CN110675956A - Method and device for determining facial paralysis treatment scheme, readable medium and electronic equipment - Google Patents
Method and device for determining facial paralysis treatment scheme, readable medium and electronic equipment Download PDFInfo
- Publication number
- CN110675956A CN110675956A CN201910787303.5A CN201910787303A CN110675956A CN 110675956 A CN110675956 A CN 110675956A CN 201910787303 A CN201910787303 A CN 201910787303A CN 110675956 A CN110675956 A CN 110675956A
- Authority
- CN
- China
- Prior art keywords
- treatment
- scheme
- information
- determining
- sample
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000011282 treatment Methods 0.000 title claims abstract description 152
- 238000000034 method Methods 0.000 title claims abstract description 55
- 208000004929 Facial Paralysis Diseases 0.000 title claims abstract description 33
- 208000036826 VIIth nerve paralysis Diseases 0.000 title claims abstract description 33
- 238000004458 analytical method Methods 0.000 claims abstract description 61
- 201000010099 disease Diseases 0.000 claims abstract description 30
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims abstract description 30
- 238000012549 training Methods 0.000 claims abstract description 30
- 238000011269 treatment regimen Methods 0.000 claims abstract description 16
- 230000001815 facial effect Effects 0.000 claims description 16
- 238000004364 calculation method Methods 0.000 claims description 8
- 230000000007 visual effect Effects 0.000 claims 1
- 230000000694 effects Effects 0.000 abstract description 15
- 238000004422 calculation algorithm Methods 0.000 abstract description 7
- 238000010801 machine learning Methods 0.000 abstract description 7
- 238000011369 optimal treatment Methods 0.000 abstract description 5
- 239000003814 drug Substances 0.000 description 13
- 238000001467 acupuncture Methods 0.000 description 10
- 230000008569 process Effects 0.000 description 7
- 238000011156 evaluation Methods 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 238000013459 approach Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000004590 computer program Methods 0.000 description 2
- 210000000744 eyelid Anatomy 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- 208000006373 Bell palsy Diseases 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 238000009792 diffusion process Methods 0.000 description 1
- 238000002598 diffusion tensor imaging Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000002599 functional magnetic resonance imaging Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000002595 magnetic resonance imaging Methods 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 210000001747 pupil Anatomy 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 210000000697 sensory organ Anatomy 0.000 description 1
- 230000001225 therapeutic effect Effects 0.000 description 1
Images
Classifications
-
- 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
- G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
-
- 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
- G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Public Health (AREA)
- Data Mining & Analysis (AREA)
- Biomedical Technology (AREA)
- Databases & Information Systems (AREA)
- Pathology (AREA)
- Epidemiology (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
Abstract
The invention discloses a method and a device for determining a facial paralysis treatment scheme, a readable medium and electronic equipment, wherein the method comprises the following steps: carrying out data training on the sample data to establish a scheme analysis model; determining condition information for a target patient and determining a plurality of treatment options; analyzing and calculating by using the scheme analysis model through the disease information of the target patient and each treatment scheme to determine a predicted treatment result corresponding to each treatment scheme; determining a target treatment regimen from the plurality of treatment regimens based on the predicted treatment outcome; establishing a scheme analysis model through a machine learning algorithm, analyzing predicted treatment results of a plurality of treatment schemes according to specific disease information of a target patient, and selecting one treatment scheme with the most ideal treatment effect according to the predicted treatment results; the best treatment scheme is selected correspondingly under different clinical conditions, so that the optimal treatment effect is achieved.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a method and a device for determining a facial paralysis treatment scheme, a readable medium and electronic equipment.
Background
Facial paralysis is a common disease, and is called idiopathic facial paralysis in modern medicine. The traditional Chinese medicine acupuncture and moxibustion for treating facial paralysis has already existed clinical experience for many years, has relatively ideal treatment effect all the time, and is an important means for treating facial paralysis at present in China.
However, the problem of the traditional Chinese medicine for treating facial paralysis is that the treatment effect is often evaluated through subjective feeling, and an objective and effective evaluation method is lacked. In addition, there are various treatment schemes for treating facial paralysis by traditional Chinese medicine acupuncture. However, due to the lack of evaluation methods, it is difficult to determine how to select the best treatment regimen to achieve the most desirable treatment effect under different clinical conditions.
