CN112466456A - Intelligent medical fault processing method combining visit data transmission and cloud server - Google Patents
Intelligent medical fault processing method combining visit data transmission and cloud server Download PDFInfo
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- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/40—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
- G16H40/67—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
Abstract
The application relates to an intelligent medical fault processing method and a cloud server combined with treatment data transmission. First, when it is detected that there is the failure indication information, a failure trace map is generated based on the failure indication information. And secondly, determining first identity information from the received visit data and determining second identity information from the fault prompt information. And then, when the first identity information and the second identity information are the same, the diagnosis data determined as the rechecking data are transmitted based on the fault track map so as to realize the on-line rechecking of the intelligent medical equipment with faults, when the first identity information and the second identity information are different, the transmission direction information except the fault track map is determined, the diagnosis data determined as the normal data are transmitted based on the transmission direction information, and the diagnosis data of the patient cannot be received when the intelligent medical equipment is in a fault detection state. Thus, when fault detection is carried out on the intelligent medical equipment, the treatment data can be accurately processed.
Description
Technical Field
The application relates to the technical field of intelligent medical treatment, in particular to an intelligent medical treatment fault processing method and a cloud server combining visit data transmission.
Background
With the rapid development of science and technology, the increasing maturity of intelligent medical treatment provides a great deal of convenience for patients to seek medical advice, so that the waiting time of the patients is greatly shortened, and the workload of medical workers is effectively reduced. In some large hospitals, a large number of intelligent medical devices are typically provided to enable the processing of patient visit data. However, when some intelligent medical devices are out of order and need to be subjected to fault detection, the following two technical problems exist: for the first technical problem, if the visit data is transmitted to the intelligent medical device in the fault detection state, the visit data may not be accurately processed, which delays the visit of the patient; the second technical problem is that if the intelligent medical equipment which completes the fault repair but does not complete the review and detection is put into use again, the data of the doctor will be processed wrongly. In summary, at present, the data of medical treatment cannot be correctly processed when the intelligent medical equipment is subjected to fault detection.
Disclosure of Invention
The application provides an intelligent medical fault processing method and a cloud server which are combined with treatment data transmission, so that the technical problems in the prior art are solved.
The intelligent medical fault processing method combined with treatment data transmission is applied to a cloud server which is communicated with a device cluster in an intelligent medical fault processing system, and comprises the following steps:
judging whether the visit data is received in real time; if the visit data is received, detecting whether fault prompt information exists or not, and generating a fault track map based on the fault prompt information under the condition that the fault prompt information exists; the fault trace graph is formed by intelligent medical equipment for transmitting rechecking data, the fault trace graph comprises a plurality of equipment nodes, each equipment node corresponds to one intelligent medical equipment, and each corresponding intelligent medical equipment in the fault trace graph is in a different equipment cluster;
determining first identity information from the visit data and second identity information from the fault prompt information; the second identity information is identity information corresponding to preset rechecking data;
matching the first identity information with the second identity information to obtain a matching result;
when the matching result represents that the first identity information and the second identity information are the same, transmitting the visit data based on the fault track map;
and when the matching result represents that the first identity information and the second identity information are different, determining transfer direction information except the fault track graph, and transferring the visit data based on the transfer direction information.
Preferably, the step of transmitting the visit data based on the fault track map comprises:
transmitting the visit data to a first intelligent medical device corresponding to a first device node in the fault track map;
and enabling the first intelligent medical equipment to transmit the treatment data to the next intelligent medical equipment of the first intelligent medical equipment according to the comparison result between the preset third identity information and the first identity information in the treatment data.
Preferably, the step of enabling the first intelligent medical device to transmit the visit data to a next intelligent medical device of the first intelligent medical device according to a comparison result between the preset third identity information and the first identity information in the visit data includes:
when the comparison result represents that the third identity information is the same as the first identity information, enabling the first intelligent medical equipment to transmit the clinic data to the target intelligent medical equipment;
and when the comparison result represents that the third identity information is different from the first identity information, enabling the first intelligent medical equipment to transmit the diagnosis data to any intelligent medical equipment except the target intelligent medical equipment in the equipment cluster where the target intelligent medical equipment is located.
Preferably, the step of transferring the visit data based on the transfer direction information includes:
and transmitting the visit data to any intelligent medical equipment except the first intelligent medical equipment in the equipment cluster where the first intelligent medical equipment corresponding to the first equipment node in the fault track graph is located.
Preferably, the method further comprises:
and when the confirmation information fed back by the intelligent medical equipment corresponding to the last equipment node in the fault track map according to the received diagnosis data is acquired, the fault track map is regenerated.
Preferably, the method further comprises:
and when the reconstruction completion information aiming at the fault track map is detected, sending a control instruction to the current intelligent medical equipment corresponding to the fault prompt information so as to enable the current intelligent medical equipment to stop outputting the fault prompt information.
