CN110249392A - Intelligent assisting in diagnosis and treatment system and method - Google Patents
Intelligent assisting in diagnosis and treatment system and method Download PDFInfo
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Abstract
The present invention provides a kind of intelligent assisting in diagnosis and treatment system, comprising: receiving module, for receiving case history；Categorization module, for the case history received to be carried out classification processing according to disease type, and by sorted medical records storage to corresponding database；Matching module obtains the medical record templates that match degree is greater than the preset threshold, wherein medical record templates storage disease type and illness information corresponding with disease type for matching case history with the medical record templates in medical record templates library；Secondary diagnostic module, matched disease type and illness information corresponding with disease type for obtaining, corresponding historical diagnostic reference scheme is provided using artificial intelligence convolutional neural networks learning method, and the matched disease type of institute and illness information corresponding with disease type are exported, for doctor's reference.Example of the present invention solves in current medical and health services, and the medical level of doctor not only can be improved, and effectively reduces the misdiagnosis rate of doctor in the horizontal insufficient problem of doctor.
Description
Technical field
The present invention relates to medical information technical field more particularly to a kind of intelligent assisting in diagnosis and treatment system and methods.
Background technique
With the development of science and technology, the appearance of especially internet, artificial intelligence, big data, changes the world, society is changed
Can every aspect, deep effect we live every field.With the development of medical technology, medical information amount is big,
Many kinds of, various information formats are different (text, number, image, audio-visual), and doctor needs to consult bulk information, can just provide
Corresponding diagnosis and treatment scheme, but since information content is huge, it inevitably has and omits and provide incomplete diagnosis and treatment scheme.Medical quality in hospital
It needs conveniently manage miscellaneous medical information in management.Patient needs to obtain the detailed progress note of doctor
Ensure the vital interests of oneself.The it is proposed of these demands, so that must have reliable hospital electronic diagnosis and treatment in hygiene medical treatment industry
Auxiliary system helps through.Medical auxiliary system based on electronic health record can meet to the greatest extent more than the needs of, and
The work quality and efficiency of medical industry can be greatly improved.
Summary of the invention
The purpose of the present invention is to provide a kind of intelligent assisting in diagnosis and treatment system and methods to carry out accurately patient with realizing
Diagnoses and treatment, the biggish treatment level and working efficiency for improving hospital.
On the one hand, the embodiment of the present invention provides a kind of intelligent assisting in diagnosis and treatment system characterized by comprising
Receiving module, for receiving case history；
Categorization module, for the case history received to be carried out classification processing according to disease type, and will be sorted
The medical records storage is to corresponding database；
It is big to obtain matching degree for matching the case history with the medical record templates in medical record templates library for matching module
In the medical record templates of preset threshold, wherein medical record templates store disease type and illness information corresponding with disease type；
Secondary diagnostic module, matched disease type and illness information corresponding with disease type for obtaining, utilizes
Artificial intelligence convolutional neural networks learning method provides corresponding historical diagnostic reference scheme, and exports the matched disease type of institute
And illness information corresponding with disease type, for doctor's reference.
Preferably, further includes:
Conversion module, for being converted text case history according to artificial intelligence deep learning method by text and image analysis
At the electronic health record of standardization, the electronic health record of the electronic health record of non-standardization and half standardization is turned according to systemic presupposition rule
Change the electronic health record of standardization into.
Preferably, further includes:
Artificial intelligence module, for according to the disease type of patient by several doctors to matched disease type treatment
Scheme carries out global alignment, obtains including that correspondence illness information and the diagnosis and treatment scheme of similar conditions information are sent to auxiliary diagnosis mould
Block.
Preferably, further includes:
Tracking and monitoring module, for after doctor determines the disease type of patient, check in case history whether there is also not by
The project of inspection or the process not being diagnosed timely feedback the implementation progress of therapeutic scheme and are provided in subsequent therapeutic scheme
Therapeutic effect analysis report prompts doctor whether to need to modify therapeutic scheme over the course for the treatment of and carries out secondary assisting in diagnosis and treatment.
Preferably, further includes:
Remote communication module, for providing the external interface of intelligent assisting in diagnosis and treatment system and remote assistant system communication, with
And the remote access request of doctor is received, and establish and communicate according to access request and remote assistant system, to carry out remote online
Auxiliary.