The western medicine field can evaluate the facial paralysis state of a patient by means of a grading scale or surface electromyogram and the like. However, these methods generally only evaluate the severity of facial paralysis of patients, but cannot be combined with the treatment of traditional Chinese medicine to evaluate the treatment effect of the treatment scheme of traditional Chinese medicine.
Disclosure of Invention
The invention provides a method and a device for determining a treatment scheme for facial paralysis, a readable medium and electronic equipment.
In a first aspect, the present invention provides a method for determining a facial paralysis treatment plan, including:
carrying out data training on the sample data to establish a scheme analysis model;
determining condition information for a target patient and determining a plurality of treatment options;
analyzing and calculating by using the scheme analysis model through the disease information of the target patient and each treatment scheme to determine a predicted treatment result corresponding to each treatment scheme;
determining a target treatment regimen from the plurality of treatment regimens based on the predicted treatment outcome.
Preferably, the sample data comprises:
sample condition information, sample treatment protocol, and corresponding treatment conclusion information.
Preferably, the data training of the sample data to establish the scheme analysis model includes:
combining the sample condition information and sample treatment protocol into sample clinical information;
and performing supervised learning training by taking the sample clinical information and the treatment conclusion information as training samples to obtain a functional relation between the sample clinical information and the treatment conclusion information, and establishing the scheme analysis model through the functional relation.
Preferably, the method further comprises the following steps:
substituting the sample clinical information and the treatment conclusion information into the protocol analysis model to obtain a fitting index of the protocol analysis model;
and when the fitting index is lower than a preset fitting standard, correcting the functional relation through the supervised learning training.
Preferably, the sample condition information includes at least one of photographic image condition information, surface electromyogram condition information, and facial structure feature information.
Preferably, the facial feature information includes:
the facial feature information will be located based on the distance between the particular facial reference points determined by the facial image.
Preferably, said determining a target treatment plan from said plurality of treatment plans based on said predicted treatment outcome comprises:
determining a cure index for each of said predicted treatment outcomes;
and determining the treatment scheme corresponding to the predicted treatment result with the highest cure index as the target treatment scheme.
In a second aspect, the present invention provides a facial paralysis treatment plan determination apparatus, including:
the modeling module is used for carrying out data training on the sample data so as to establish a scheme analysis model;
an information determination module for determining condition information of a target patient and determining a plurality of treatment protocols;
the calculation analysis module is used for performing analysis calculation through the disease information of the target patient and each treatment scheme by using the scheme analysis model to determine a predicted treatment result corresponding to each treatment scheme;
a regimen determination module for determining a target treatment regimen from the plurality of treatment regimens based on the predicted treatment outcome.
In a third aspect, the invention provides a readable medium comprising executable instructions, which when executed by a processor of an electronic device, perform the method according to any of the first aspect.
In a fourth aspect, the present invention provides an electronic device, comprising a processor and a memory storing execution instructions, wherein when the processor executes the execution instructions stored in the memory, the processor performs the method according to any one of the first aspect.
The invention provides a method and a device for determining a treatment scheme of facial paralysis, a readable medium and electronic equipment, wherein a scheme analysis model is established through a machine learning algorithm, and the predicted treatment results of a plurality of treatment schemes are analyzed according to specific disease information of a target patient, so that the objective analysis of the traditional Chinese medicine acupuncture treatment scheme is realized; selecting a treatment plan with optimal treatment effect according to the predicted treatment result; the best treatment scheme is correspondingly selected under different clinical conditions, so that the optimal treatment effect is achieved; the disease information of the target patient is obtained through a relatively low-cost and high-popularity medical approach, so that the method is relatively easy to implement and is convenient for diagnosing and treating the patient.
Further effects of the above-mentioned unconventional preferred modes will be described below in conjunction with specific embodiments.
Drawings
In order to more clearly illustrate the embodiments or the prior art solutions of the present invention, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.
Fig. 1 is a schematic flow chart illustrating a method for determining a facial paralysis treatment plan according to an embodiment of the present invention;
fig. 2 is a schematic flow chart illustrating a scheme analysis model established in another method for determining a facial paralysis treatment scheme according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a device for determining a facial paralysis treatment plan according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail and completely with reference to the following embodiments and accompanying drawings. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The above-mentioned known problem of treating facial paralysis by acupuncture and moxibustion in traditional Chinese medicine is that the treatment effect is often evaluated by subjective feeling, and an objective and effective evaluation method is lacked. In addition, there are various treatment schemes for treating facial paralysis by traditional Chinese medicine acupuncture. However, due to the lack of evaluation methods, it is difficult to determine how to select the best treatment regimen to achieve the most desirable treatment effect under different clinical conditions. Therefore, the invention establishes a scheme analysis model through a machine learning algorithm, analyzes the predicted treatment results of a plurality of treatment schemes according to the specific disease information of the target patient, and selects one treatment scheme with the most ideal treatment effect according to the predicted treatment results.
