CN110085316A - A kind of hypertension question answering system and its system method for building up based on deep learning - Google Patents
A kind of hypertension question answering system and its system method for building up based on deep learning Download PDFInfo
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- CN110085316A CN110085316A CN201910391205.XA CN201910391205A CN110085316A CN 110085316 A CN110085316 A CN 110085316A CN 201910391205 A CN201910391205 A CN 201910391205A CN 110085316 A CN110085316 A CN 110085316A
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- hypertension
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- 206010020772 Hypertension Diseases 0.000 title claims abstract description 51
- 238000003745 diagnosis Methods 0.000 claims abstract description 18
- 230000004048 modification Effects 0.000 claims description 9
- 238000006011 modification reactions Methods 0.000 claims description 9
- 230000036772 blood pressure Effects 0.000 claims description 3
- 230000001419 dependent Effects 0.000 claims description 3
- 235000005911 diet Nutrition 0.000 claims description 3
- 230000000378 dietary Effects 0.000 claims description 3
- 230000003993 interaction Effects 0.000 claims description 3
- 230000035800 maturation Effects 0.000 claims description 3
- 210000001519 tissues Anatomy 0.000 claims description 3
- 210000004556 Brain Anatomy 0.000 claims 1
- 238000010276 construction Methods 0.000 description 3
- 238000000034 methods Methods 0.000 description 3
- 238000005516 engineering processes Methods 0.000 description 2
- 239000000203 mixtures Substances 0.000 description 2
- 230000001360 synchronised Effects 0.000 description 2
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Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/332—Query formulation
- G06F16/3329—Natural language query formulation or dialogue systems
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/26—Speech to text systems
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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
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
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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
- G16H80/00—ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
Abstract
Description
Technical field
The present invention relates to a kind of medical question answering systems, and in particular to a kind of hypertension question answering system based on deep learning and Its system method for building up.
Background technique
In the past, in such a way that search engine obtains knowledge, user's a large amount of time is on the one hand wasted；On the other hand it is curing The field of disease inquiry is treated, the good and bad jumbled together for information source, and user's resolving ability is limited, and there are misguided possibilities.Traditional asks Answering community needs human-edited's answer, and period of reservation of number is longer, along with the development of the artificial intelligence technologys such as NLP, knowledge mapping, Instant Health information service is provided in the form of question and answer for user to be possibly realized.
So needing a novel intelligent Answer System, which can satisfy user to specific hypertension medical field Question and answer demand, can recognize that the answer of inquiry is expressed and quickly can correctly be provided to the colloquial style of user.
Summary of the invention
The purpose of the present invention is to provide a kind of hypertension question answering system and its system method for building up based on deep learning, To solve the problems, such as that existing time-consuming by search engine acquisition medical knowledge and information accuracy difficulty is sentenced.
In order to solve the above technical problems, the present invention adopts the following technical scheme:
A kind of hypertension question answering system based on deep learning, the system comprises voice pick devices, voice paraphrase module, language Sound literal pool, hypertension medical knowledge base, question and answer knowledge base, reasoning diagnosis reply module and reply feedback module；
The voice pick device is used to being converted to the voice messaging of user into electric signal, inputs voice paraphrase module；
The voice paraphrase module utilizes the language message in language and characters library, for analyzing the language message of user's input, analysis Content the problem of user out；
The reasoning diagnosis replies the problem of module receives language paraphrase module content, retrieves hypertension medical knowledge according to problem The diagnosis input content of missing is sent to answer feedback module when lacking dependent diagnostic input by library and question and answer knowledge base, when After obtaining complete diagnosis input, reasoning diagnosis replies module and obtains the highest answer of confidence level, is sent to answer feedback module；
The answer feedback module will be for that will reply through language, text or photo feedback to user.
Preferably, above-mentioned voice pick device includes the microphone of the microphone of smart machine, the microphone of mobile phone and computer.
Preferably, the problem of above-mentioned voice paraphrase module analysis comes out content include blood pressure values, symptom, special population and Dietetic variety.
