for obtaining the completion adjustment rule can be set according to actual needs, and the application is not limited herein.
S400: presetting an abnormal identification feature according to the first classification result, and performing traversal retrieval on the standard pathology archive information based on the abnormal identification feature to obtain a first abnormal retrieval pathology archive set;
specifically, the pathological diagnosis method for the patient comprises the steps of presetting the disease type of the patient according to diagnosis and treatment experience, obtaining a perspective image of a body part of the patient or a blood routine detection based on a modern medical detection means to obtain a plurality of physiological indexes, comparing a standard diseased image of a disease with a blood routine threshold value according to the actually obtained image or blood routine index, and judging that the patient suffers from the disease if the actual result falls into the standard result threshold value range. It should be understood that, when the pathological profile information of the patient is systematically recorded, part of the information is abnormal due to input errors or management failure.
The abnormal recognition features are standard images and blood routine threshold values of specific diseases in each classification result. When the actual medical image or blood routine of the patient does not meet the abnormal identification characteristics of the corresponding disease, the pathological file information of the patient needs to be modified and corrected, and the pathological file information management system is re-entered.
And traversing and retrieving the actual pathological archive information of the patient according to the abnormality identification characteristics, and screening the abnormal pathological archive that the actual medical image of the patient does not meet the standard image or the blood routine numerical value deviates from the threshold range, namely the first abnormal retrieval pathological archive set.
The patient pathology archive information with complete information completion is screened for the wrong pathology archive by presetting the abnormal recognition features, so that medical accidents caused by the fact that doctors refer to the wrong pathology archive to perform follow-up treatment on patients who are not cured are avoided, and the technical effect of improving the accuracy of warehousing information of the pathology archive library is achieved.
S500: performing specificity analysis on the first abnormal retrieval pathology archive set to obtain a first removal instruction;
in particular, it will be appreciated that there are two possibilities that the patient's pathology profile does not meet the standard disorder condition threshold, one being a profile entry error, and the other being a special case of the disease. Therefore, abnormal pathological files need to be screened out and analyzed, and difficult and complicated pathological files are recovered to a standard pathological file set. It should be understood that the pathology file is the individual privacy of the patient, and in order to avoid the disclosure of the privacy information of the patient, the pathology file information of the patient needs to be deleted in a classified manner.
The first removing instruction is an information deleting instruction after the obtained first abnormal retrieval pathology archive set is subjected to specificity analysis. And the pathology archive management system records the privacy information of the wrong patient and the disease information of the wrong patient into the pathology archive information based on the first removal instruction and safely deletes the privacy information and the disease information of the wrong patient. By performing specificity analysis on the first abnormal retrieval pathological file set, the pathological files of difficult and complicated diseases are prevented from being misjudged as information input errors, and the technical effect of improving the information accuracy of pathological file management is achieved.
S600: based on the first removal instruction, removing the corresponding pathological file, and then obtaining pathological file information to be stored;
specifically, the pathology file information management system removes wrong pathology file information in the first abnormal retrieval pathology file set based on the first removal instruction, and recovers the difficult and complicated pathology file information in the first abnormal retrieval pathology file set. The pathological file information to be stored is a set formed by removing the standard pathological file information of the first abnormal retrieval pathological file set and the pathological file information of the difficult and complicated disease recovered from the first abnormal retrieval pathological file set.
S700: and performing chain storage on the pathological archive information to be stored according to the first classification result.
Specifically, in this embodiment, according to the first classification result, the pathological file information to be stored is stored in a chain manner, which can reduce the requirement for a single storage space, and the data modification is efficient and fast when the patient performs a plurality of disease review and assay tests.
The chain storage comprises a plurality of storage nodes, and each node can be used for storing all or at least part of pathological file information of a student. Because the data needs to be searched one by one from the head node when the data is searched and modified in the chained storage, the searching efficiency of the data in the node behind is low. Therefore, according to the morbidity and the mortality characteristics, the pathological file information of the patient is stored in different nodes in the chain type storage.