Preferably, the step of determining first identity information from the visit data comprises:
acquiring first data coding information of the visit data; traversing second data coding information in a preset database to obtain a traversal result, wherein the preset database is used for storing a plurality of target data coding information, an information correlation coefficient of each target data coding information and an information category of each target data coding information, and the second data coding information is the same data coding information as the first data coding information;
when the traversal result represents that the second data coding information exists in the preset database, obtaining a noise influence factor of the second data coding information based on a first information category of the first data coding information and a second information category of the second data coding information; wherein the noise impact factor is used for characterizing noise interference of the second data coding information on the first data coding information;
determining the accumulated calling times of the second data coding information, and determining the current calling probability of the second data coding information based on the accumulated calling times; based on the noise influence factor and the current calling probability, performing data feature extraction on the terminal equipment which uploads the second data coding information to obtain a second data feature of the second data coding information relative to the terminal equipment; the terminal equipment is intelligent medical equipment except for the intelligent medical fault treatment;
performing feature recognition on the first data coding information through a preset identity information recognition thread to obtain a recognition result; the identification result comprises a plurality of target information correlation coefficients of the first data coding information, the weight of each target information correlation coefficient and a first data characteristic of the first data coding information under each target information correlation coefficient;
and determining a first data feature with the minimum similarity value with the second data feature, and analyzing the first data feature to obtain the first identity information.
Preferably, the step of determining the second identity information from the fault notification information includes:
determining an information flow sequence in the fault prompt information, and extracting the information flow based on the information flow sequence; the information flow sequence is a sequence formed by information flows related to identity information in the fault prompt information;
carrying out information coding pairing on the information flow of the fault prompt information and each information flow of preset information in a preset information set to obtain a pairing result; the preset information set stores character types corresponding to a plurality of preset information and character capacities represented by the character types;
extracting an information character string from the information flow of the fault prompt information on the premise that the matching result represents that the information flow of the fault prompt information and the information flow of each piece of preset information are successfully matched; judging whether an information character string in the information stream of the fault prompt information changes relative to an information character string in a previous information stream of the fault prompt information;
if so, determining an information character string extracted from the information stream in the fault prompt information as a character string corresponding to the second identity information;
otherwise, fusing an information character string extracted from an information stream in the fault prompt information with a target character string of a corresponding character sequence in a previous information stream in the fault prompt information, and determining a fusion result as a character string corresponding to the second identity information;
and determining the second identity information according to the character string corresponding to the second identity information.
Provided is a cloud server including:
a processor, and
a memory and a network interface connected with the processor;
the network interface is connected with a nonvolatile memory in the cloud server;
when the processor is operated, the computer program is called from the nonvolatile memory through the network interface, and the computer program is operated through the memory so as to execute the method.
The readable storage medium is applied to a computer, and is burnt with a computer program, and the computer program realizes the method when running in the memory of the cloud server.
Through the scheme, firstly, under the condition that the fault prompting information is detected, the fault track graph is generated based on the fault prompting information. And secondly, determining first identity information from the received visit data and determining second identity information from the fault prompt information. And then, when the first identity information and the second identity information are the same, the diagnosis data determined as the rechecking data are transmitted based on the fault track map so as to realize the on-line rechecking of the intelligent medical equipment with faults, and when the first identity information and the second identity information are different, transmission direction information except the fault track map is determined so as to transmit the diagnosis data determined as normal data based on the transmission direction information, so that the diagnosis data of the patient cannot be received when the intelligent medical equipment is in a fault detection state. Thus, when fault detection is carried out on the intelligent medical equipment, the treatment data can be accurately processed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
Fig. 1 is a schematic diagram of an intelligent medical fault handling system incorporating visit data delivery according to an exemplary embodiment of the present application.
Fig. 2 is a flow chart illustrating a method for intelligent medical fault handling in conjunction with treatment data delivery according to an exemplary embodiment of the present application.
Fig. 3 is a block diagram of one embodiment of an intelligent medical fault handling device incorporating visit data delivery according to one illustrated embodiment of the present application.
Fig. 4 is a hardware structure diagram of a cloud server where the intelligent medical fault processing apparatus of the present application is located in conjunction with the transmission of medical data.
Detailed Description
The present invention is further described below in conjunction with the following figures and specific examples so that those skilled in the art may better understand the present invention and practice it, but the examples are not intended to limit the present invention.
In order to solve the technical problem that treatment data cannot be correctly processed when current intelligent medical equipment is subjected to fault detection, the embodiment of the invention provides an intelligent medical fault processing method and a cloud server which are combined with treatment data transmission. Therefore, when the intelligent medical equipment is subjected to fault detection. The data of the medical treatment can be correctly processed.
