CN118528289B - Hospital diagnosis guiding robot with decision support and method thereof - Google Patents
Hospital diagnosis guiding robot with decision support and method thereof Download PDFInfo
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- CN118528289B CN118528289B CN202410809290.8A CN202410809290A CN118528289B CN 118528289 B CN118528289 B CN 118528289B CN 202410809290 A CN202410809290 A CN 202410809290A CN 118528289 B CN118528289 B CN 118528289B
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- 238000003745 diagnosis Methods 0.000 title claims abstract description 87
- 238000000034 method Methods 0.000 title claims abstract description 33
- 230000003993 interaction Effects 0.000 claims abstract description 48
- 238000004458 analytical method Methods 0.000 claims abstract description 38
- 238000004891 communication Methods 0.000 claims abstract description 24
- 201000010099 disease Diseases 0.000 claims description 40
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 40
- 238000004590 computer program Methods 0.000 claims description 14
- 208000016354 hearing loss disease Diseases 0.000 claims description 14
- 230000008451 emotion Effects 0.000 claims description 12
- 238000010219 correlation analysis Methods 0.000 claims description 5
- 238000007405 data analysis Methods 0.000 claims description 5
- 206010011878 Deafness Diseases 0.000 claims description 3
- 208000016621 Hearing disease Diseases 0.000 claims description 3
- 238000013473 artificial intelligence Methods 0.000 claims description 3
- 230000006735 deficit Effects 0.000 claims description 3
- 238000005516 engineering process Methods 0.000 claims description 3
- 230000000875 corresponding effect Effects 0.000 description 11
- 230000002596 correlated effect Effects 0.000 description 2
- 230000002996 emotional effect Effects 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 208000007882 Gastritis Diseases 0.000 description 1
- 206010019375 Helicobacter infections Diseases 0.000 description 1
- 206010028980 Neoplasm Diseases 0.000 description 1
- 208000005718 Stomach Neoplasms Diseases 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
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- 238000013500 data storage Methods 0.000 description 1
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- 238000010586 diagram Methods 0.000 description 1
- 210000005069 ears Anatomy 0.000 description 1
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- 230000001815 facial effect Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 206010017758 gastric cancer Diseases 0.000 description 1
- 210000001035 gastrointestinal tract Anatomy 0.000 description 1
- 208000019423 liver disease Diseases 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
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- 230000002485 urinary effect Effects 0.000 description 1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J11/00—Manipulators not otherwise provided for
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
- B25J9/161—Hardware, e.g. neural networks, fuzzy logic, interfaces, processor
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1661—Programme controls characterised by programming, planning systems for manipulators characterised by task planning, object-oriented languages
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Abstract
The invention belongs to the technical field of medical service robots. A hospital guided robot with decision support and a method thereof are provided. The method comprises the steps of communicating a guided diagnosis robot with a patient, determining a target diagnosis room of the patient according to communication content, carrying out privacy analysis on the target diagnosis room to obtain a privacy analysis result, and providing medical service information for the patient by adopting an image interaction module if the privacy analysis result indicates that the target diagnosis room is a diagnosis room related to privacy, otherwise carrying out voice communication with the patient by adopting a voice interaction module to realize providing medical service information for the patient. The scheme of the invention can carry out privacy analysis on the target consulting room of the patient, and a proper medical service providing mode is selected according to the privacy analysis, so that the privacy of the patient can be fully ensured on the basis of timely providing accurate medical service for the patient.
Description
Technical Field
The invention relates to the technical field of medical service robots, in particular to a hospital diagnosis guiding robot with decision support and a method thereof.
Background
The hospital diagnosis guiding robot is a service robot specially designed for medical environment, and aims to improve the service quality of hospitals, reduce the workload of medical staff and provide convenience for patients.
The hospital diagnosis guiding robot has the key functions and characteristics that 1) information inquiry is carried out, namely, basic information such as positions of various doctor rooms, doctor information, registering processes and the like of a hospital is provided, 2) navigation guidance is carried out, namely, a patient is guided to reach a designated doctor room or an examination room through a built-in map or integrated with a hospital navigation system, 3) appointment registering is carried out, the patient is assisted in appointment registering, self-service is provided, queuing waiting time is reduced, 4) inquiry answers are carried out, namely, common problems about the doctor-seeking processes, hospital regulations and the like of the patient are answered, and 5) autonomous movement is carried out, namely, the robot has autonomous movement capability and freely shuttles inside the hospital to avoid obstacles.