Preferably, further includes:
Speech recognition module, for acquisition voice signal and identified, the voice messaging of identification is converted into text
Information, and corresponding position of the typing into patient medical history template.
Correspondingly, the present invention also provides a kind of intelligent assisting in diagnosis and treatment methods, comprising the following steps:
Receive case history；
The case history received is subjected to classification processing according to disease type, and the sorted medical records storage is arrived
Corresponding database；
The case history is matched with the medical record templates in medical record templates library, obtains the disease that match degree is greater than the preset threshold
Template is gone through, wherein medical record templates storage disease type and illness information corresponding with disease type；
The matched disease type of institute and illness information corresponding with disease type are obtained, artificial intelligence convolutional Neural net is utilized
Network learning method provides corresponding historical diagnostic reference scheme, and exports the matched disease type of institute and corresponding with disease type
Illness information, for doctor's reference.
Preferably, the case history includes electronic health record and/or document case history, after receiving case history further include:
If received case history is document case history, will be literary according to artificial intelligence deep learning method by text and image analysis
This case history is converted into the electronic health record of standardization；
If received case history is the electronic health record of non-standardization and the electronic health record of half standardization, by the electronics of non-standardization
Case history and the electronic health record of half standardization are converted into the electronic health record of standardization according to systemic presupposition rule.
Preferably, matched disease type and illness information corresponding with disease type obtaining, utilize artificial intelligence
Convolutional neural networks learning method provides corresponding historical diagnostic reference scheme, and exports the matched disease type of institute and and disease
The corresponding illness information of type, after the step of doctor's reference further include:
According to the disease type of patient by several doctors to matched disease type therapeutic scheme carry out global alignment,
It obtains including that the diagnosis and treatment scheme of corresponding illness information and similar conditions information is sent to doctor.
Preferably, further includes:
After doctor determines the disease type of patient, check in case history whether not examined there is also not examined project or
Disconnected process timely feedbacks the implementation progress of therapeutic scheme in subsequent therapeutic scheme and provides therapeutic effect analysis report,
Whether prompt doctor needs to modify therapeutic scheme over the course for the treatment of carries out secondary assisting in diagnosis and treatment.
Preferably, further includes:
The remote access request of doctor is received, and is established and is communicated according to the access request and remote assistant system, to carry out
Remote online auxiliary.
Preferably, further includes:
Patient medical history template is provided, the voice signal of doctor is received, voice signal collected is identified, will identify
Voice messaging be converted to text information, and corresponding position of the typing into patient medical history template, generate case history.
The implementation of the embodiments of the present invention has the following beneficial effects: intelligence assisting in diagnosis and treatment system and method provided by the invention,
It is matched by electronic health record with the medical record templates in history medical record templates library, artificial intelligence is recycled to learn each doctor expert
The experience of therapeutic scheme.The diagnosis and treatment method that intelligent diagnosis and treatment are carried out to illness, provides the most effective treatment method of history associated disease
And the synthesis of the therapeutic scheme of the experience of current each such expert, to assist general doctor to diagnose.Therefore, example of the present invention
It solves in current medical and health services, the medical level of doctor, Er Qieyou not only can be improved in the horizontal insufficient problem of doctor
Effect reduces the misdiagnosis rate of doctor.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with
It obtains other drawings based on these drawings.