For the convenience of explaining the present solution, the intelligent medical fault handling system in the present solution will be described first. As shown in fig. 1, the intelligent medical fault handling system 100 includes a cloud server 200 and a plurality of device clusters, and the cloud server 200 and the device clusters are in a cascade relationship. For example, cloud server 200 communicates with device cluster 310, device cluster 310 communicates with device cluster 320, device cluster 330 communicates with device cluster 340, and so on. This embodiment takes four device clusters as an example for explanation.
Furthermore, each device cluster comprises at least one intelligent medical device, and the intelligent medical devices in the device clusters of different levels sequentially communicate to form a complete medical procedure. Cloud server 200 may perform fault handling for the intelligent medical device and deliver the visit data. In this embodiment, the medical data may be medical record information, diagnosis information, and the like of the patient, and is not limited herein.
On the basis, please refer to fig. 2 in combination, which is a flowchart of an intelligent medical fault processing method according to an embodiment of the present invention, and the intelligent medical fault processing method may be applied to the cloud server 200 in fig. 1, and may be specifically implemented by the following steps.
And step 230, matching the first identity information with the second identity information to obtain a matching result.
And 240, when the matching result represents that the first identity information and the second identity information are the same, transmitting the visit data based on the fault track map.
And 250, when the matching result represents that the first identity information is different from the second identity information, determining transfer direction information except the fault track map, and transferring the clinic data based on the transfer direction information.
Through the above steps 210 to 250, first, when the presence of the failure indication information is detected, the failure trace map is generated based on the failure indication information. And secondly, determining first identity information from the received visit data and determining second identity information from the fault prompt information. And then, when the first identity information and the second identity information are the same, the diagnosis data determined as the rechecking data are transmitted based on the fault track map so as to realize the on-line rechecking of the intelligent medical equipment with faults, and when the first identity information and the second identity information are different, transmission direction information except the fault track map is determined so as to transmit the diagnosis data determined as normal data based on the transmission direction information, so that the diagnosis data of the patient cannot be received when the intelligent medical equipment is in a fault detection state. Thus, when fault detection is carried out on the intelligent medical equipment, the treatment data can be accurately processed.
In one possible example, the delivering the visit data based on the fault trace map described in step 240 may specifically include the following.
Step 241, transmitting the visit data to a first intelligent medical device corresponding to a first device node in the fault track map.
Referring to fig. 1, the intelligent medical devices corresponding to the device nodes in the fault trace diagram have a cascade relationship, which sequentially includes: smart medical device 311, smart medical device 325, smart medical device 332, and smart medical device 343. The cloud server 200 may transfer the visit data determined as the review data to the smart medical device 311. In this way, smart medical device 311 may perform a test and review of the fault repair based on the review data.
And 242, enabling the first intelligent medical device to transmit the visit data to a next intelligent medical device of the first intelligent medical device according to a comparison result between the preset third identity information and the first identity information in the visit data.
On one hand, when the comparison result represents that the third identity information is the same as the first identity information, the first intelligent medical equipment transmits the visit data to the target intelligent medical equipment; wherein the target intelligent medical device is the intelligent medical device next to the first intelligent medical device in the fault trace map. For example, the target smart medical device may be smart medical device 325.
On the other hand, when the comparison result indicates that the third identity information is different from the first identity information, the first intelligent medical device transmits the visit data to any intelligent medical device except the target intelligent medical device in the device cluster where the target intelligent medical device is located.
For example, smart medical device 311 may communicate the visit data to any of smart medical device 321, smart medical device 322, smart medical device 323, and smart medical device 324.
Therefore, the correct transmission of the diagnosis data can be ensured by the grading judgment of the identity information of the terminal equipment, and the delay of the patient's diagnosis is avoided.
In another possible example, the step 250 of communicating the visit data based on the communication direction information specifically includes: and transmitting the visit data to any intelligent medical equipment except the first intelligent medical equipment in the equipment cluster where the first intelligent medical equipment corresponding to the first equipment node in the fault track graph is located.
In this embodiment, the transfer direction information includes a device trace diagram, the device trace diagram is different from the fault trace diagram, and all device nodes in the device trace diagram are different from those in the fault trace diagram.
When the matching result indicates that the first identity information and the second identity information are not the same, the visit data may be determined to be normal data, in which case, the cloud server 200 may transmit the visit data to any one of the intelligent medical device 312, the intelligent medical device 313, and the intelligent medical device 314. In this way, it can be ensured that normal visit data of the patient is not transmitted to the intelligent medical device in a fault repair or fault detection state.
On the basis of the above, the method may further include: and when the confirmation information fed back by the intelligent medical equipment corresponding to the last equipment node in the fault track map according to the received diagnosis data is acquired, the fault track map is regenerated. Therefore, through modification of the fault track diagram, different fault test paths can be adopted for fault repair test and recheck, and the intelligent medical equipment can be ensured to be normally used after fault repair is completed.