The existing guiding robot can communicate with the patient through voice and image modes to provide relevant medical services, but the optimal communication mode is selected based on the characteristics of the patient, so that the guiding experience of the patient is poor and improvement is needed.
Disclosure of Invention
In view of the above, the present invention provides a hospital diagnosis guiding method based on a diagnosis guiding robot with decision support, a hospital diagnosis guiding robot with decision support, an electronic device, a computer storage medium and a computer program product, so as to solve at least one of the above technical problems.
The invention provides a hospital diagnosis guiding method based on a diagnosis guiding robot with decision support, which is applied to the diagnosis guiding robot, and comprises the following steps:
The diagnosis guiding robot communicates with a patient, and a target diagnosis room of the patient is determined according to communication content;
performing privacy analysis on the target consulting room to obtain a privacy analysis result;
If the privacy analysis result shows that the target consulting room is the consulting room related to privacy, the image interaction module is adopted to provide medical service information for the patient, otherwise, the voice interaction module is adopted to carry out voice communication with the patient so as to provide medical service information for the patient.
Optionally, the performing privacy analysis on the target consulting room to obtain a privacy analysis result includes:
inquiring a first basic privacy value corresponding to the target consulting room, wherein the first basic privacy value is obtained in advance based on big data analysis;
determining a disease name of the patient based on the communication content, and performing correlation analysis on the disease name and the target consulting room to obtain a first correlation coefficient;
and correcting the first basic privacy value by using the first correlation coefficient to obtain a target privacy value, namely obtaining a privacy analysis result.
Optionally, the determining manner of the first basic privacy value specifically includes:
Carrying out emotion analysis on the collected big data, judging emotion tendencies of users to different consulting rooms, and preparing a second basic privacy value of each consulting room according to the emotion tendencies;
acquiring diagnosis and treatment record data of the target consulting room of the hospital corresponding to the patient, and determining a plurality of good disease types of the target consulting room according to the diagnosis and treatment record data;
and extracting the maximum value of a third basic privacy value of each target good disease, determining a second correlation coefficient according to the maximum third basic privacy value, and correcting the second basic privacy value by using the second correlation coefficient to obtain the first basic privacy value.
Optionally, the method further comprises:
When the diagnosis guiding robot communicates with the patient, the diagnosis guiding robot outputs preset voice to the patient and acquires non-language features of the patient after a specified period of time based on a camera, wherein the non-language features refer to head and hand features which indicate that the patient may have hearing impairment;
Deeply analyzing the non-linguistic features by using artificial intelligence technology, and judging whether the hearing disorder exists in the patient or not;
If the patient is judged to have hearing impairment, an image interaction module is adopted to provide medical service information for the patient no matter whether the target consulting room is a consulting room related to privacy;
And if the patient is judged to have no hearing impairment, carrying out voice communication with the patient by adopting an image interaction module or a voice interaction module so as to provide medical service information for the patient.
Optionally, the determining manner of the specified period is specifically:
the diagnosis guiding robot obtains sound data of a diagnosis guiding area, analyzes the sound data to obtain noise volume in the diagnosis guiding area, and determines the length of the designated period according to the noise volume.
Optionally, when the voice interaction module is adopted to perform voice communication with the patient, the method further comprises:
and determining the voice interaction volume of the guided robot by taking the voice volume of the patient as a basis and taking the noise volume in the guided area into consideration.
The invention also provides a hospital diagnosis guiding robot with decision support, which comprises a voice interaction module, an image interaction module, a camera, a processing module and a storage module, wherein the processing module is electrically connected with the voice interaction module, the image interaction module, the camera and the storage module;
The voice interaction module is used for carrying out communication interaction with a patient and providing medical service information for the patient according to the instruction of the processing module;
The image interaction module is used for providing medical service information for patients according to the instruction of the processing module;
The camera is used for shooting image data of a patient according to the instruction of the processing module;
the processing module is configured to retrieve and execute the computer instructions stored in the storage module, so as to implement the method of any one of the foregoing claims.
The invention also provides a computer storage medium storing a computer program executable by a processor to implement a method as claimed in any one of the preceding claims.
The invention also provides a computer program product comprising a computer program executable by a processor to implement a method as claimed in any preceding claim.