Fig. 1 is to interact signal with hospital terminal when the intelligent assisting in diagnosis and treatment system of the present invention is applied to the server of hospital
Figure；
Fig. 2 is the hardware structure schematic diagram of server applied by the intelligent assisting in diagnosis and treatment system of the present invention；
Fig. 3 is the functional block diagram of the first embodiment of intelligent assisting in diagnosis and treatment system provided by the invention；
Fig. 4 is the functional block diagram of the second embodiment of intelligent assisting in diagnosis and treatment system provided by the invention；
Fig. 5 is the log-in interface schematic diagram of intelligent assisting in diagnosis and treatment system provided by the invention；
Fig. 6 is the interface schematic diagram after intelligent assisting in diagnosis and treatment system login provided by the invention；
Fig. 7 is the functional block diagram of the 3rd embodiment of intelligent assisting in diagnosis and treatment system provided by the invention；
Fig. 8 is the flow chart of the first embodiment of intelligent assisting in diagnosis and treatment method provided by the invention；
Fig. 9 is the flow chart of the second embodiment of intelligent assisting in diagnosis and treatment method provided by the invention；
Figure 10 is the flow chart of the 3rd embodiment of intelligent assisting in diagnosis and treatment method provided by the invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
As shown in Figure 1, intelligent assisting in diagnosis and treatment system of the invention may be disposed in server 100.The server 100 for
Terminal 500 (for example, computer terminal of all kinds of hospitals, diagnosis and treatment terminal etc.) and other doctors linked by cloud platform 200 in institute
Institute's terminal 300 accesses.All kinds of hospitals can be communicated by network cloud platform 200 and server 100.That is the server 100
It can be located in the local area network of hospital, and be visited for other hospitals of hospital subordinate by wide area network or mobile Internet
It asks.To access database 400, it is necessary to which, through effective authentication, including doctor's face recognition, identity information password is stepped on
Land or speech recognition only pass through the user of authentication or the accessible database 400 of terminal.
Server 100 also has the function of database access, which is used to store Various types of data, such as medicine is known
Knowledge, patient diagnosis information, diagnosis experience and therapeutic scheme etc..When server 100 receives the place of user or terminal
After reason demand, is wanted to obtain more illness information comparisons according to terminal requirements, may also access cloud platform 200, to transfer cloud platform 200
In data, cloud platform links other hospital terminal news files, uses for doctor.In the present embodiment, which can be with
In server 100, accessed convenient for server 100.Certainly, in another embodiment, the server 100 can also and cloud platform
It is provided separately, i.e., cloud platform 200 is isolated with the formation of database 400, the server 100 only authorized could access between 200
The data safety of database so can be improved in the database.
As shown in Fig. 2, above-mentioned database 100 may include processor 101, storage equipment 102, user interactive module 103, lead to
News center 104.Communication center 104 is used for for the communication between each building block in server 100, user interactive module 103
Receive information, the instruction etc. of user's input, such as touch screen, mouse, keyboard, voice, recognition of face etc..Communication center 104
It is communicated with each other for server 100 with outside, which may include wireline interface and wireless interface, example
Such as RS232 module, radio-frequency module, WIFI module.Storing equipment 102 may include that one or more are computer-readable
Storage medium, and it not only includes internal storage, further includes external memory.Be stored in the memory operating system and
Holographic assisting in diagnosis and treatment system etc..Processor 101 is used to call holographic assisting in diagnosis and treatment system and other groups in memory 102
(for example, user interactive module 103, communication center 104) is built, holographic assisting in diagnosis and treatment information etc. is provided for doctor.
Fig. 3 is the functional block diagram of the first embodiment of intelligent assisting in diagnosis and treatment system provided by the invention.Such as Fig. 3 institute
Show, intelligence assisting in diagnosis and treatment system provided in this embodiment includes:
Receiving module 110, for receiving case history；
Categorization module 120, for the case history received to be carried out classification processing according to disease type, and will be after classification
The medical records storage to corresponding database；
Matching module 130 obtains matching degree for matching the case history with the medical record templates in medical record templates library
Greater than the medical record templates of preset threshold, wherein medical record templates store disease type and illness information corresponding with disease type；
Secondary diagnostic module 140, matched disease type and illness information corresponding with disease type for obtaining, benefit
Manually intelligent convolutional neural networks learning method provides corresponding historical diagnostic reference scheme, and exports the matched disease class of institute
Type and illness information corresponding with disease type, for doctor's reference.
Above-mentioned receiving module 110 receives the case history being uploaded in server 100 by communication center 104；Then the classification
The case history received is carried out classification processing according to disease type by module 120, and by the sorted medical records storage to accordingly
Database；Matching module 130 matches the case history received with the medical record templates in the medical record templates library in database 400
The disease type that match degree is greater than the preset threshold is obtained, the disease type that match degree is greater than the preset threshold here may have multiple.