Optionally, the pathological file information of the pathological type with high morbidity and high mortality can be stored in the front node in the chained storage, and the pathological file information of the pathological type with low morbidity and low mortality can be stored in the rear node in the chained storage. Therefore, when the relevant pathological archive information of the patient is inquired or modified, the efficiency is high, and the working efficiency of the pathological archive information management system can be improved.
The pathological archive information classification method and the pathological archive classification system have the advantages that the pathological archive information of a plurality of patients is classified and divided by building the pathological archive classification decision tree, and the first classification result is obtained, so that pathological archives are clearly divided by taking disease types as the division principle. And by setting different completion adjustment rules, the pathological archive information in the first classification result is subjected to completion adjustment to obtain standard pathological archive information, so that the condition that the pathological archive content is invalid due to content deletion is avoided, and the defects of pathological archives are overcome. According to the first classification result, the abnormal identification features are preset, the standard pathological archive information is subjected to traversal retrieval based on the abnormal identification features, a first abnormal retrieval pathological archive set is obtained, abnormal items of the pathological archive information with complete contents are screened out, and the problem that the scientific value of the pathological archive is reduced when the abnormal items are extracted and used in subsequent pathological archives is avoided. Carry out the specificity analysis to first unusual retrieval pathology archives set, get rid of after corresponding pathology archives, obtain to wait to store pathology archives information and carry out the chain storage according to first classification result, the inquiry and the change of the data of being convenient for, and the pathology archives information of this pathology type that the morbidity is high and the fatality rate is high can be stored in comparatively node in the front, when the relevant pathology archives information of inquiry or modification disease, efficiency is very fast, can promote this application pathology archives information management system's work efficiency. The method avoids the wrong removal of difficult and complicated diseases and the privacy information of the patients, and ensures the protection of the pathological archive information on the privacy of the patients, the perfection of the difficult and complicated disease information and the efficient management. The technical effects of scientifically and efficiently performing content improvement and accurate management on the pathological file information and realizing the proper storage of the pathological file information of the patient are achieved.
Further, based on the first classification result, different completion adjustment rules are set, and the pathological profile information in the first classification result is subjected to completion adjustment to obtain standard pathological profile information, where step S300 of the method provided by the present application further includes:
s310: building a multi-logic-layer standardized model, wherein the multi-logic-layer standardized model comprises an input layer, a classification layer, a feature extraction layer, a hiding layer and an output layer;
s320: sequentially inputting the first classification result into the multi-logic-layer standardized model to obtain a first output result set, wherein the first output result set is a completion adjustment rule set;
s330: and correspondingly adjusting the first classification result based on the completion adjustment rule set to obtain the standard pathological archive information.
Specifically, the corresponding adjustment of the first classification result needs to be adjusted according to an accurate completion adjustment rule, and since the multi-logic-layer standardized model is a model with multiple logic layers which can be continuously self-trained and learned according to different actual conditions, the multi-logic-layer standardized model is simply a mathematical model, and an input layer and an output layer of the model are fixed. And training a classification layer, a feature extraction layer and a hidden layer of the multi-logic-layer standardized model layer by layer based on a large amount of training data. The classification layer divides pathological archive information into text information and non-text information, the specific text information comprises information such as cases, blood examination results and urine examination results, the non-text information comprises CT images and X-ray images, and the human tissue slice archive is processed digitally. The feature extraction layer performs semantic recognition feature extraction on the literal file information according to the pathological file information classification result of the classification layer, and performs image feature comparison extraction on the non-literal content. And the hidden layer analyzes and processes the extraction result of the feature extraction layer, determines the content which needs to be subjected to completion adjustment in each classification result, forms a feature completion adjustment rule set and outputs the feature completion adjustment rule set by the output layer.