On the basis of the above, the method may further include: and when the reconstruction completion information aiming at the fault track map is detected, sending a control instruction to the current intelligent medical equipment corresponding to the fault prompt information so as to enable the current intelligent medical equipment to stop outputting the fault prompt information.
In this embodiment, the reconstruction completion information is used to represent that the cloud server 200 has completed reconstructing all the categories of the fault trace map. In this case, it may be determined that the test procedure and the rechecking procedure of the fault repair are completed, and the cloud server 200 may send a control instruction to the current intelligent medical device, so that the current intelligent medical device stops outputting the fault prompt information.
For example, the cloud server 200 may send control instructions to the current smart medical device 325. Therefore, the state of the whole intelligent medical fault processing system 100 can be updated in time after the fault repairing test and rechecking are completed, and the normal operation of the intelligent medical fault processing system 100 is ensured.
In an implementation, in order to effectively filter noise in the visit data and thus accurately determine the first identity information, the determination of the first identity information from the visit data as described in step 220 may specifically include the following steps.
2211, acquiring first data coding information of the visit data; traversing second data coding information in a preset database to obtain a traversal result, wherein the preset database is used for storing a plurality of target data coding information, an information association coefficient of each target data coding information and an information category of each target data coding information, and the second data coding information is the same data coding information as the first data coding information.
Step 2212, when the traversal result indicates that the second data encoding information exists in the preset database, obtaining a noise influence factor of the second data encoding information based on a first information category of the first data encoding information and a second information category of the second data encoding information; wherein the noise impact factor is used to characterize noise interference of the second data encoding information on the first data encoding information.
Step 2213, determining the cumulative calling times of the second data coding information, and determining the current calling probability of the second data coding information based on the cumulative calling times; based on the noise influence factor and the current calling probability, performing data feature extraction on the terminal equipment which uploads the second data coding information to obtain a second data feature of the second data coding information relative to the terminal equipment; wherein the terminal equipment is intelligent medical equipment except the intelligent medical fault processing.
2214, performing feature recognition on the first data coding information through a preset identity information recognition thread to obtain a recognition result; the identification result comprises a plurality of target information correlation coefficients of the first data coding information, the weight of each target information correlation coefficient and the first data characteristic of the first data coding information under each target information correlation coefficient.
Step 2215, determining the first data feature with the minimum similarity value with the second data feature, and analyzing the first data feature to obtain the first identity information.
It will be appreciated that based on steps 2211-2215 above, the similarity value between the first data feature and the second data feature can be given to effectively filter noise in the visit data, thereby accurately determining the first identity information.
In another example, the step of determining the second identity information from the fault indication information described in step 220 may specifically include the following steps.
Step 2221, determining an information flow sequence in the fault prompt message, and extracting an information flow based on the information flow sequence; the information flow sequence is a sequence formed by information flows related to identity information in the fault prompt information.
Step 2222, performing information coding pairing on the information stream of the fault prompt message and the information stream of each piece of preset information in a preset information set to obtain a pairing result; and the preset information set stores character types corresponding to a plurality of preset information and the character capacity represented by the character types.
Step 2223, on the premise that the matching result represents that the information flow of the fault prompt information and the information flow of each preset information are successfully matched, extracting an information character string from the information flow of the fault prompt information; and judging whether the information character string in the information stream of the fault prompt information changes relative to the information character string in the last information stream of the fault prompt information.
Step 2225, if yes, determining the information character string extracted from the information stream in the fault prompt information as the character string corresponding to the second identity information.
Step 2226, otherwise, fusing the information character string extracted from the information stream in the fault prompt information with the target character string of the corresponding character sequence in the previous information stream in the fault prompt information, and determining the fused result as the character string corresponding to the second identity information.
Step 2227, determining the second identity information according to the character string corresponding to the second identity information.
When the method described in steps 2221-2227 is applied, the character compression and the character conversion performed during the transmission of the fault prompt information between the intelligent medical device and the cloud server can be taken into account, so that the character string corresponding to the second identity information is determined according to whether the character string of the information stream changes. Thus, the second identity information can be accurately and unmistakably determined.
In an alternative embodiment, the cloud server 200 may access other intelligent medical devices in normal working states sequentially, and in order to ensure data security of the cloud server 200 and the original intelligent medical devices and avoid data loss, on the basis of the above, the method may further include the following steps.
And 320, performing protocol analysis on the access request to obtain information transmission protocol parameters corresponding to the access request.
Step 350, based on the verification result, performing similarity query in a preset verification result pool to obtain a current query result; for each preset check result included in the current query result, acquiring a weight ratio between a device permission request included in the access request and the preset check result; and obtaining the confidence ratio of the equipment permission request included in the access request in the preset verification result.