Preferably, above-mentioned answer feedback module by the microphone of smart machine or display, mobile phone loudspeaker or Screen, the loudspeaker of computer or screen are by language, text or photo feedback to user.
A kind of hypertension question answering system method for building up based on deep learning, method for building up specifically comprise the following steps:
Step1: voice pick device needed for establishing system operation and the hardware for replying feedback module, realize system and user it Between information interaction；
Step2: the language and characters library based on existing maturation constructs voice paraphrase module, writing system software；
Step3: the existing medical knowledge relevant to hypertension of typing constructs hypertension medical knowledge base, and in system operation In constantly improve the hypertension medical knowledge base constructed；
Step4: being based on existing network question and answer relevant to hypertension, constructs question and answer knowledge base；
Step5: in system operation, tissue doctor is reviewed modification to system replies result, and system passes through doctor's Modification is checked, constantly improve and updates hypertension knowledge library and question and answer knowledge base.
Preferably, existing medical knowledge relevant to the hypertension source in above-mentioned Step3 include books, periodical and High-level meeting paper.
Preferably, the existing network question and answer relevant to hypertension in above-mentioned Step4 include the question and answer of professional forum, hospital The medical software information of webpage and profession.
The present invention has the advantage that
It takes the present invention is based on after the scheme of the hypertension question answering system of deep learning, realizes to existing medical knowledge and question and answer The combination of system realizes the consulting to user and is correctly identified；Integrate the base of existing medical system and question answering system knowledge On plinth, in conjunction with the Real-time Feedback synchronous refresh knowledge base of doctor, completes and the system Construction correctly replied is provided to user's question and answer, User is allowed to obtain reliable medical advice or answer in time by the system.
Detailed description of the invention
Fig. 1 is a kind of work flow diagram of the hypertension question answering system embodiment based on deep learning of the present invention；
Fig. 2 is a kind of process of construction process of the hypertension question answering system method for building up embodiment based on deep learning of the present invention Figure.
Specific embodiment
Embodiments of the present invention are illustrated by particular specific embodiment below, those skilled in the art can be by this explanation Content disclosed by book is understood other advantages and efficacy of the present invention easily.
It should be clear that this specification structure depicted in this specification institute accompanying drawings, ratio, size etc., only to cooperate specification to be taken off The content shown is not intended to limit the invention enforceable qualifications so that those skilled in the art understands and reads, therefore Do not have technical essential meaning, the modification of any structure, the change of proportionate relationship or the adjustment of size are not influencing the present invention Under the effect of can be generated and the purpose that can reach, it should all still fall in disclosed technology contents and obtain the model that can cover In enclosing.Meanwhile cited such as "upper", "lower", " left side ", the right side in this specification ", the term of " centre ", be merely convenient to chat That states is illustrated, rather than to limit the scope of the invention, relativeness is altered or modified, and is changing skill without essence It is held in art, when being also considered as the enforceable scope of the present invention.
Embodiment 1
Referring to Fig. 1, a kind of hypertension question answering system based on deep learning, the system comprises voice pick device, voices to release Adopted module, language and characters library, hypertension medical knowledge base, question and answer knowledge base, reasoning diagnosis reply module and reply feedback module； Voice pick device includes the microphone of the microphone of smart machine, the microphone of mobile phone and computer, for turning the voice messaging of user It is changed to electric signal, inputs voice paraphrase module；Voice paraphrase module utilizes the language message in language and characters library, for analyzing user The language message of input, the problem of analyzing user content, analyze the problem content come include blood pressure values, it is symptom, special Crowd and dietetic variety；Reasoning diagnosis replies the problem of module receives language paraphrase module content, retrieves hypertension according to problem It is anti-to be sent to answer when lacking dependent diagnostic input by medical knowledge base and question and answer knowledge base for the diagnosis input content of missing Module is presented, after obtaining complete diagnosis input, reasoning diagnosis replies module and obtains the highest answer of confidence level, is sent to answer Feedback module；It replies feedback module and passes through the microphone of smart machine or display, the loudspeaker of mobile phone or screen, computer Perhaps photo feedback is anti-by language, text or photo for that will reply to user by language, text for loudspeaker or screen Feed user.