Referring to fig. 1, a specific embodiment of the method for determining a facial paralysis treatment plan according to the present invention is shown. The method in this embodiment includes the following steps:
And 103, analyzing and calculating according to the disease condition information of the target patient and each treatment scheme by using the scheme analysis model, and determining a predicted treatment result corresponding to each treatment scheme.
And 104, determining a target treatment scheme from the plurality of treatment schemes according to the predicted treatment result.
In this embodiment, a scheme analysis model is first established using sample data. The sample data, namely the historical clinical data of treating facial paralysis by using traditional Chinese medicine acupuncture, can specifically comprise the clinical data of a large number of historical patients. Sample data for a historic patient may include sample condition information, sample treatment protocol and corresponding treatment conclusion information for the historic patient.
The sample disease information generally refers to facial image information of the historical patient before treatment, and can reflect specific illness states of facial paralysis of the historical patient. The facial image information at least comprises one of image disease information, surface electromyogram disease information and facial structure characteristic information. The image information may be long echo time of Magnetic Resonance Imaging (MRI), active region pixel value of Functional MRI, anisotropic fraction (FA value) of Diffusion Tensor Imaging (DTI), Apparent Diffusion Coefficient (ADC value), and the like. The surface electromyogram disease information can be the root mean square ratio of the affected side, and can also be other corresponding characteristics screened according to different research purposes. The facial feature information may be facial feature information determined based on a distance between specific facial reference points determined from the facial image. For example, historical patient left and right internal canthus to mouth corner distances. Or the distance between reference positions of the middle pupil line, the upper eyelid edge, the lower eyelid edge, the base of the nose wing, the position of the middle upper lip, the position of the oral commissure, the position of the middle lip and the like of the historical patient. The facial feature information can show whether the distribution of five sense organs of a historical patient is symmetrical or not and whether the position relationship is symmetrical or not is reasonable.
The sample treatment plan represents the historical treatment plan of traditional Chinese medicine acupuncture and moxibustion received by the patient in the historical clinical data. Such as acupuncture points, acupuncture techniques, and the length of time for holding needles.
The treatment conclusion information represents the cure condition of the patient after the treatment. If the patient is cured, the curing time, the curing and recovering degree and the like.
Therefore, one sample data of a historical patient can completely reflect the information of the historical patient in various aspects such as the illness state, the treatment mode and the cure condition. And a large amount of similar sample data are used for data training based on a machine learning algorithm, so that the potential logic relationship among the sample disease information, the sample treatment scheme and the corresponding treatment conclusion information can be obtained, and a scheme analysis model is further established. By means of the scheme analysis model, it can be analyzed what treatment effect will be achieved by adopting a specific treatment scheme for a specific patient.
Therefore, when determining a facial paralysis treatment plan for a specific target patient using the plan analysis model, it is necessary to first determine the disease information of the target patient. The disease information embodies the specific condition of the facial paralysis of the target patient. The specific content of the disease information of the target patient may be similar to the sample condition information in the sample data. It should be noted that, when the disease information also includes the above-mentioned image disease information, surface electromyogram disease information and/or facial structure feature information, it can be seen that the above-mentioned information can be obtained through a relatively low-cost and highly popular medical approach, so the method of this embodiment is relatively easy to implement, and is convenient for diagnosing and treating patients. At the same time, multiple treatment regimens for the target patient need to be determined for subsequent analysis and screening.
And substituting the disease information of the target patient and a treatment scheme into the scheme analysis model, namely performing analysis calculation by using the scheme analysis model, and determining a corresponding predicted treatment result after the target patient is treated by using the treatment scheme. And in the same way, the disease information of the target patient and each treatment scheme are substituted into the scheme analysis model, so that the predicted treatment result corresponding to each treatment scheme can be obtained.
In this embodiment, each of the predicted treatment outcomes is further analyzed to determine a cure index for each of the predicted treatment outcomes. In general, a higher cure index means a higher cure for the predicted therapeutic outcome, and thus means a better outcome of the corresponding treatment regimen for the subject patient. Therefore, the treatment plan corresponding to the predicted treatment result with the highest cure index is determined as the target treatment plan.
