CN111292842A - Intelligent diagnosis guide implementation method - Google Patents
Intelligent diagnosis guide implementation method Download PDFInfo
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- CN111292842A CN111292842A CN202010124223.4A CN202010124223A CN111292842A CN 111292842 A CN111292842 A CN 111292842A CN 202010124223 A CN202010124223 A CN 202010124223A CN 111292842 A CN111292842 A CN 111292842A
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- 238000000034 method Methods 0.000 title claims abstract description 42
- 238000003745 diagnosis Methods 0.000 title claims abstract description 18
- 230000008569 process Effects 0.000 claims abstract description 30
- 201000010099 disease Diseases 0.000 claims abstract description 3
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims abstract description 3
- 230000006399 behavior Effects 0.000 claims description 21
- 230000009471 action Effects 0.000 claims description 6
- 238000013527 convolutional neural network Methods 0.000 claims description 3
- 238000013144 data compression Methods 0.000 claims description 3
- 238000007906 compression Methods 0.000 claims description 2
- 230000006835 compression Effects 0.000 claims description 2
- 208000002193 Pain Diseases 0.000 description 2
- 206010019233 Headaches Diseases 0.000 description 1
- 206010033425 Pain in extremity Diseases 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000000740 bleeding effect Effects 0.000 description 1
- 210000000988 bone and bone Anatomy 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 231100000869 headache Toxicity 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/20—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/20—Movements or behaviour, e.g. gesture recognition
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20084—Artificial neural networks [ANN]
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- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Business, Economics & Management (AREA)
- General Business, Economics & Management (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Medical Informatics (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Multimedia (AREA)
- Human Computer Interaction (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Radiology & Medical Imaging (AREA)
- Quality & Reliability (AREA)
- Social Psychology (AREA)
- Psychiatry (AREA)
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- Epidemiology (AREA)
- Primary Health Care (AREA)
- Public Health (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
Abstract
The invention discloses an intelligent diagnosis guide realization method, which comprises a scanning process, an image processing process, a recommendation process and a registration process; the scanning process comprises an image recognition process and a behavior recognition process, the image recognition process is used for enabling a user to take pictures through a mobile phone camera to analyze the injured part, and the behavior recognition process comprises uploading of a disease behavior to judge what department the user needs to look at. Through the mode, the invention can greatly improve the diagnosis guiding accuracy by registering through image recognition and behavior recognition.
Description
Technical Field
The invention relates to the technical field of diagnosis guidance, in particular to an intelligent diagnosis guidance method for shooting an injured part through video recording action.
Background
In the mobile application for realizing intelligent diagnosis guiding, under the condition that the intelligent diagnosis guiding function does not use the method, the intelligent diagnosis guiding service is realized by two modes, one mode is that a user clicks a corresponding part to check a hangable department by displaying human body graphs (the mode has high error rate and is difficult to select), and the other mode is that the injured part of the user is explained by a voice and character assistant mode to know the hangable department recommended by the voice assistant, so that the problem that the language or character description is not smooth and the error is caused exists.
Disclosure of Invention
The invention mainly solves the technical problem of providing an intelligent diagnosis guiding realization method which can improve the diagnosis guiding accuracy rate based on behavior detection, image recognition and artificial intelligence.
In order to solve the technical problems, the invention adopts a technical scheme that: the method for realizing intelligent diagnosis guiding comprises the following steps: scanning flow, image processing flow, recommendation flow and registration flow; the scanning process comprises an image recognition process and a behavior recognition process, the image recognition process is that a user takes a picture through a mobile phone camera to analyze an injured part, and the behavior recognition process comprises uploading a disease behavior to judge what department the user needs to check; the image recognition process and the behavior recognition process both need a convolutional neural network to perform image processing, a user acquires an image or a video through image scanning and then performs data compression, the image or the video is uploaded to a server side after the compression, the server side obtains a result after the image and the behavior are analyzed and processed, a corresponding department or recommended content is inquired in a data index library through a score and returned to a client side, the image is visually displayed on the scanned image, and the user can perform corresponding appointment registration operation by clicking the displayed department.