In embodiment, the method for the voice messaging of above-mentioned voice paraphrase module analysis user input, first is that using nature language Speech technology carries out profound understanding to problem, understanding content include be intended to analysis, name Entity recognition, interdependent syntactic analysis, Word sense disambiguation etc.；It is included into different classifications second is that puing question to user by Question Classification, is enabled a system to for different problem classes Type obtains candidate answers set using different answer feedback mechanism；Third is that extracting main completion customer problem by problem focus Information requirement accurate positioning, obtain accurate user put question to the problem of content.
Referring to fig. 2, a kind of hypertension question answering system method for building up based on deep learning, method for building up specifically includes as follows Step:
Step1: voice pick device needed for establishing system operation and the hardware for replying feedback module, realize system and user it Between information interaction；
Step2: the language and characters library based on existing maturation constructs voice paraphrase module, writing system software；
Step3: (existing medical knowledge relevant with hypertension source includes figure to the existing medical knowledge relevant to hypertension of typing Book, periodical and high-level meeting paper) building hypertension medical knowledge base, and structure is constantly improve in system operation The hypertension medical knowledge base built；
Step4: based on existing network question and answer relevant to hypertension, (existing network question and answer relevant with hypertension include profession opinion The medical software information of altar, the question and answer webpage of hospital and profession), construct question and answer knowledge base；
Step5: in system operation, tissue doctor is reviewed modification to system replies result, and system passes through doctor's Modification is checked, constantly improve and updates hypertension knowledge library and question and answer knowledge base, the machine learning frame increased income using Google TensorFlow, which improve to hypertension knowledge library and question and answer knowledge base, to be updated and completes to diagnose reasoning the mould for replying module Type training.
Take the present invention is based on after the scheme of the hypertension question answering system of deep learning, realizing to existing medical knowledge and The combination of question answering system realizes the consulting to user and is correctly identified；Integrate existing medical system and question answering system knowledge On the basis of, in conjunction with the Real-time Feedback synchronous refresh knowledge base of doctor, completes and the system correctly replied is provided to user's question and answer Construction allows user to obtain reliable medical advice or answer in time by the system.
In actual use, with the increase of number of users, the rising of question and answer number checks result with doctor, The answer accuracy and reliability of system is gradually increasing, and obtains more accurate and reliable diagnosis capability with the development of medical treatment.
Although above having used general explanation and specific embodiment, the present invention is described in detail, at this On the basis of invention, it can be made some modifications or improvements, this will be apparent to those skilled in the art.Therefore, These modifications or improvements without departing from theon the basis of the spirit of the present invention are fallen within the scope of the claimed invention.
Claims (7)
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Citations (4)
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| CN106202301A (en) * | 2016-07-01 | 2016-12-07 | 武汉泰迪智慧科技有限公司 | A kind of intelligent response system based on degree of depth study |
| CN106557653A (en) * | 2016-11-15 | 2017-04-05 | 合肥工业大学 | A kind of portable medical intelligent medical guide system and method |
| CN109545391A (en) * | 2018-10-26 | 2019-03-29 | 曾警卫 | A kind of intelligent medical automatically request-answering system and application method based on deep learning |
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2019
- 2019-05-11 CN CN201910391205.XA patent/CN110085316A/en active Search and Examination
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20130116128A (en) * | 2012-04-14 | 2013-10-23 | 윤재민 | Question answering system using speech recognition by tts, its application method thereof |
| CN106202301A (en) * | 2016-07-01 | 2016-12-07 | 武汉泰迪智慧科技有限公司 | A kind of intelligent response system based on degree of depth study |
| CN106557653A (en) * | 2016-11-15 | 2017-04-05 | 合肥工业大学 | A kind of portable medical intelligent medical guide system and method |
| CN109545391A (en) * | 2018-10-26 | 2019-03-29 | 曾警卫 | A kind of intelligent medical automatically request-answering system and application method based on deep learning |
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