In the present embodiment, matched disease type will be set and be up to 10 kinds, if when the disease type that match degree is greater than the preset threshold, it will
The disease type for meeting condition is ranked up from big to small according to matching degree.The secondary diagnostic module 140 is according to matched disease
Illness information corresponding with the disease type is extracted in complementary diagnostic information library of the type into database 400, utilizes artificial intelligence
Convolutional neural networks learning method provides corresponding historical diagnostic reference scheme, meanwhile, extracted illness information is passed through into net
Network communication module 104 is back to the terminal for uploading case history.If doctor according in matched medical record templates disease type and
The corresponding illness information of disease type does not such as find matching illness, then secondary diagnostic module 140 is rolled up by artificial intelligence
Product neural network algorithm after the disease type provided in conjunction with this illness expert opinion, obtains the corresponding assisting in diagnosis and treatment of corresponding disease
Scheme is referred to for doctor.
Above-mentioned medical record templates library further include: normal including 300 kinds of general practices from the standard medical record templates of evidence-based medicine EBM
See frequently-occurring disease, and the medical record templates library updates timing.Medical record templates are classified by disease type, and every class disease type is corresponding
The information of disease may include main suit, present illness history, past medical history, positive sign and laboratory examination result, image check result, gene inspection
Observe and predict announcement, vital sign, statement-of-health etc..
Intelligence assisting in diagnosis and treatment system provided in this embodiment, passes through the medical record templates of electronic health record and history medical record templates library
It is matched, artificial intelligence is recycled to learn the experience of each doctor expert's therapeutic scheme.Intelligent diagnosis and treatment are carried out to illness to examine
Treatment method provides the comprehensive of the therapeutic scheme of the most effective treatment method of history associated disease and the experience of current each such expert
It closes, to assist general doctor to diagnose.Therefore, the present embodiment solves in current medical and health services, and doctor is horizontal insufficient
The problem of, the medical level of doctor not only can be improved, and effectively reduce the misdiagnosis rate of doctor.
Fig. 4 is the functional block diagram of the second embodiment of intelligent assisting in diagnosis and treatment system provided by the invention.With Fig. 3 institute
The first embodiment shown is compared, intelligence assisting in diagnosis and treatment system provided in this embodiment further include:
Conversion module 150, for by text and image analysis according to artificial intelligence deep learning method by text case history
It is converted into the electronic health record of standardization, the electronic health record of the electronic health record of non-standardization and half standardization is advised according to systemic presupposition
Then it is converted into the electronic health record of standardization；
Artificial intelligence module 160, for according to the disease type of patient by several doctors to matched disease type
Therapeutic scheme carries out global alignment, obtains including that the diagnosis and treatment scheme of correspondence illness information and similar conditions information is sent to auxiliary and examines
Disconnected module.
It is above-mentioned that system in institute can be applied to based on intelligent assisting in diagnosis and treatment system, to ensure information security in institute, and simultaneously may be used
Linked network cloud platform supplies other hospital, alliance shared datas.As shown in figure 3, by conversion module 150 can obtain sufferer from its
Its hospital transfers from one hospital to another to the text case history of this hospital or is converted to standard from other hospitals acquisition patient data by authentication
Case history matches database or cloud platform database in institute after being uploaded to receiving module.
It is matched for the ease of disease type of the medical record templates to electronic health record, the case medical record templates in medical record templates library are equal
Medical record templates for same format, and hospital's offer are not usually the medical record templates standardized.Therefore the intelligence that this city the first provides
The image identification function that diagnosis and therapy system is provided by conversion module can identify that electronics and text case history are converted into preset standard
Information module.Remaining will not use artificial intelligence module 160 to carry out data processing, classification information with the matched information of module information
Translate into other supplementary information modules of intelligent assisting in diagnosis and treatment.Artificial intelligence module 140 can also pass through intelligent interaction module
220 merge with other systems information in institute and are learnt by intelligence learning scheme, out of, other institutes of the hospital's enterprises union
System calls related medical record information to be learnt and judged for artificial intelligence module, is passed to auxiliary diagnosis mould after providing intelligent result
Block provides doctor's assisting in diagnosis and treatment scheme according to illness demand.
Further, the intelligent assisting in diagnosis and treatment system of the present embodiment further include:
Speech recognition module, for acquisition voice signal and identified, the voice messaging of identification is converted into text
Information, and corresponding position of the typing into patient medical history template.