Each set of training data in the training data for training the classification layer includes: pathological file information of a plurality of patients, literal and non-literal classification features of the pathological file information and identification information used for marking file feature classification results, wherein the neural network model is continuously corrected by self, and when the output information of the neural network model reaches a preset accuracy rate/reaches a convergence state, the supervised learning process is ended. Each set of training data in the training data for training the feature extraction layer includes: the pathological archive information classification result, the literal archive information and the non-literal archive information feature extraction method of the classification layer and the identification information used for marking the literal archive information and the non-literal archive information feature extraction result are used for continuously self-correcting the neural network model, and when the output information of the neural network model reaches a preset accuracy rate/reaches a convergence state, the supervised learning process is ended. Each set of training data in the training data for training the hidden layer includes: the characteristic extraction result of the literal file information and the non-literal file information of the characteristic extraction layer, the traversal completion adjustment rule and the identification information for completing the adjustment rule set are continuously corrected by the neural network model, and when the output information of the neural network model reaches the preset accuracy rate/reaches the convergence state, the supervised learning process is ended.
The data training is carried out on the plurality of logic layers of the multi-logic-layer standardized model, and according to the characteristic that the data of the trained model is more accurate, the completion adjustment rule set output by the multi-logic-layer standardized model is more accurate, so that the first classification result is accurately adjusted, the missing information of the pathological archive information in each classification result is accurately supplemented, and the technical effect of standard pathological archive information is achieved.
Further, as shown in fig. 2, the performing specificity analysis on the first abnormality retrieval pathology archive set to obtain a first removal instruction further includes, in step S500 of the method provided by the present application:
s510: constructing a three-dimensional space coordinate system according to the storage form information, the rare file information and the file authority information;
s520: inputting the first abnormal retrieval pathology archive set into the three-dimensional space coordinate system;
s530: obtaining a characteristic image set of the first abnormal retrieval pathology archive set;
s540: presetting particularity evaluation vector information;
s550: obtaining a first specificity analysis result according to the feature image set and the preset specificity evaluation vector information;
s560: obtaining the first removal instruction based on the first specificity analysis result.
Specifically, the first abnormal retrieval pathology archive set is not directly removed, specificity analysis is firstly performed, and part of pathology archive information meeting the requirement of the specificity analysis is recovered, wherein the specific specificity analysis comprises storage form analysis, archive rare analysis and archive authority analysis. Illustratively, if a tumor section of a certain neoplastic condition is in an extremely standardized form and is well preserved for use in medical teaching and research experiments, the preserved form of the tumor section is considered to meet the requirements of a specific analysis and should be recycled and not disposed of as medical waste. If a certain disease is rare or no cure method exists, the pathological archive information of the disease is stored to be beneficial to subsequent medical teaching and scientific research experiments, and the archive is considered to meet the requirement of specificity analysis due to rareness and is not recovered as a failure archive to be destroyed. All patient's privacy information has high sensitivity, forbids any individual to obtain it, can not simply delete patient's privacy, needs the thorough formatting processing of technical staff.
And constructing a three-dimensional space coordinate system by using the stored form information, the file rare information and the file authority information. Inputting the three-dimensional space coordinate system into the first abnormal retrieval pathology archive set; obtaining a characteristic image set of the first abnormal retrieval pathology archive set; the assignment standard of the specificity evaluation vector information is preset, and the specific assignment value can be obtained by referring to the assignment standard in the prior art or through an expert analysis method. Obtaining a first specificity analysis result according to the feature image set and the preset specificity evaluation vector information; outputting a first removing instruction, removing wrong pathology archive information in the first abnormal retrieval pathology archive set, and recovering pathology archive information which meets storage form feature analysis, archive rare feature analysis and archive authority feature analysis in the first abnormal retrieval pathology archive set.
Through carrying out characteristic analysis to first unusual retrieval pathology archives set, retrieve and be judged as the pathology archives information of content mistake and have the pathology archives content that the risk was revealed to patient's privacy, reached and avoided having the pathology archives data loss of scientific research value and revealing of patient's privacy, improve the medical value of pathology archives information management and the technological effect of security attribute.