According to the technical scheme, the beneficial effects of the embodiment are as follows: a scheme analysis model is established through a machine learning algorithm, and the predicted treatment results of a plurality of treatment schemes are analyzed according to the specific disease information of a target patient, so that the objective analysis of the traditional Chinese medicine acupuncture treatment scheme is realized; selecting a treatment plan with optimal treatment effect according to the predicted treatment result; the best treatment scheme is correspondingly selected under different clinical conditions, so that the optimal treatment effect is achieved; the disease information of the target patient is obtained through a relatively low-cost and high-popularity medical approach, so that the method is relatively easy to implement and is convenient for diagnosing and treating the patient.
Fig. 1 shows only a basic embodiment of the method of the present invention, and based on this, certain optimization and expansion can be performed, and other preferred embodiments of the method can also be obtained.
Fig. 2 shows another embodiment of the method for determining a facial paralysis treatment plan according to the present invention. On the basis of the previous embodiment, the embodiment performs more detailed description and a certain degree of optimization on the training modeling process. In this embodiment, the creating of the scheme analysis model includes the following steps:
And step 203, establishing the scheme analysis model through the functional relation.
And step 204, substituting the sample clinical information and the treatment conclusion information into the scheme analysis model to obtain a fitting index of the scheme analysis model.
And step 205, when the fitting index is lower than a preset fitting standard, correcting the functional relation through the supervised learning training.
The supervised learning training, i.e. through a machine learning algorithm, finds the association between data features and targets. Therefore, in this embodiment, the sample disease condition information and the sample treatment plan are combined into sample clinical information, and the sample clinical information is used as a feature in the supervised learning training. And using the treatment conclusion information as a target in the supervised learning training.
Before data training, the sample data can be preprocessed according to requirements, so that the format of the sample data meets the requirements of the data training. The preprocessing specifically comprises data feature extraction, data feature dimension reduction, data feature null value processing, data feature conversion, data feature normalization, data target value null value processing, data target value conversion and the like.
Assume a sample data representation as (x)1-nY). Wherein x represents clinical information of the sample, i.e. characteristics of the data, and may be used in particularx1-n＝(x1,x2…xn) To express x1～xnAnd n is the numerical value of the specific parameter. y represents the treatment conclusion information, i.e., the goal of the data.
After the supervised learning training, the functional relationship y ═ f (x) between the sample clinical information and the treatment conclusion information can be obtained1-n). I.e. to obtain the protocol analysis model. Subsequently, only the disease information and the treatment scheme of the target patient are taken as x1-nAnd substituting the calculated output y into the model to obtain the predicted treatment result.
The specific process of supervised learning training, and the corresponding functional relationship y ═ f (x)1-n) The expression of (c) is not limited in this embodiment. All realizable machine learning algorithms in the prior art can be combined under the overall solution of the present embodiment. And the mathematical operation process of modeling can be properly adjusted according to specific application scenes and requirements.
In order to ensure the accuracy of the scheme analysis model, in this embodiment, after the above functional relationship is obtained through a certain degree of training, it is also necessary to perform verification and correction. The checking mode is that the sample clinical information is substituted into the scheme analysis model for calculation, and whether the target (namely y value) of the calculated data is consistent with the pre-known treatment conclusion information or not is judged.
In the present embodiment, the functional relationship y is obtained as f (x)1-n) Meanwhile, a loss function defined as L (f (x) can be obtained1-n) Y). And substituting a large amount of sample clinical information into the scheme analysis model for verification, and calculating the fitting index of the scheme analysis model according to the loss function. In principle, a higher fit index indicates a more accurate analysis model for the recipe. However, if the fitting index is lower than the preset fitting standard, the current accuracy of the scheme analysis model is not satisfactory. Therefore, supervised learning training is required to be carried out on the functional relation, and the functional relation is corrected until the requirements of the fitting standard are met.
It should also be noted that in some special cases, there may be cases where the protocol analysis model is significantly contrary to clinical experience. In this case, the recipe analysis model may also be manually revised to ensure accuracy.
According to the technical solutions above, on the basis of the embodiment shown in fig. 1, the present embodiment further has the following beneficial effects: the process of establishing a scheme analysis model by using a supervised learning training method is disclosed in detail, and the steps of checking and correcting the scheme analysis model are further included. Therefore, the precision of the scheme analysis model is guaranteed, and the accuracy of the treatment scheme analysis is improved.