Further, above-mentioned server 100 can provide access network address or access interface, doctor using computer, mobile phone, wear
Device end is worn to access the access network address or link the access interface.As shown in figure 5, doctor can by account and password and
Face identification functions log in intelligent assisting in diagnosis and treatment system, and doctor must register on server 100, and by auditing in institute, note
Volume can just log in after auditing successfully.As shown in fig. 6, doctor can consult all patient's illnesss after logging in holographic assisting in diagnosis and treatment system
Historical information, diagnosis and treatment scheme, therapeutic scheme track process, scheme effective percentage feedback.
Fig. 7 is the functional block diagram of the 3rd embodiment of intelligent assisting in diagnosis and treatment system provided by the invention.With Fig. 3 institute
The first embodiment shown is compared, intelligence assisting in diagnosis and treatment system provided in this embodiment further include:
Tracking and monitoring module 170, for after doctor determines the disease type of patient, checking whether there is also not in case history
Examined project or the process not being diagnosed, timely feedbacked in subsequent therapeutic scheme the implementation progress of therapeutic scheme and to
Therapeutic effect analysis report out prompts doctor whether to need to modify therapeutic scheme over the course for the treatment of and carries out secondary assisting in diagnosis and treatment.
Remote communication module 180, for providing the external interface of intelligent assisting in diagnosis and treatment system and remote assistant system communication,
And the remote access request of doctor is received, and establish and communicate according to access request and remote assistant system, remotely exist
Line auxiliary.
In the present embodiment, assisting in diagnosis and treatment scheme will also be optimized using the opinion of doctor, doctor is being directed to the disease
When, the project for needing to check or the diagnosis algorithm according to required for evidence-based medicine EBM give the reference of the newest medical knowledge of doctor,
Such as the medical procedure for the associated disease not carried out according to evidence-based medicine EBM, then prompt information is issued.The tracking and monitoring module 170 may be used also
With doctor according to matched disease type and the corresponding illness information of disease type and pass through intelligent algorithm obtain
After disease correlation type, check whether there is also not examined project or the processes not being diagnosed in the electronic health record, rear
Timely feedback the effective percentage of therapeutic scheme in continuous therapeutic scheme and provide treated effect analysis report, prompt doctor whether
It needs to modify therapeutic scheme in therapeutic process and carries out secondary assisting in diagnosis and treatment.
In the present embodiment, above-mentioned intelligent assisting in diagnosis and treatment system additionally provides remote online miscellaneous function, that is, provides long-range
The external interface of supplemental communication.Remote communication module 180 by according to the remote access request of doctor, provided by outside connect
Mouth establishes connection with remote assistant system.In the present embodiment, doctor passes through intelligent assisting in diagnosis and treatment system and the remote assistant system
After establishing the link, doctor can remotely connect sufferer or related specialist, and can be shared corresponding by assisting in diagnosis and treatment system
Illness information and history sufferer information and diagnosis and treatment scheme.
Correspondingly, the present invention also provides a kind of intelligent assisting in diagnosis and treatment methods.Fig. 8 is intelligent assisting in diagnosis and treatment provided by the invention
The flow chart of the first embodiment of method, as shown in figure 8, it is provided by the invention intelligence assisting in diagnosis and treatment method the following steps are included:
Step S110: case history is received；
Step S120: the case history received is carried out by classification processing according to disease type, and will be sorted described
Medical records storage is to corresponding database；
Step S130: the case history is matched with the medical record templates in medical record templates library, is obtained matching degree and is greater than in advance
If the medical record templates of threshold value, wherein medical record templates store disease type and illness information corresponding with disease type；
Step S140: the matched disease type of institute and illness information corresponding with disease type are obtained, artificial intelligence is utilized
Convolutional neural networks learning method provides corresponding historical diagnostic reference scheme, and exports the matched disease type of institute and and disease
The corresponding illness information of type, for doctor's reference.