Further, as shown in fig. 3, the method provided by the present application further includes:
s810: acquiring first user attribute information;
s820: based on the first user attribute information and the first classification result, performing attribute association degree analysis to obtain a first association degree analysis result;
s830: according to the first relevance analysis result, carrying out weight distribution on the first classification result to obtain a first weight distribution result;
s840: and performing weighted calculation according to the first weight distribution result to obtain reference pathological archive information.
Specifically, the first user is a specific patient in an outpatient service, and the first user attribute information includes the age, weight, past medical history of the first user and specific characteristic information of a current disease state. And performing attribute association degree analysis on the first user attribute information and the first classification result, determining the similarity degree between the current disease of the first user and each type of disease of the first classification result, and outputting the first association analysis result. And according to different body reflection conditions and different reflection strengths of different diseases under the same medical department, performing weight distribution on the first classification result according to a first association degree analysis result to obtain a first weight distribution result. And performing weighted calculation according to the first weight distribution result to obtain reference pathological archive information, and determining which type of symptoms can be referred to when judging the state of illness of the first user so as to improve the accuracy of patient diagnosis.
The pathological characteristics of the patients in the current outpatient clinic are associated with the historical pathological files in the pathological file information management library, so that the pathological file information of the hospital is fully utilized, and the technical effects of improving the accuracy of judging the illness state of the patients in outpatient clinic treatment and optimizing the current treatment scheme of the patients are achieved.
Further, the to-be-stored pathological archive information is stored in a chain manner according to the first classification result, and step S700 of the method provided by the present application further includes:
s710: constructing a circulating chain type storage chain, wherein the circulating chain type storage chain comprises a plurality of storage nodes;
s720: according to the morbidity and mortality of the disease information corresponding to the pathological archive information to be stored, carrying out weight distribution to obtain a second weight distribution result;
s730: according to the second weight distribution result, carrying out storage node distribution to obtain a node distribution result;
and S740: and according to the node distribution result, performing chain storage on the pathological archive information to be stored and the corresponding archive acquisition time information.
Further, in the step S710 of constructing the endless chain type storage chain, the method provided by the present application further includes: s711: constructing a head node of the chained storage based on the chained storage, wherein the head node comprises a head pointer;
s712: according to the head pointer, sequentially constructing other multiple storage nodes till a tail node, wherein the other multiple storage nodes comprise node pointers and node data spaces;
s713: and connecting the head node and the tail node according to the node pointer and the head pointer in the tail node to obtain the circular chain type storage chain.
Specifically, based on the principle of chained storage, a head node of chained storage is constructed, and in the present application, data is not stored in the head node, but only a head pointer is included to point to a next node.
And according to the pointing address of the head pointer in the head node, sequentially constructing a plurality of other nodes for storing data, wherein the number of the nodes is related to the specific classification number in the first classification result, and the nodes can be constructed or deleted when the classification result of the pathology archive is newly added in the follow-up process. The other nodes comprise node pointers and node data spaces, the node data spaces are used for storing pathological file information of the patient, and the node pointers are used for pointing to the nodes next to the current nodes.
And according to node pointers in tail nodes in the plurality of storage nodes, the node pointers point to the head nodes, and the head nodes and the tail nodes are connected to obtain the circular chain type storage chain. Therefore, data access and modification can be carried out from the tail node, the efficiency of data access can be improved for data behind the storage node, and the access efficiency of the data in the middle part of the cyclic chain type storage chain is not changed and is lower than the nodes close to the head node and the tail node.
After the circulating chain type storage chain is constructed, weight distribution is carried out according to the morbidity and the mortality of the disease information corresponding to the pathological archive information to be stored, and optionally, in the specific distribution process, the weight value of the disease information with higher morbidity and mortality is larger, and the weight value of the disease information with lower morbidity and mortality is smaller. Thus, the weight distribution is completed, and a second weight distribution result is obtained.