The invention has the beneficial effects that:
The scheme of the invention can carry out privacy analysis on the target consulting room of the patient, and a proper medical service providing mode is selected according to the privacy analysis, so that the privacy of the patient can be fully ensured on the basis of timely providing accurate medical service for the patient.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a hospital diagnosis guiding method based on a diagnosis guiding robot with decision support according to an embodiment of the present invention;
Fig. 2 is a schematic structural diagram of a hospital diagnosis guiding robot with decision support according to an embodiment of the present invention.
Detailed Description
Other advantages and advantages of the present application will become apparent to those skilled in the art from the following detailed description, which, by way of illustration, is to be read in connection with certain specific embodiments, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In addition, the technical features of the different embodiments of the present application described below may be combined with each other as long as they do not collide with each other.
As shown in fig. 1, the embodiment of the invention discloses a hospital diagnosis guiding method based on a diagnosis guiding robot with decision support, which is applied to the diagnosis guiding robot, and comprises the following steps:
The diagnosis guiding robot communicates with a patient, and a target diagnosis room of the patient is determined according to communication content;
performing privacy analysis on the target consulting room to obtain a privacy analysis result;
If the privacy analysis result shows that the target consulting room is the consulting room related to privacy, the image interaction module is adopted to provide medical service information for the patient, otherwise, the voice interaction module is adopted to carry out voice communication with the patient so as to provide medical service information for the patient.
The existing medical diagnosis guiding robot has a module for communicating in a voice and image mode, but lacks in selecting an optimal communication mode based on the characteristics of a patient, so that the diagnosis guiding experience of the patient is poor. For example, when the patient guides the diagnosis robot to describe the disease characteristics of the patient or designates a specific disease, the diagnosis guiding robot analyzes that the corresponding target diagnosis room is a diagnosis room possibly related to privacy, such as a male department, a urinary department, a gynecology department, a oncology department, etc., if the diagnosis guiding robot communicates with the patient in a voice manner at this time, the patient becomes embarrassing in the diagnosis guiding hall, and the privacy of the patient is easily compromised.
Aiming at the technical problems, the guided diagnosis robot of the invention initially communicates with a patient, determines a target diagnosis room matched with the guided diagnosis robot based on analysis of communication content, then carries out privacy analysis on the target diagnosis room to obtain a privacy analysis result, and provides corresponding medical services for the patient in an image mode, such as outputting registration information, diagnosis room doctor information, diagnosis room guide information and the like if the privacy analysis result shows that the target diagnosis room is a diagnosis room related to privacy, otherwise carries out more efficient interaction with the patient in a voice mode. Therefore, the scheme of the invention can carry out privacy analysis on the target consulting room of the patient, and a proper medical service providing mode is selected according to the privacy analysis, so that the privacy of the patient can be fully ensured on the basis of timely providing accurate medical service for the patient.
Optionally, the performing privacy analysis on the target consulting room to obtain a privacy analysis result includes:
inquiring a first basic privacy value corresponding to the target consulting room, wherein the first basic privacy value is obtained in advance based on big data analysis;
determining a disease name of the patient based on the communication content, and performing correlation analysis on the disease name and the target consulting room to obtain a first correlation coefficient;
and correcting the first basic privacy value by using the first correlation coefficient to obtain a target privacy value, namely obtaining a privacy analysis result.
In this embodiment, different consulting rooms relate to different privacy, which can be determined in advance by big data analysis techniques. The big data mainly comprises massive questionnaire data, such as anonymized data in a collection hospital information system, including consulting room access records, patient satisfaction surveys and the like, and discussion and comments of users on various offices of a hospital on public platforms such as social media, forums and blogs.
Meanwhile, one consulting room can treat various diseases, such as gastroenterology, for example, not only conventional gastritis and helicobacter pylori infection, but also various liver diseases, gastric cancer, digestive tract cancers and the like, and the privacy corresponding to the prior type of diseases is obviously low, and the privacy corresponding to the later type of diseases is obviously particularly high. Therefore, the invention determines the name of the disease suffered by the patient based on the communication content of the guided diagnosis robot and the patient, carries out correlation analysis on the name of the disease and the target diagnosis room to obtain a first correlation coefficient, and then uses the first correlation coefficient to correct the obtained first basic privacy value to obtain the target privacy value.
Wherein, when the disease of the patient belongs to the above type of privacy disease among the diseases related to the target consulting room, although the name of the target consulting room does not directly reflect the disease name, the above privacy disease is not suggested by other people based on the name of the target consulting room, the patient may still be unwilling to conduct voice output by the guiding robot subjectively. The basic analysis principle of the correlation analysis is that all disease types corresponding to each consulting room are listed, each disease in which the privacy (namely a third basic privacy value described below) is higher than a specified threshold value is calculated, whether the disease name of the patient belongs to any disease with the privacy higher than the specified threshold value is further judged, if yes, the first correlation coefficient is set to be a large value, and if not, the first correlation coefficient is set to be a small value.