Intelligence assisting in diagnosis and treatment method provided in this embodiment, passes through the medical record templates of electronic health record and history medical record templates library
It is matched, artificial intelligence is recycled to learn the experience of each doctor expert's therapeutic scheme.Intelligent diagnosis and treatment are carried out to illness to examine
Treatment method provides the comprehensive of the therapeutic scheme of the most effective treatment method of history associated disease and the experience of current each such expert
It closes, to assist general doctor to diagnose.Therefore, the present embodiment solves in current medical and health services, and doctor is horizontal insufficient
The problem of, the medical level of doctor not only can be improved, and effectively reduce the misdiagnosis rate of doctor.
Fig. 9 is the flow chart of the second embodiment of intelligent assisting in diagnosis and treatment method provided by the invention, as shown in figure 9, this hair
The intelligent assisting in diagnosis and treatment method of bright offer the following steps are included:
Step S210: case history is received；
Step S220: according to preset transformation rule, case history is converted.
Specifically, if received case history is document case history, by text and image analysis according to artificial intelligence deep learning
Text case history is converted into the electronic health record of standardization by method；If received case history is that the electronic health record of non-standardization and half standardize
The electronic health record of the electronic health record of non-standardization and half standardization is converted established practice according to systemic presupposition rule by the electronic health record of change
The electronic health record of generalized.Above-mentioned intelligence assisting in diagnosis and treatment system application, can use with the hospital, alliance of hospital.It, can by this step
The electronic health record that any type of case history (electronic health record, text case history) that hospital, alliance provides is converted to standardization is stored in
Cloud platform.It is matched for the ease of disease type of the intelligent assisting in diagnosis and treatment system to electronic health record, the electronics disease in medical record templates library
Template is gone through as unified format, and the case history that the hospital, alliance provides is not usually specification case history.Therefore, when intelligent assisting in diagnosis and treatment system
It whether will be specification case history using the current archives of artificial intelligence automatic identification after system receives the case history of hospital, alliance upload.If
The electronic health record received is not specification case history, then according to pre-set transformation rule, the case history of hospital, alliance is converted to
Specification case history.
Step S230: the case history received is carried out by classification processing according to disease type, and will be sorted described
Medical records storage is to corresponding database；
Step S240: the case history is matched with the medical record templates in medical record templates library, is obtained matching degree and is greater than in advance
If the medical record templates of threshold value, wherein medical record templates store disease type and illness information corresponding with disease type；
Step S250: the matched disease type of institute and illness information corresponding with disease type are obtained, artificial intelligence is utilized
Convolutional neural networks learning method provides corresponding historical diagnostic reference scheme, and exports the matched disease type of institute and and disease
The corresponding illness information of type, for doctor's reference.
Step S260: according to the disease type of patient by several doctors to matched disease type therapeutic scheme carry out
Global alignment obtains including that the diagnosis and treatment scheme of corresponding illness information and similar conditions information is sent to doctor.
Step S270: after doctor determines the disease type of patient, check whether there is also not examined items in case history
Mesh or the process not being diagnosed timely feedback the implementation progress of therapeutic scheme in subsequent therapeutic scheme and provide therapeutic effect
Analysis report prompts doctor whether to need to modify therapeutic scheme over the course for the treatment of and carries out secondary assisting in diagnosis and treatment.
Specifically, above-mentioned intelligent assisting in diagnosis and treatment system additionally provides the corresponding diagnosis and treatment auxiliary information of disease type.Above-mentioned intelligence
Can assisting in diagnosis and treatment system after illness information corresponding to disease type and disease type in matched medical record templates, the information
It is displayed on terminal screen, is checked for doctor.Doctor is according to the corresponding illness of disease type and disease type of display
Information, then according to artificial intelligence convolutional neural networks algorithm obtain as a result, determine patient disease type after, intelligence assist
Diagnosis and therapy system then obtains the corresponding assisting in diagnosis and treatment scheme of the disease type from database, and provides and utilize artificial intelligence convolution mind
The diagnosis and treatment scheme obtained through network algorithm, such as the inspection item that the disease currently lacks treat process, therapeutic regimen, diagnosis and treatment
Scheme etc..
In the present embodiment, doctor according to disease type and the corresponding disease of disease type in matched medical record templates library
Disease information after the disease type for determining patient, carries out the assisting in diagnosis and treatment scheme that artificial intelligence convolutional neural networks algorithm provides, supplies
Doctor's reference, further assists doctor to judge.In addition, the present embodiment can also give the historical therapeutic of the disease type
The data of scheme and therapeutic effect.Moreover, above-mentioned intelligence assisting in diagnosis and treatment systematic connection database can check that other doctors share
Current therapeutic effective percentage be greater than preset threshold therapeutic scheme report, for doctor refer to.