And distributing storage nodes to the pathological archive information of the plurality of patients according to the second weight distribution result, wherein in the specific distribution process, the larger the weight value is, the closer the distributed storage nodes are to the head node or the tail node, and the storage nodes are distributed according to the sorting of the weight values to finish the distribution of the storage nodes of the pathological management information of the plurality of patients so as to obtain the node distribution result.
And according to the node distribution result, performing chain storage on the pathological management information of the plurality of patients, and storing the pathological management information into the corresponding nodes obtained by distribution. Therefore, the pathological archive information with high morbidity and mortality can be stored into the storage node with higher query efficiency.
Further, the method provided by the present application further includes:
s750: analyzing the storage life of the pathological archive information to be stored to obtain a first time period set;
s760: obtaining a set of drop time nodes based on the first set of time periods;
s770: traversing and searching the circular chain type storage chain based on the discarding time node set to obtain discarding node information;
s780: updating the cyclical chained storage chain based on the discarded node information.
Specifically, according to the "guidelines for construction and management of pathological department" issued by the Ministry of health, the shelf life of pathological sections, wax lumps, and positive smears is 15 years, the shelf life of negative smears is 1 year, and the shelf life of tissue specimens is 2 weeks after the report is issued. Therefore, the management personnel of the pathological file information should timely clear the data which has reached the deadline and register the data for record, but for the special pathological file data (such as the difficult and complicated pathological file information and the patient privacy information which are recovered from the first abnormal retrieval pathological file set in the application), the management personnel can individually process the data, including long-term storage and complete deletion.
The first time period set is a retention time requirement set of different types of pathological archive information, and the pathological archive information to be stored is analyzed for retention period to obtain a first time period set; obtaining a set of drop time nodes based on the first set of time periods; traversing and searching the circular chain type storage chain based on the discarding time node set to obtain discarding node information; and updating the circulating chain type storage chain based on the discarded node information, and removing overdue pathological file information.
Through analyzing the link-in time of the current storage pathology archive information in the circulating chain type storage chain, the invalid pathology archive information reaching the failure time limit is removed in real time, so that the unnecessary storage space consumption caused by the extrusion of the invalid pathology archive in the archive is avoided, and the technical effects of improving the operating efficiency and the storage space utilization rate of the pathology archive information base are achieved.
Example two
Based on the same inventive concept as one of the pathological profile information management methods in the foregoing embodiments, as shown in fig. 4, the present application provides a pathological profile information management system, wherein the system includes:
the first construction unit 11 is configured to acquire pathological archive information of a plurality of patients and build a pathological archive classification decision tree based on the pathological archive information of the plurality of patients;
the first execution unit 12 is configured to classify the pathological archive information of the plurality of patients according to the pathological archive classification decision tree to obtain a first classification result;
a second executing unit 13, configured to set different completion adjustment rules based on the first classification result, and perform completion adjustment on the pathology file information in the first classification result to obtain standard pathology file information;
a third executing unit 14, configured to preset an abnormal identification feature according to the first classification result, and perform traversal retrieval on the standard pathology archive information based on the abnormal identification feature to obtain a first abnormal retrieval pathology archive set;
a first analysis unit 15, configured to perform specificity analysis on the first anomaly retrieval pathology archive set to obtain a first removal instruction;
a fourth execution unit 16, configured to obtain pathological file information to be stored after removing the corresponding pathological file based on the first removal instruction;
and a fifth execution unit 17, configured to perform chain storage on the pathological archive information to be stored according to the first classification result.
Further, the system further comprises:
the second construction unit is used for constructing a multi-logic-layer standardized model, and the multi-logic-layer standardized model comprises an input layer, a classification layer, a feature extraction layer, a hiding layer and an output layer;
a sixth execution unit, configured to input the first classification result into the multi-logic-layer standardized model in sequence to obtain a first output result set, where the first output result set is a completion adjustment rule set;
and the first adjusting unit is used for correspondingly adjusting the first classification result based on the completion adjusting rule set to obtain the standard pathological archive information.