Optionally, the determining manner of the first basic privacy value specifically includes:
Carrying out emotion analysis on the collected big data, judging emotion tendencies of users to different consulting rooms, and preparing a second basic privacy value of each consulting room according to the emotion tendencies;
acquiring diagnosis and treatment record data of the target consulting room of the hospital corresponding to the patient, and determining a plurality of good disease types of the target consulting room according to the diagnosis and treatment record data;
and extracting the maximum value of a third basic privacy value of each target good disease, determining a second correlation coefficient according to the maximum third basic privacy value, and correcting the second basic privacy value by using the second correlation coefficient to obtain the first basic privacy value.
In this embodiment, emotion analysis is performed on the collected big data, so that emotion tendencies of the user for different consulting rooms, such as positive tendencies, negative tendencies or neutral tendencies, can be determined, and a second basic privacy value of each consulting room can be made. Since the big data are obtained by trans-regional means, it represents the general emotional tendency of the people to each consulting room, and the target consulting room corresponding to the aforesaid patient is the specific consulting room of a hospital in a certain region, and the diseases that the same consulting room in different regions is good at treating are different, which is generally known to the general people in that region. Therefore, the present invention further obtains diagnosis and treatment record data of the target consulting room to determine a plurality of disease types (for example, disease types with a large number of treatment cases and a large number of cure cases) of the target consulting room, extracts the maximum value of the third basic privacy values of the disease types, determines the second correlation coefficient based on the maximum value, and corrects the second basic privacy values representing the general emotion tendencies of the masses to the consulting rooms to the third basic privacy values representing the local actual conditions of the target consulting room by using the second correlation coefficient. Obviously, the second correlation coefficient is positively correlated with the largest of said third base privacy values.
The third basic privacy value of the target good disease is obtained by big data analysis in advance, and the specific analysis mode is identical to the mode of preparing the second basic privacy value of each diagnosis room. Since the emotional propensity of the masses in each region to a particular disease is substantially the same, the confidence of the third base privacy value is sufficiently high. Of course, the third base privacy value should also be updated according to a preset period, which may be two years, five years, etc.
Optionally, the method further comprises:
When the diagnosis guiding robot communicates with the patient, the diagnosis guiding robot outputs preset voice to the patient and acquires non-language features of the patient after a specified period of time based on a camera, wherein the non-language features refer to head and hand features which indicate that the patient may have hearing impairment;
Deeply analyzing the non-linguistic features by using artificial intelligence technology, and judging whether the hearing disorder exists in the patient or not;
If the patient is judged to have hearing impairment, an image interaction module is adopted to provide medical service information for the patient no matter whether the target consulting room is a consulting room related to privacy;
And if the patient is judged to have no hearing impairment, carrying out voice communication with the patient by adopting an image interaction module or a voice interaction module so as to provide medical service information for the patient.
In this embodiment, in addition to the above-mentioned method for deciding the providing of the medical service information based on the privacy of the target consulting room, the present invention further considers whether the patient has a hearing impairment. Specifically, when the lead robot communicates with the patient (the patient may manually input disease information on the touch screen of the lead robot, or swipe a diagnosis and treat card at the card swiping part to input the disease information thereof to the lead robot, the disease information may be a disease name or a disease symptom description information), the lead robot outputs a preset voice to the patient before executing the foregoing embodiment of the present invention, the preset voice may be "do you input the disease information exactly. When the patient is judged to have hearing impairment, the medical service information is obviously unsuitable to be provided through voice, so that the image interaction module is adopted to provide the medical service information for the patient no matter whether the target consulting room is a consulting room related to privacy or not at the moment, and when the patient is judged to not have hearing impairment, the most suitable medical service information providing mode is needed to be determined by comprehensively considering the privacy of the target consulting room according to the mode.
The non-language features are mainly hand features and head features, the hand features can be raised from the palm to the ears and are concave, and the head features comprise head tilting and neck shrinking behaviors and facial confusing features (micro Zhang Zuiba, frowning and the like).
Optionally, the determining manner of the specified period is specifically:
the diagnosis guiding robot obtains sound data of a diagnosis guiding area, analyzes the sound data to obtain noise volume in the diagnosis guiding area, and determines the length of the designated period according to the noise volume.