And step 360, calculating a data safety factor of the access request sent by the equipment to be accessed based on the weight proportion and the confidence coefficient proportion matched with each preset check result, accessing the equipment to be accessed into the first equipment cluster when the data safety factor is greater than or equal to a preset coefficient, and refusing to respond to the access request sent by the equipment to be accessed when the data safety factor is less than the preset coefficient.
By executing the method described in the above steps 310 to 360, the access of the device to be accessed can be verified, so that the data security of the cloud server 200 and the original intelligent medical device is ensured, and data loss is avoided.
In another alternative embodiment, to trace the cause of the failure of the failed intelligent medical device, the method may further include the following steps based on the above description.
In step 410, the information tag extracted based on the fault prompt information is determined.
Step 420, for a current information tag in the information tags, determining an activation probability of the current information tag in a target duration based on an activation duration of the current information tag in the target duration and a total activation duration of each information tag in the target duration.
And 430, determining a local fault coefficient of the current information label between two adjacent target time lengths according to the activation probability of the current information label in the two adjacent target time lengths.
Step 440, determining whether the current information tag is a valid tag based on the local failure coefficient.
Step 450, when the current information tag is determined to be an effective tag, determining a global failure coefficient of each information tag in two adjacent target durations based on the activation probability of the current information tag in the two adjacent target durations and the total activation duration of each information tag in each target duration.
Step 460, determining a fault type corresponding to the fault prompt information based on the mapping relationship between the global fault coefficient and the local fault coefficient, and performing associated storage on the fault type and the fault prompt information.
It can be understood that through the above steps 410 to 460, the information tag corresponding to the fault prompting information can be analyzed, and then the fault type used for tracing the fault reason corresponding to the fault prompting information is determined. By storing the fault prompt information and the fault types in a correlation mode, the fault reason of the intelligent medical equipment with the fault can be effectively traced.
On the basis of the above, please refer to fig. 3, and an intelligent medical fault handling apparatus 500 corresponding to the intelligent medical fault handling method is further provided, which is described in detail below.
A1. An intelligent medical fault processing device combined with visit data transmission is applied to a cloud server which is communicated with a device cluster in an intelligent medical fault processing system, and the device comprises:
a trajectory generation module 510, configured to determine whether the visit data is received in real time; if the visit data is received, detecting whether fault prompt information exists or not, and generating a fault track map based on the fault prompt information under the condition that the fault prompt information exists; the fault trace graph is formed by intelligent medical equipment for transmitting rechecking data, the fault trace graph comprises a plurality of equipment nodes, each equipment node corresponds to one intelligent medical equipment, and each corresponding intelligent medical equipment in the fault trace graph is in a different equipment cluster;
an information determining module 520, configured to determine first identity information from the visit data and second identity information from the fault notification information; the second identity information is identity information corresponding to preset rechecking data;
an information matching module 530, configured to match the first identity information with the second identity information to obtain a matching result;
a data transmission module 540, configured to transmit the visit data based on the fault trace map when the matching result indicates that the first identity information and the second identity information are the same; and when the matching result represents that the first identity information and the second identity information are different, determining transfer direction information except the fault track graph, and transferring the visit data based on the transfer direction information.
A2. The apparatus of a1, the data transfer module 540, configured to:
transmitting the visit data to a first intelligent medical device corresponding to a first device node in the fault track map;
and enabling the first intelligent medical equipment to transmit the treatment data to the next intelligent medical equipment of the first intelligent medical equipment according to the comparison result between the preset third identity information and the first identity information in the treatment data.
A3. The apparatus of a2, the data transfer module 540, configured to:
when the comparison result represents that the third identity information is the same as the first identity information, enabling the first intelligent medical equipment to transmit the clinic data to the target intelligent medical equipment;
and when the comparison result represents that the third identity information is different from the first identity information, enabling the first intelligent medical equipment to transmit the diagnosis data to any intelligent medical equipment except the target intelligent medical equipment in the equipment cluster where the target intelligent medical equipment is located.
A4. The apparatus of a1, the data transfer module 540, configured to:
and transmitting the visit data to any intelligent medical equipment except the first intelligent medical equipment in the equipment cluster where the first intelligent medical equipment corresponding to the first equipment node in the fault track graph is located.
A5. The apparatus of any of a1-a4, the trajectory generation module 510, further to:
and when the confirmation information fed back by the intelligent medical equipment corresponding to the last equipment node in the fault track map according to the received diagnosis data is acquired, the fault track map is regenerated.
A6. The apparatus of a5, the trajectory generation module 510, further configured to:
and when the reconstruction completion information aiming at the fault track map is detected, sending a control instruction to the current intelligent medical equipment corresponding to the fault prompt information so as to enable the current intelligent medical equipment to stop outputting the fault prompt information.