Further, the system further comprises:
the third construction unit is used for constructing a three-dimensional space coordinate system according to the storage form information, the rare file information and the file authority information;
a seventh execution unit, configured to input the first abnormality retrieval pathology archive set into the three-dimensional space coordinate system;
a first obtaining unit, configured to obtain a feature image set of the first abnormality retrieval pathology archive set;
the eighth execution unit is used for presetting the specificity evaluation vector information;
the second obtaining unit is used for obtaining a first specificity analysis result according to the feature image set and the preset specificity evaluation vector information;
a third obtaining unit, configured to obtain the first removal instruction based on the first uniqueness analysis result.
Further, the system further comprises:
a fourth obtaining unit, configured to obtain first user attribute information;
the second analysis unit is used for carrying out attribute association degree analysis based on the first user attribute information and the first classification result to obtain a first association degree analysis result;
a ninth execution unit, configured to perform weight distribution on the first classification result according to the first relevance analysis result, so as to obtain a first weight distribution result;
and the tenth execution unit is used for performing weighting calculation according to the first weight distribution result to obtain reference pathological archive information.
Further, the system further comprises:
the fourth construction unit is used for constructing a circulating chain type storage chain, wherein the circulating chain type storage chain comprises a plurality of storage nodes;
the eleventh execution unit is used for performing weight distribution according to the morbidity and mortality of the disease information corresponding to the pathological archive information to be stored to obtain a second weight distribution result;
a twelfth execution unit, configured to perform storage node allocation according to the second weight allocation result, to obtain a node allocation result;
and the thirteenth execution unit is used for performing chain storage on the pathological archive information to be stored and the corresponding archive acquisition time information according to the node distribution result.
Further, the system further comprises:
the fifth construction unit is used for constructing head nodes of the chained storage based on the chained storage, and the head nodes comprise head pointers;
a sixth construction unit, configured to sequentially construct, according to the head pointer, other multiple storage nodes until a tail node, where the other multiple storage nodes all include node pointers and node data spaces;
and the fourteenth execution unit is used for connecting the head node and the tail node according to the node pointer and the head pointer in the tail node to obtain the circular chain type storage chain.
Further, the system further comprises:
the third analysis unit is used for analyzing the storage life of the pathological archive information to be stored to obtain a first time period set;
a fifteenth performing unit, configured to obtain a set of discarded time nodes based on the first set of time periods;
a fifth obtaining unit, configured to search the circular chain storage chain in a traversal manner based on the discarded time node set, so as to obtain discarded node information;
a sixteenth execution unit, configured to update the cyclic chain storage chain based on the discarded node information.
EXAMPLE III
Based on the same inventive concept as one of the pathological profile information management methods in the foregoing embodiments, the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as in the first embodiment.
Exemplary electronic device
The electronic device of the present application is described below with reference to fig. 5.
Based on the same inventive concept as the pathological archive information management method in the foregoing embodiment, the present application also provides a pathological archive information management system, including: a processor coupled to a memory, the memory for storing a program that, when executed by the processor, causes the system to perform the steps of the method of embodiment one.
The electronic device 300 includes: processor 302, communication interface 303, memory 301. Optionally, the electronic device 300 may also include a bus architecture 304. Wherein, the communication interface 303, the processor 302 and the memory 301 may be connected to each other through a bus architecture 304; the bus architecture 304 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus architecture 304 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 5, but that does not indicate only one bus or one type of bus.
The memory 301 may be, but is not limited to, ROM or other type of static storage device that can store static information and instructions, RAM or other type of dynamic storage device that can store information and instructions, EEPROM, CD-ROM or other optical disk storage, optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. The memory may be self-contained and coupled to the processor through a bus architecture 304. The memory may also be integral to the processor.