Fig. 3 shows an embodiment of the facial paralysis treatment plan determining apparatus according to the present invention. The apparatus of this embodiment is a physical apparatus for performing the method described in fig. 1-2. The technical solution is essentially the same as that in the above embodiment, and the corresponding description in the above embodiment is also applicable to this embodiment. The device in this embodiment includes:
the modeling module 301 is configured to perform data training on the sample data to establish a scheme analysis model.
An information determination module 302 for determining condition information of a target patient and determining a plurality of treatment options.
A calculation and analysis module 303, configured to perform analysis and calculation according to the disease condition information of the target patient and each of the treatment plans by using the plan analysis model, and determine a predicted treatment result corresponding to each of the treatment plans.
A regimen determination module 304 for determining a target treatment regimen from the plurality of treatment regimens based on the predicted treatment outcome.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. On the hardware level, the electronic device comprises a processor and optionally an internal bus, a network interface and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory, such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.
The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry standard architecture) bus, a PCI (Peripheral component interconnect) bus, an EISA (extended Industry standard architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 4, but that does not indicate only one bus or one type of bus.
And the memory is used for storing the execution instruction. In particular, a computer program that can be executed by executing instructions. The memory may include both memory and non-volatile storage and provides execution instructions and data to the processor.
In a possible implementation manner, the processor reads the corresponding execution instruction from the nonvolatile memory to the memory and then runs the corresponding execution instruction, and the corresponding execution instruction can also be obtained from other equipment so as to form the determining device of the facial paralysis treatment plan on a logic level. The processor executes the execution instructions stored in the memory, so that the method for determining the facial paralysis treatment plan provided by any embodiment of the invention is realized through the executed execution instructions.
The method performed by the apparatus for determining a facial paralysis treatment plan according to the embodiment of the present invention shown in fig. 3 can be implemented in or by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
An embodiment of the present invention further provides a readable storage medium, where the readable storage medium stores an execution instruction, and when the stored execution instruction is executed by a processor of an electronic device, the electronic device can be caused to execute the method for determining a facial paralysis treatment plan provided in any embodiment of the present invention, and is specifically configured to execute the method shown in fig. 1 or fig. 2.
The electronic device described in the foregoing embodiments may be a computer.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects.
The embodiments of the present invention are described in a progressive manner, and the same and similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the apparatus embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above description is only an example of the present invention, and is not intended to limit the present invention. Various modifications and alterations to this invention will become apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.
Claims (10)
1. A method for determining a treatment plan for facial paralysis, comprising:
carrying out data training on the sample data to establish a scheme analysis model;
determining condition information for a target patient and determining a plurality of treatment options;
analyzing and calculating by using the scheme analysis model through the disease information of the target patient and each treatment scheme to determine a predicted treatment result corresponding to each treatment scheme;
determining a target treatment regimen from the plurality of treatment regimens based on the predicted treatment outcome.
2. The method of claim 1, wherein the sample data comprises:
sample condition information, sample treatment protocol, and corresponding treatment conclusion information.
3. The method of claim 2, wherein the data training of the sample data to create the solution analysis model comprises:
combining the sample condition information and sample treatment protocol into sample clinical information;
performing supervised learning training by taking the sample clinical information and the treatment conclusion information as training samples to obtain a functional relation between the sample clinical information and the treatment conclusion information;
and establishing the scheme analysis model through the functional relation.
4. The method of claim 3, further comprising:
substituting the sample clinical information and the treatment conclusion information into the protocol analysis model to obtain a fitting index of the protocol analysis model;
and when the fitting index is lower than a preset fitting standard, correcting the functional relation through the supervised learning training.
5. The method of claim 2, wherein the sample condition information includes at least one of a visual image condition information, a surface electromyogram condition information, and a facial structure feature information.
6. The method of claim 5, wherein the facial feature information comprises:
the distance between specific face reference points determined based on the face image is taken as the face feature information.
7. The method of any one of claims 1 to 6, wherein said determining a target treatment plan from said plurality of treatment plans based on said predicted treatment outcome comprises:
determining a cure index for each of said predicted treatment outcomes;
and determining the treatment scheme corresponding to the predicted treatment result with the highest cure index as the target treatment scheme.