A7. The apparatus of any of a1-a4, the information determining module 520 to:
acquiring first data coding information of the visit data; traversing second data coding information in a preset database to obtain a traversal result, wherein the preset database is used for storing a plurality of target data coding information, an information correlation coefficient of each target data coding information and an information category of each target data coding information, and the second data coding information is the same data coding information as the first data coding information;
when the traversal result represents that the second data coding information exists in the preset database, obtaining a noise influence factor of the second data coding information based on a first information category of the first data coding information and a second information category of the second data coding information; wherein the noise impact factor is used for characterizing noise interference of the second data coding information on the first data coding information;
determining the accumulated calling times of the second data coding information, and determining the current calling probability of the second data coding information based on the accumulated calling times; based on the noise influence factor and the current calling probability, performing data feature extraction on the terminal equipment which uploads the second data coding information to obtain a second data feature of the second data coding information relative to the terminal equipment; the terminal equipment is intelligent medical equipment except for the intelligent medical fault treatment;
performing feature recognition on the first data coding information through a preset identity information recognition thread to obtain a recognition result; the identification result comprises a plurality of target information correlation coefficients of the first data coding information, the weight of each target information correlation coefficient and a first data characteristic of the first data coding information under each target information correlation coefficient;
and determining a first data feature with the minimum similarity value with the second data feature, and analyzing the first data feature to obtain the first identity information.
A8. The apparatus of any of a1-a4, the information determining module 520 to:
determining an information flow sequence in the fault prompt information, and extracting the information flow based on the information flow sequence; the information flow sequence is a sequence formed by information flows related to identity information in the fault prompt information;
carrying out information coding pairing on the information flow of the fault prompt information and each information flow of preset information in a preset information set to obtain a pairing result; the preset information set stores character types corresponding to a plurality of preset information and character capacities represented by the character types;
extracting an information character string from the information flow of the fault prompt information on the premise that the matching result represents that the information flow of the fault prompt information and the information flow of each piece of preset information are successfully matched; judging whether an information character string in the information stream of the fault prompt information changes relative to an information character string in a previous information stream of the fault prompt information;
if so, determining an information character string extracted from the information stream in the fault prompt information as a character string corresponding to the second identity information;
otherwise, fusing an information character string extracted from an information stream in the fault prompt information with a target character string of a corresponding character sequence in a previous information stream in the fault prompt information, and determining a fusion result as a character string corresponding to the second identity information;
and determining the second identity information according to the character string corresponding to the second identity information.
A8. The apparatus of a1, the apparatus further comprising an access authentication module to:
acquiring an access request sent by equipment to be accessed; the equipment to be accessed is other intelligent medical equipment in a normal working state;
performing protocol analysis on the access request to obtain an information transmission protocol parameter corresponding to the access request;
performing first feature extraction on an information transmission protocol parameter corresponding to the access request to obtain a first feature of the access request, wherein the first feature is used for describing a parameter distribution feature of the information transmission protocol parameter; performing second feature extraction on the information transmission protocol parameter corresponding to the access request to obtain a second feature of the access request, wherein the second feature is used for describing a parameter confidence feature of the information transmission protocol parameter;
when the access request comprises at least two equipment permission requests, respectively performing cyclic redundancy check calculation on a first characteristic and a second characteristic of the equipment permission requests aiming at each equipment permission request in the access request to obtain a check result;
based on the verification result, similarity query is carried out in a preset verification result pool to obtain a current query result; for each preset check result included in the current query result, acquiring a weight ratio between a device permission request included in the access request and the preset check result; obtaining a confidence ratio of the equipment permission request included in the access request in the preset verification result;
and calculating the data safety factor of the access request sent by the equipment to be accessed based on the weight proportion and the confidence coefficient proportion matched with each preset check result, accessing the equipment to be accessed into the first equipment cluster when the data safety factor is greater than or equal to a preset coefficient, and refusing to respond to the access request sent by the equipment to be accessed when the data safety factor is less than the preset coefficient.
A9. The apparatus of a1, the apparatus further comprising a failure resolution module to:
determining an information label extracted based on the fault prompt information;
aiming at a current information label in the information labels, determining the activation probability of the current information label in a target time length based on the activation time length of the current information label in the target time length and the total activation time length of each information label in the target time length;
determining a local fault coefficient of the current information label between two adjacent target time lengths according to the activation probability of the current information label in the two adjacent target time lengths;
determining whether the current information tag is a valid tag based on the local failure coefficient;
when the current information tags are determined to be effective tags, determining a global fault coefficient of each information tag in two adjacent target time lengths based on the activation probability of the current information tag in the two adjacent target time lengths and the total activation time length of each information tag in each target time length;
and determining the fault type corresponding to the fault prompt information based on the mapping relation between the global fault coefficient and the local fault coefficient, and performing associated storage on the fault type and the fault prompt information.