The memory 301 is used for storing computer-executable instructions for executing the present application, and is controlled by the processor 302 to execute. The processor 302 is configured to execute the computer executable instructions stored in the memory 301, so as to implement a pathology file information management method provided in the above embodiment of the present application.
Those of ordinary skill in the art will understand that: the various numbers of the first, second, etc. mentioned in this application are for convenience of description and are not intended to limit the scope of this application nor to indicate the order of precedence. "and/or" describes the association relationship of the associated object, indicating that there may be three relationships, for example, a and/or B, which may indicate: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one" means one or more. At least two means two or more. "at least one," "any," or similar expressions refer to any combination of these items, including any combination of item(s) or item(s). For example, at least one (one ) of a, b, or c, may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or multiple.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, it may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the procedures or functions described in accordance with the present application are generated, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device including one or more available media integrated servers, data centers, and the like. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid State Disk (SSD)), among others.
The various illustrative logical units and circuits described in this application may be implemented or operated upon by design of a general purpose processor, a digital signal processor, an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration.
The steps of a method or algorithm described in this application may be embodied directly in hardware, in a software element executed by a processor, or in a combination of the two. The software cells may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. For example, a storage medium may be coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, which may be disposed in a terminal. In the alternative, the processor and the storage medium may reside in different components within the terminal. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Although the present application has been described in conjunction with specific features and embodiments thereof, it will be evident that various modifications and combinations may be made thereto without departing from the spirit and scope of the application. Accordingly, the specification and figures are merely exemplary of the application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of the application. It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the present application and its equivalent technology, it is intended that the present application include such modifications and variations.
Claims (10)
1. A pathology archive information management method, comprising:
acquiring pathological file information of a plurality of patients, and building a pathological file classification decision tree based on the pathological file information of the plurality of patients;
classifying the pathological archive information of the plurality of patients according to the pathological archive classification decision tree to obtain a first classification result;
setting different completion adjustment rules based on the first classification result, and performing completion adjustment on the pathological file information in the first classification result to obtain standard pathological file information;
presetting an abnormal identification feature according to the first classification result, and performing traversal retrieval on the standard pathology archive information based on the abnormal identification feature to obtain a first abnormal retrieval pathology archive set;
performing specificity analysis on the first abnormal retrieval pathology archive set to obtain a first removal instruction;
removing the corresponding pathological archive based on the first removing instruction, and then obtaining pathological archive information to be stored;
and performing chain storage on the pathological archive information to be stored according to the first classification result.
2. The method according to claim 1, wherein different completion adjustment rules are set based on the first classification result, and completion adjustment is performed on the pathology file information in the first classification result to obtain standard pathology file information, and the method further comprises:
building a multi-logic-layer standardized model, wherein the multi-logic-layer standardized model comprises an input layer, a classification layer, a feature extraction layer, a hiding layer and an output layer;
sequentially inputting the first classification result into the multi-logic-layer standardized model to obtain a first output result set, wherein the first output result set is a completion adjustment rule set;
and correspondingly adjusting the first classification result based on the completion adjustment rule set to obtain the standard pathological archive information.
3. The method of claim 1, wherein said performing a specificity analysis on said first set of abnormality retrieval pathology files to obtain a first removal instruction, further comprises:
constructing a three-dimensional space coordinate system according to the storage form information, the rare file information and the file authority information;
inputting the first abnormal retrieval pathology file set into the three-dimensional space coordinate system;
obtaining a characteristic image set of the first abnormal retrieval pathology archive set;
presetting particularity evaluation vector information;
obtaining a first specificity analysis result according to the feature image set and the preset specificity evaluation vector information;
obtaining the first removal instruction based on the first specificity analysis result.
4. The method according to claim 1, wherein the pathological profile information to be stored is stored in a chain manner according to the first classification result, and thereafter, the method further comprises:
acquiring first user attribute information;
based on the first user attribute information and the first classification result, performing attribute association degree analysis to obtain a first association degree analysis result;
according to the first correlation degree analysis result, carrying out weight distribution on the first classification result to obtain a first weight distribution result;
and performing weighting calculation according to the first weight distribution result to obtain reference pathological archive information.