Figure 10 is the flow chart of the 3rd embodiment of intelligent assisting in diagnosis and treatment method provided by the invention, as shown in Figure 10, phase
Compared with first embodiment shown in Fig. 8, intelligence assisting in diagnosis and treatment method provided in this embodiment is further comprising the steps of:
The remote access request of doctor is received, and is established and is communicated according to the access request and remote assistant system, to carry out
Remote online auxiliary.
Specifically, above-mentioned intelligent assisting in diagnosis and treatment system provides remote online miscellaneous function, that is, provides and remote assistant system
The external interface of communication.Intelligent assisting in diagnosis and treatment system by according to the remote access request of doctor, provided by external interface
It is established the link with remote assistant system.In the present embodiment, doctor is built by intelligent assisting in diagnosis and treatment system with the remote assistant system
After vertical connection, doctor can help with remote assistance to the more professional doctor of this illness, including illness vital sign with
And other corresponding signs or surgical procedure etc. are shared, operation remote assistance etc..
Further, further comprising the steps of in other preferred embodiments of the invention:
Patient medical history template is provided, the voice signal of doctor is received, voice signal collected is identified, will identify
Voice messaging be converted to text information, and corresponding position of the typing into patient medical history template, generate case history.
Above disclosed is only a preferred embodiment of the present invention, cannot limit the power of the present invention with this certainly
Sharp range, those skilled in the art can understand all or part of the processes for realizing the above embodiment, and weighs according to the present invention
Benefit requires made equivalent variations, still belongs to the scope covered by the invention.
Claims (12)
1. a kind of intelligence assisting in diagnosis and treatment system characterized by comprising
Receiving module, for receiving case history；
Categorization module, for the case history received to be carried out classification processing according to disease type, and will be sorted described
Medical records storage is to corresponding database；
Matching module obtains matching degree and is greater than in advance for matching the case history with the medical record templates in medical record templates library
If the medical record templates of threshold value, wherein medical record templates store disease type and illness information corresponding with disease type；
Secondary diagnostic module, for obtaining institute's matched disease type and illness information corresponding with disease type, using artificial
Intelligent convolutional neural networks learning method provides corresponding historical diagnostic reference scheme, and export the matched disease type of institute and with
The corresponding illness information of disease type, for doctor's reference.
2. intelligence assisting in diagnosis and treatment system according to claim 1, which is characterized in that further include:
Conversion module, for text case history to be converted established practice according to artificial intelligence deep learning method by text and image analysis
The electronic health record of the electronic health record of non-standardization and half standardization is converted by the electronic health record of generalized according to systemic presupposition rule
The electronic health record of standardization.
3. intelligence assisting in diagnosis and treatment system according to claim 1, which is characterized in that further include:
Artificial intelligence module, for according to the disease type of patient by several doctors to matched disease type therapeutic scheme
Global alignment is carried out, obtains including that correspondence illness information and the diagnosis and treatment scheme of similar conditions information are sent to secondary diagnostic module.
4. intelligence assisting in diagnosis and treatment system according to claim 1, which is characterized in that further include:
Tracking and monitoring module, for after doctor determines the disease type of patient, checking whether there is also be not examined in case history
Project or the process that is not diagnosed, the implementation progress of therapeutic scheme is timely feedbacked in subsequent therapeutic scheme and provides treatment
Effect analysis report prompts doctor whether to need to modify therapeutic scheme over the course for the treatment of and carries out secondary assisting in diagnosis and treatment.
5. intelligence assisting in diagnosis and treatment system according to claim 1, which is characterized in that further include:
Remote communication module, for providing the external interface of intelligent assisting in diagnosis and treatment system and remote assistant system communication, Yi Jijie
The remote access request of doctor is received, and is established and is communicated according to access request and remote assistant system, to carry out remote online auxiliary.