The implementation process of the functions and actions of each module in the above device is specifically described in the implementation process of the corresponding step in the above method, and is not described herein again.
For the device embodiments, since they substantially correspond to the method embodiments, reference may be made to the partial description of the method embodiments for relevant points. The above-described embodiments of the apparatus are merely illustrative, wherein the modules described as separate parts may or may not be physically separate, and the parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of the application. One of ordinary skill in the art can understand and implement it without inventive effort.
Referring to fig. 4, an embodiment of the present invention further provides a cloud server 200, including: a processor 210, and a memory 220 and a network interface 230 connected to the processor 210, wherein the network interface 230 is connected to a non-volatile memory 240 in the cloud server 200. The processor 200 retrieves the computer program from the non-volatile memory 240 via the network interface 230 and runs the computer program via the memory 220 to perform the above-mentioned method.
Further, a readable storage medium applied to a computer is provided, and the readable storage medium is burned with a computer program, and the computer program implements the method when running in the memory 220 of the cloud server 200.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
It will be understood that the present application is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.
Claims (9)
1. An intelligent medical fault processing method combined with visit data transmission is applied to a cloud server which is communicated with a device cluster in an intelligent medical fault processing system, and the method comprises the following steps:
judging whether the visit data is received in real time; if the visit data is received, detecting whether fault prompt information exists or not, and generating a fault track map based on the fault prompt information under the condition that the fault prompt information exists; the fault trace graph is formed by intelligent medical equipment for transmitting rechecking data, the fault trace graph comprises a plurality of equipment nodes, each equipment node corresponds to one intelligent medical equipment, and each corresponding intelligent medical equipment in the fault trace graph is in a different equipment cluster;
determining first identity information from the visit data and second identity information from the fault prompt information; the second identity information is identity information corresponding to preset rechecking data;
matching the first identity information with the second identity information to obtain a matching result;
when the matching result represents that the first identity information and the second identity information are the same, transmitting the visit data based on the fault track map;
when the matching result represents that the first identity information and the second identity information are different, determining transfer direction information except the fault track map, and transferring the visit data based on the transfer direction information;
wherein the method further comprises:
determining an information label extracted based on the fault prompt information;
aiming at a current information label in the information labels, determining the activation probability of the current information label in a target time length based on the activation time length of the current information label in the target time length and the total activation time length of each information label in the target time length;
determining a local fault coefficient of the current information label between two adjacent target time lengths according to the activation probability of the current information label in the two adjacent target time lengths;
determining whether the current information tag is a valid tag based on the local failure coefficient;
when the current information tags are determined to be effective tags, determining a global fault coefficient of each information tag in two adjacent target time lengths based on the activation probability of the current information tag in the two adjacent target time lengths and the total activation time length of each information tag in each target time length;
and determining the fault type corresponding to the fault prompt information based on the mapping relation between the global fault coefficient and the local fault coefficient, and performing associated storage on the fault type and the fault prompt information.
2. The method of claim 1, wherein the step of communicating the encounter data based on the fault trace map comprises:
transmitting the visit data to a first intelligent medical device corresponding to a first device node in the fault track map;
and enabling the first intelligent medical equipment to transmit the treatment data to the next intelligent medical equipment of the first intelligent medical equipment according to the comparison result between the preset third identity information and the first identity information in the treatment data.
3. The method of claim 2, wherein said step of causing the first intelligent medical device to pass the visit data to a next intelligent medical device of the first intelligent medical device based on a comparison between the preset third identity information and the first identity information in the visit data comprises:
when the comparison result represents that the third identity information is the same as the first identity information, enabling the first intelligent medical equipment to transmit the clinic data to the target intelligent medical equipment;
and when the comparison result represents that the third identity information is different from the first identity information, enabling the first intelligent medical equipment to transmit the diagnosis data to any intelligent medical equipment except the target intelligent medical equipment in the equipment cluster where the target intelligent medical equipment is located.
4. The method of claim 1, wherein the step of communicating the encounter data based on the communication direction information comprises:
and transmitting the visit data to any intelligent medical equipment except the first intelligent medical equipment in the equipment cluster where the first intelligent medical equipment corresponding to the first equipment node in the fault track graph is located.
5. The method of any one of claims 1-4, further comprising:
and when the confirmation information fed back by the intelligent medical equipment corresponding to the last equipment node in the fault track map according to the received diagnosis data is acquired, the fault track map is regenerated.
6. The method of claim 5, wherein the method further comprises:
and when the reconstruction completion information aiming at the fault track map is detected, sending a control instruction to the current intelligent medical equipment corresponding to the fault prompt information so as to enable the current intelligent medical equipment to stop outputting the fault prompt information.