In this embodiment, the hospital care area (typically, a hospital hall) has more people entering and exiting and speaking, so that the noise level in the care area may be higher, and the presence of the higher noise may cause the patient without hearing impairment to have the above-mentioned non-speech feature due to inaudibility. In order to avoid misjudgment on whether a patient has hearing impairment caused by noise in a diagnosis guiding area, the invention is arranged to acquire the non-language features of the patient after a specified period of time and analyze whether the patient has hearing impairment, wherein the starting time of the specified period of time refers to the time when the diagnosis guiding robot starts to output the preset voice, and the non-language features of the patient are acquired after timing to a specified duration of time. The length of the appointed time period is positively correlated with the determined noise volume, namely, the larger the noise volume of the diagnosis guiding area is, the later the collection of the non-language features is started, namely, the patient is informed of the preset speech segment output by the diagnosis guiding robot in sufficient time when the noise is higher, the probability of misjudging as hearing impairment is reduced, otherwise, the earlier the collection of the non-language features is started, and the provision rate of the follow-up medical service information can be improved.
Optionally, when the voice interaction module is adopted to perform voice communication with the patient, the method further comprises:
and determining the voice interaction volume of the guided robot by taking the voice volume of the patient as a basis and taking the noise volume in the guided area into consideration.
In this embodiment, when the diagnosis guiding robot makes a decision to communicate with the patient in a voice interaction manner, it is also necessary to determine how much volume it should use. The invention adopts the mode that the voice volume of the patient is taken as the basis, the noise volume in the diagnosis guiding area is properly considered, for example, when the noise volume in the diagnosis guiding area is large, the voice volume of the patient is properly adjusted, and the adjusted voice volume is used as the voice interaction volume of the diagnosis guiding robot.
The voice volume of the patient may be the volume of the acquired patient corresponding to the voice when the diagnosis guiding robot outputs the preset voice to the patient (the patient is not a person with hearing impairment).
As shown in fig. 2, the invention also discloses a hospital diagnosis guiding robot with decision support, which comprises a voice interaction module, an image interaction module, a camera, a processing module and a storage module, wherein the processing module is electrically connected with the voice interaction module, the image interaction module, the camera and the storage module;
The voice interaction module is used for carrying out communication interaction with a patient and providing medical service information for the patient according to the instruction of the processing module;
The image interaction module is used for providing medical service information for patients according to the instruction of the processing module;
The camera is used for shooting image data of a patient according to the instruction of the processing module;
the processing module is configured to retrieve and execute the computer instructions stored in the storage module, so as to implement the method of any one of the foregoing claims.
The invention also discloses an electronic device comprising at least one processor, a memory and a computer program stored in the memory and executable on the at least one processor, which computer program, when executed by the processor, implements the method as claimed in any one of the preceding claims.
The invention also discloses a computer storage medium storing a computer program executable by a processor to implement a method according to any one of the preceding claims.
The invention also discloses a computer program product comprising a computer program executable by a processor to implement the method according to any of the preceding claims.
The computer readable storage medium may be Read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), compact disc Read-Only Memory (CD-ROM), magnetic tape, floppy disk, optical data storage device, etc.
It should be understood that references herein to "a plurality" are to two or more. "and/or" describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate that there are three cases of a alone, a and B together, and B alone. The character "/" generally indicates that the context-dependent object is an "or" relationship.
The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
The above embodiments are merely exemplary embodiments of the present application and are not intended to limit the present application, any modifications, equivalent substitutions, improvements, etc. that fall within the principles of the present application should be included in the scope of the present application.
Claims (8)
1. A hospital diagnosis guiding method based on a diagnosis guiding robot with decision support, which is applied to the diagnosis guiding robot, and is characterized by comprising the following steps:
The diagnosis guiding robot communicates with a patient, and a target diagnosis room of the patient is determined according to communication content;
performing privacy analysis on the target consulting room to obtain a privacy analysis result;
If the privacy analysis result shows that the target consulting room is a consulting room related to privacy, the image interaction module is adopted to provide medical service information for the patient, otherwise, the voice interaction module is adopted to carry out voice communication with the patient so as to provide medical service information for the patient;
Performing privacy analysis on the target consulting room to obtain a privacy analysis result, wherein the privacy analysis result comprises:
inquiring a first basic privacy value corresponding to the target consulting room, wherein the first basic privacy value is obtained in advance based on big data analysis;
determining a disease name of the patient based on the communication content, and performing correlation analysis on the disease name and the target consulting room to obtain a first correlation coefficient;
Correcting the first basic privacy value by using the first correlation coefficient to obtain a target privacy value, namely obtaining a privacy analysis result;
the determining mode of the first basic privacy value specifically comprises the following steps:
Carrying out emotion analysis on the collected big data, judging emotion tendencies of users to different consulting rooms, and preparing a second basic privacy value of each consulting room according to the emotion tendencies;
acquiring diagnosis and treatment record data of the target consulting room of the hospital corresponding to the patient, and determining a plurality of good disease types of the target consulting room according to the diagnosis and treatment record data;
And extracting the maximum value of the third basic privacy value of each disease-adequacy species, determining a second correlation coefficient according to the maximum third basic privacy value, and correcting the second basic privacy value by using the second correlation coefficient to obtain the first basic privacy value.