Further, the server side analyzes and processes the image, and medical human body comparison is carried out on the image to obtain a score.
Further, the server side analyzes and processes the behaviors, scores the actions through an algorithm, directly indexes the actions to corresponding departments when the score is over 75.
The invention has the beneficial effects that: the invention can greatly improve the diagnosis guiding accuracy by registering through image recognition and behavior recognition.
Drawings
FIG. 1 is a flowchart illustrating an implementation method of intelligent medical guidance according to a preferred embodiment of the present invention.
Detailed Description
The following detailed description of the preferred embodiments of the present invention, taken in conjunction with the accompanying drawings, will make the advantages and features of the invention easier to understand by those skilled in the art, and thus will clearly and clearly define the scope of the invention.
Referring to fig. 1, an embodiment of the present invention includes:
an intelligent diagnosis guide implementation method comprises the following steps: scanning is performed through an intelligent diagnosis guide service, and two modes are combined and divided into an image identification process and a behavior identification process (also called video acquisition and identification);
and (3) image identification flow: a user takes a picture through a mobile phone camera to analyze an injured part, characteristic information such as knocking, bleeding and the like is inquired to a department for presentation in a recognition mode, and if the problem is that the bone headache, the cervical vertebra pain and the like of a patient need behavior recognition;
and (3) behavior identification flow: the behavior recognition can support various modes, and a user touches a pain part or for example, leg pain, walks, and has difference in action to judge what department the user needs to check;
the image recognition and the behavior recognition both need a convolutional neural network to perform image processing, a user acquires an image or a video through image scanning, then performs data compression, uploads the compressed image or video to a server side, performs image (medical human body contrast to obtain a score), performs behavior analysis processing (scores actions through an algorithm, the score is over 75, and corresponding departments are directly indexed), obtains a result, queries the corresponding departments or recommended contents in a data index library through the score, returns the contents to a client, is visually displayed on a scanned image, and can perform corresponding appointment registration operation by clicking the displayed departments.
The invention can greatly improve the accuracy rate by registering through image recognition and behavior recognition and can also provide suggestions for doctor to see a doctor.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes performed by the present specification and drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (3)
1. An intelligent diagnosis guide implementation method is characterized by comprising the following steps: scanning flow, image processing flow, recommendation flow and registration flow; the scanning process comprises an image recognition process and a behavior recognition process, the image recognition process is that a user takes a picture through a mobile phone camera to analyze an injured part, and the behavior recognition process comprises uploading a disease behavior to judge what department the user needs to check; the image recognition process and the behavior recognition process both need a convolutional neural network to perform image processing, a user acquires an image or a video through image scanning and then performs data compression, the image or the video is uploaded to a server side after the compression, the server side obtains a result after the image and the behavior are analyzed and processed, a corresponding department or recommended content is inquired in a data index library through a score and returned to a client side, the image is visually displayed on the scanned image, and the user can perform corresponding appointment registration operation by clicking the displayed department.
2. The method for implementing intelligent diagnosis guiding according to claim 1, wherein: and the server side analyzes and processes the image and obtains a score by performing medical human body comparison on the image.
3. The method for implementing intelligent diagnosis guiding according to claim 1, wherein: and the server side analyzes and processes the behaviors, scores the actions through an algorithm, directly indexes corresponding departments when the score is over 75.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010124223.4A CN111292842A (en) | 2020-02-27 | 2020-02-27 | Intelligent diagnosis guide implementation method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010124223.4A CN111292842A (en) | 2020-02-27 | 2020-02-27 | Intelligent diagnosis guide implementation method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111292842A true CN111292842A (en) | 2020-06-16 |
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Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010124223.4A Withdrawn CN111292842A (en) | 2020-02-27 | 2020-02-27 | Intelligent diagnosis guide implementation method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111292842A (en) |
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2020
- 2020-02-27 CN CN202010124223.4A patent/CN111292842A/en not_active Withdrawn
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Application publication date: 20200616 |