7. The method of any of claims 1-4, wherein the step of determining first identity information from the visit data comprises:
acquiring first data coding information of the visit data; traversing second data coding information in a preset database to obtain a traversal result, wherein the preset database is used for storing a plurality of target data coding information, an information correlation coefficient of each target data coding information and an information category of each target data coding information, and the second data coding information is the same data coding information as the first data coding information;
when the traversal result represents that the second data coding information exists in the preset database, obtaining a noise influence factor of the second data coding information based on a first information category of the first data coding information and a second information category of the second data coding information; wherein the noise impact factor is used for characterizing noise interference of the second data coding information on the first data coding information;
determining the accumulated calling times of the second data coding information, and determining the current calling probability of the second data coding information based on the accumulated calling times; based on the noise influence factor and the current calling probability, performing data feature extraction on the terminal equipment which uploads the second data coding information to obtain a second data feature of the second data coding information relative to the terminal equipment; the terminal equipment is intelligent medical equipment except for the intelligent medical fault treatment;
performing feature recognition on the first data coding information through a preset identity information recognition thread to obtain a recognition result; the identification result comprises a plurality of target information correlation coefficients of the first data coding information, the weight of each target information correlation coefficient and a first data characteristic of the first data coding information under each target information correlation coefficient;
and determining a first data feature with the minimum similarity value with the second data feature, and analyzing the first data feature to obtain the first identity information.
8. The method of any of claims 1-4, wherein determining second identity information from the fault indication information comprises:
determining an information flow sequence in the fault prompt information, and extracting the information flow based on the information flow sequence; the information flow sequence is a sequence formed by information flows related to identity information in the fault prompt information;
carrying out information coding pairing on the information flow of the fault prompt information and each information flow of preset information in a preset information set to obtain a pairing result; the preset information set stores character types corresponding to a plurality of preset information and character capacities represented by the character types;
extracting an information character string from the information flow of the fault prompt information on the premise that the matching result represents that the information flow of the fault prompt information and the information flow of each piece of preset information are successfully matched; judging whether an information character string in the information stream of the fault prompt information changes relative to an information character string in a previous information stream of the fault prompt information;
if so, determining an information character string extracted from the information stream in the fault prompt information as a character string corresponding to the second identity information;
otherwise, fusing an information character string extracted from an information stream in the fault prompt information with a target character string of a corresponding character sequence in a previous information stream in the fault prompt information, and determining a fusion result as a character string corresponding to the second identity information;
and determining the second identity information according to the character string corresponding to the second identity information.
9. A cloud server, comprising:
a processor, and
a memory and a network interface connected with the processor;
the network interface is connected with a nonvolatile memory in the cloud server;
the processor, when running, retrieves a computer program from the non-volatile memory via the network interface and runs the computer program via the memory to perform the method of any of claims 1-8.
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| CN202010308895.0A CN111489816B (en) | 2020-04-19 | 2020-04-19 | Intelligent medical fault processing method based on visit data transmission and cloud server |
| CN202011404495.6A CN112466456A (en) | 2020-04-19 | 2020-04-19 | Intelligent medical fault processing method combining visit data transmission and cloud server |
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| CN202011404470.6A Withdrawn CN112466455A (en) | 2020-04-19 | 2020-04-19 | Intelligent medical fault processing method applied to treatment data transmission and cloud server |
| CN202011404495.6A Withdrawn CN112466456A (en) | 2020-04-19 | 2020-04-19 | Intelligent medical fault processing method combining visit data transmission and cloud server |
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| CN100453985C (en) * | 2007-08-28 | 2009-01-21 | 北京航空航天大学 | Portable two-channel vibrating functional failure diagnostic apparatus |
| US20090112618A1 (en) * | 2007-10-01 | 2009-04-30 | Johnson Christopher D | Systems and methods for viewing biometrical information and dynamically adapting schedule and process interdependencies with clinical process decisioning |
| CN105303050B (en) * | 2015-11-10 | 2018-03-30 | 中国人民解放军第三军医大学第三附属医院 | The fault message storage method and system of a kind of Medical Devices |
| CN105678092B (en) * | 2016-02-01 | 2018-10-19 | 中国人民解放军第三军医大学第三附属医院 | Intensive Care Therapy intelligent alarm based on Internet of Things manages system |
| CN106210139A (en) * | 2016-08-30 | 2016-12-07 | 上海雷尼威尔技术有限公司 | Intelligent agricultural machinery based on Internet of Things management platform |
| CN108898238B (en) * | 2018-05-24 | 2022-02-01 | 东软医疗系统股份有限公司 | Medical equipment fault prediction system and related method, device and equipment |
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| CN111489816B (en) | 2021-01-26 |
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Application publication date: 20210309 |