2. The hospital consultation method based on the consultation robot with decision support of claim 1, further comprising the following steps:
When the diagnosis guiding robot communicates with the patient, the diagnosis guiding robot outputs preset voice to the patient and acquires non-language features of the patient after a specified period of time based on a camera, wherein the non-language features refer to head and hand features which indicate that the patient may have hearing impairment;
Deeply analyzing the non-linguistic features by using artificial intelligence technology, and judging whether the hearing disorder exists in the patient or not;
If the patient is judged to have hearing impairment, an image interaction module is adopted to provide medical service information for the patient no matter whether the target consulting room is a consulting room related to privacy;
And if the patient is judged to have no hearing impairment, carrying out voice communication with the patient by adopting an image interaction module or a voice interaction module so as to provide medical service information for the patient.
3. The hospital diagnosis guiding method based on the diagnosis guiding robot with decision support according to claim 2, wherein the specific time period is determined by the following specific ways:
the diagnosis guiding robot obtains sound data of a diagnosis guiding area, analyzes the sound data to obtain noise volume in the diagnosis guiding area, and determines the length of the designated period according to the noise volume.
4. The method for guiding a doctor in a hospital based on a robot for guiding a doctor with decision support according to claim 3, wherein the method further comprises, when the voice interaction module is used for voice communication with the patient:
and determining the voice interaction volume of the guided robot by taking the voice volume of the patient as a basis and taking the noise volume in the guided area into consideration.
5. The hospital diagnosis guiding robot with the decision support comprises a voice interaction module, an image interaction module, a camera, a processing module and a storage module, wherein the processing module is electrically connected with the voice interaction module, the image interaction module, the camera and the storage module;
The voice interaction module is used for carrying out communication interaction with a patient and providing medical service information for the patient according to the instruction of the processing module;
The image interaction module is used for providing medical service information for patients according to the instruction of the processing module;
The camera is used for shooting image data of a patient according to the instruction of the processing module;
The processing module is configured to retrieve and execute the computer instructions stored in the storage module to implement the method according to any of claims 1-4.
6. An electronic device comprising at least one processor, a memory and a computer program stored in the memory and executable on the at least one processor, the computer program implementing the method according to any one of claims 1-4 when executed by the processor.
7. A computer storage medium, characterized in that it stores a computer program executable by a processor to implement the method according to any one of claims 1-4.
8. Computer program product, characterized in that it comprises a computer program executable by a processor for implementing the method according to any one of claims 1-4.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110489566A (en) * | 2019-08-22 | 2019-11-22 | 上海软中信息系统咨询有限公司 | A kind of hospital guide's method of intelligence hospital guide's service robot |
| CN110842947A (en) * | 2019-12-14 | 2020-02-28 | 梁静 | Hospital medical guide humanoid robot and control method thereof |
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|---|---|---|---|---|
| JP5188977B2 (en) * | 2005-09-30 | 2013-04-24 | アイロボット コーポレイション | Companion robot for personal interaction |
| CN205950753U (en) * | 2016-05-14 | 2017-02-15 | 深圳市华科安测信息技术有限公司 | Hospital guide service robot of hospital |
| CN113618748B (en) * | 2021-07-14 | 2022-08-30 | 温州理工学院 | Hospital diagnosis navigation intelligent robot and use method thereof |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110489566A (en) * | 2019-08-22 | 2019-11-22 | 上海软中信息系统咨询有限公司 | A kind of hospital guide's method of intelligence hospital guide's service robot |
| CN110842947A (en) * | 2019-12-14 | 2020-02-28 | 梁静 | Hospital medical guide humanoid robot and control method thereof |
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