6. intelligence assisting in diagnosis and treatment system according to claim 1, which is characterized in that further include:
Speech recognition module, for acquisition voice signal and identified, the voice messaging of identification is converted into text information,
And corresponding position of the typing into patient medical history template.
7. a kind of intelligence assisting in diagnosis and treatment method, which comprises the following steps:
Receive case history；
The case history received is subjected to classification processing according to disease type, and by the sorted medical records storage to accordingly
Database；
The case history is matched with the medical record templates in medical record templates library, obtains the case history mould that match degree is greater than the preset threshold
Plate, wherein medical record templates store disease type and illness information corresponding with disease type；
The matched disease type of institute and illness information corresponding with disease type are obtained, artificial intelligence convolutional neural networks are utilized
Learning method provides corresponding historical diagnostic reference scheme, and exports the matched disease type of institute and illness corresponding with disease type
Information, for doctor's reference.
8. intelligence assisting in diagnosis and treatment method according to claim 7, which is characterized in that the case history include electronic health record and/
Or document case history, after receiving case history further include:
It is according to artificial intelligence deep learning method that text is sick by text and image analysis if received case history is document case history
Go through the electronic health record for being converted into standardization；
If received case history is the electronic health record of non-standardization and the electronic health record of half standardization, by the electronic health record of non-standardization
And partly the electronic health record of standardization is converted into the electronic health record of standardization according to systemic presupposition rule.
9. intelligence assisting in diagnosis and treatment method according to claim 7, which is characterized in that obtain the matched disease type of institute and
Illness information corresponding with disease type provides corresponding historical diagnostic using artificial intelligence convolutional neural networks learning method and joins
Scheme is examined, and exports the matched disease type of institute and illness information corresponding with disease type, for the step of doctor's reference
After rapid further include:
According to the disease type of patient by several doctors to matched disease type therapeutic scheme carry out global alignment, obtain
Diagnosis and treatment scheme including corresponding illness information and similar conditions information is sent to doctor.
10. intelligence assisting in diagnosis and treatment method according to claim 7, which is characterized in that further include:
After doctor determines the disease type of patient, check in case history whether not to be diagnosed there is also not examined project or
Process timely feedbacks the implementation progress of therapeutic scheme in subsequent therapeutic scheme and provides therapeutic effect analysis report, prompts
Whether doctor needs to modify therapeutic scheme over the course for the treatment of carries out secondary assisting in diagnosis and treatment.
11. intelligence assisting in diagnosis and treatment method according to claim 7, which is characterized in that further include:
The remote access request of doctor is received, and is established and is communicated according to the access request and remote assistant system, it is long-range to carry out
Online auxiliary.
12. intelligence assisting in diagnosis and treatment method according to claim 7, which is characterized in that further include:
Patient medical history template is provided, the voice signal of doctor is received, voice signal collected is identified, by the language of identification
Message breath is converted to text information, and corresponding position of the typing into patient medical history template, generates case history.
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/CN2018/101271 WO2020037454A1 (en) | 2018-08-20 | 2018-08-20 | Smart auxiliary diagnosis and treatment system and method |
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| Publication Number | Publication Date |
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| CN110249392A true CN110249392A (en) | 2019-09-17 |
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| CN201880008002.1A Pending CN110249392A (en) | 2018-08-20 | 2018-08-20 | Intelligent assisting in diagnosis and treatment system and method |
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| WO (1) | WO2020037454A1 (en) |
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| CN116453641B (en) * | 2023-06-19 | 2023-09-05 | 潍坊医学院附属医院 | Data processing method and system for auxiliary analysis information of traditional Chinese medicine |
| CN117153319A (en) * | 2023-09-05 | 2023-12-01 | 上海分值医学科技有限公司 | Electronic medical record data intelligent analysis system based on artificial intelligence |
| CN117153319B (en) * | 2023-09-05 | 2024-02-23 | 上海分值医学科技有限公司 | Electronic medical record data intelligent analysis system based on artificial intelligence |
| CN116895372A (en) * | 2023-09-11 | 2023-10-17 | 之江实验室 | Intelligent first-aid grading system based on large-scale language model and meta-learning |
| CN116895372B (en) * | 2023-09-11 | 2024-02-09 | 之江实验室 | Intelligent first-aid grading system based on large-scale language model and meta-learning |
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