5. The method of claim 1, further comprising:
constructing a circulating chain type storage chain, wherein the circulating chain type storage chain comprises a plurality of storage nodes;
according to the morbidity and mortality of the disease information corresponding to the pathological archive information to be stored, carrying out weight distribution to obtain a second weight distribution result;
according to the second weight distribution result, carrying out storage node distribution to obtain a node distribution result;
and according to the node distribution result, performing chain storage on the pathological archive information to be stored and the corresponding archive acquisition time information.
6. The method of claim 5, wherein the building of endless chain storage chains, the method further comprises:
constructing a head node of the chained storage based on the chained storage, wherein the head node comprises a head pointer;
according to the head pointer, other multiple storage nodes are sequentially constructed until a tail node, and each of the other multiple storage nodes comprises a node pointer and a node data space;
and connecting the head node and the tail node according to the node pointer and the head pointer in the tail node to obtain the circular chain type storage chain.
7. The method of claim 6, further comprising:
analyzing the storage life of the pathological archive information to be stored to obtain a first time period set;
obtaining a set of drop time nodes based on the first set of time periods;
traversing and searching the circular chain type storage chain based on the discarding time node set to obtain discarding node information;
updating the cyclical chained storage chain based on the discarded node information.
8. A pathology archive information management system, characterized in that the system comprises:
the system comprises a first construction unit, a second construction unit and a third construction unit, wherein the first construction unit is used for acquiring pathological file information of a plurality of patients and building a pathological file classification decision tree based on the pathological file information of the plurality of patients;
the first execution unit is used for classifying the pathological archive information of the plurality of patients according to the pathological archive classification decision tree to obtain a first classification result;
the second execution unit is used for setting different completion adjustment rules based on the first classification result, and performing completion adjustment on the pathological archive information in the first classification result to obtain standard pathological archive information;
the third execution unit is used for presetting an abnormal identification feature according to the first classification result, and performing traversal retrieval on the standard pathology archive information based on the abnormal identification feature to obtain a first abnormal retrieval pathology archive set;
the first analysis unit is used for performing specificity analysis on the first abnormal retrieval pathology archive set to obtain a first removal instruction;
the fourth execution unit is used for removing the corresponding pathological file based on the first removing instruction and then obtaining pathological file information to be stored;
and the fifth execution unit is used for performing chain storage on the pathological archive information to be stored according to the first classification result.
9. A pathology archive information management system, comprising: a processor coupled to a memory, the memory for storing a program that, when executed by the processor, causes a system to perform the steps of the method of any of claims 1 to 7.
10. A computer-readable storage medium, characterized in that the storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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| CN202210469421.3A CN115438040A (en) | 2022-04-28 | 2022-04-28 | Pathological archive information management method and system |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116756089A (en) * | 2023-08-21 | 2023-09-15 | 湖南云档信息科技有限公司 | File archiving scheme forming method, system and storage medium |
| CN117216002A (en) * | 2023-08-30 | 2023-12-12 | 广州金域医学检验中心有限公司 | Intelligent pathological resource archiving method and device, electronic equipment and storage medium |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116756089A (en) * | 2023-08-21 | 2023-09-15 | 湖南云档信息科技有限公司 | File archiving scheme forming method, system and storage medium |
| CN116756089B (en) * | 2023-08-21 | 2023-11-03 | 湖南云档信息科技有限公司 | File archiving scheme forming method, system and storage medium |
| CN117216002A (en) * | 2023-08-30 | 2023-12-12 | 广州金域医学检验中心有限公司 | Intelligent pathological resource archiving method and device, electronic equipment and storage medium |
| CN117216002B (en) * | 2023-08-30 | 2024-04-09 | 太原金域临床检验所有限公司 | Intelligent pathological resource archiving method and device, electronic equipment and storage medium |
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