8. A facial paralysis treatment protocol determining apparatus, comprising:
the modeling module is used for carrying out data training on the sample data so as to establish a scheme analysis model;
an information determination module for determining condition information of a target patient and determining a plurality of treatment protocols;
the calculation analysis module is used for performing analysis calculation through the disease information of the target patient and each treatment scheme by using the scheme analysis model to determine a predicted treatment result corresponding to each treatment scheme;
a regimen determination module for determining a target treatment regimen from the plurality of treatment regimens based on the predicted treatment outcome.
9. A readable medium comprising executable instructions which, when executed by a processor of an electronic device, cause the electronic device to perform the method of any of claims 1 to 7.
10. An electronic device comprising a processor and a memory storing execution instructions, the processor performing the method of any of claims 1-7 when the processor executes the execution instructions stored by the memory.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910787303.5A CN110675956A (en) | 2019-08-26 | 2019-08-26 | Method and device for determining facial paralysis treatment scheme, readable medium and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910787303.5A CN110675956A (en) | 2019-08-26 | 2019-08-26 | Method and device for determining facial paralysis treatment scheme, readable medium and electronic equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110675956A true CN110675956A (en) | 2020-01-10 |
Family
ID=69076431
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910787303.5A Pending CN110675956A (en) | 2019-08-26 | 2019-08-26 | Method and device for determining facial paralysis treatment scheme, readable medium and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110675956A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112509669A (en) * | 2021-02-01 | 2021-03-16 | 肾泰网健康科技(南京)有限公司 | AI technology-based renal disease hemodialysis scheme customization method and system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107346369A (en) * | 2017-05-11 | 2017-11-14 | 北京紫宸正阳科技有限公司 | A kind of medical information processing method and device |
| CN107436993A (en) * | 2017-05-05 | 2017-12-05 | 陈昕 | Establish the method and server of ICU conditions of patients assessment models |
| CN108034708A (en) * | 2017-12-14 | 2018-05-15 | 中国中医科学院中药研究所 | The system that the individual validity of Tripterygium wilfordii Polyglycosidium Tablets treatment rheumatoid arthritis is determined by the expression quantity of multiple mRNA |
| CN109448858A (en) * | 2018-10-30 | 2019-03-08 | 中山大学肿瘤防治中心 | Colorectal cancer medical data processing method and processing device, storage medium, electronic equipment |
| CN109642258A (en) * | 2018-10-17 | 2019-04-16 | 上海允英医疗科技有限公司 | A kind of method and system of tumor prognosis prediction |
-
2019
- 2019-08-26 CN CN201910787303.5A patent/CN110675956A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107436993A (en) * | 2017-05-05 | 2017-12-05 | 陈昕 | Establish the method and server of ICU conditions of patients assessment models |
| CN107346369A (en) * | 2017-05-11 | 2017-11-14 | 北京紫宸正阳科技有限公司 | A kind of medical information processing method and device |
| CN108034708A (en) * | 2017-12-14 | 2018-05-15 | 中国中医科学院中药研究所 | The system that the individual validity of Tripterygium wilfordii Polyglycosidium Tablets treatment rheumatoid arthritis is determined by the expression quantity of multiple mRNA |
| CN109642258A (en) * | 2018-10-17 | 2019-04-16 | 上海允英医疗科技有限公司 | A kind of method and system of tumor prognosis prediction |
| CN109448858A (en) * | 2018-10-30 | 2019-03-08 | 中山大学肿瘤防治中心 | Colorectal cancer medical data processing method and processing device, storage medium, electronic equipment |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112509669A (en) * | 2021-02-01 | 2021-03-16 | 肾泰网健康科技(南京)有限公司 | AI technology-based renal disease hemodialysis scheme customization method and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108665462B (en) | Highly integrated annotation and segmentation system for medical imaging | |
| EP4091575A1 (en) | Method and apparatus for generating orthodontic teeth arrangement shape | |
| CN110363760B (en) | Computer system for recognizing medical images | |
| WO2019208703A1 (en) | Information processing device, control method, and program | |
| TW202145249A (en) | Image detection method and training method of related model, electronic device and computer-readable storage medium | |
| RU2011116406A (en) | SYSTEM AND METHOD FOR COMBINING CLINICAL SIGNS AND SIGNS OF IMAGES FOR DIAGNOSTIC USING A COMPUTER | |
| CN112288731A (en) | Blood vessel stenosis analysis method and device | |
| KR102233404B1 (en) | Method and apparatus for estimating bone age | |
| CN109215041B (en) | Full-automatic pelvic tumor segmentation method and system, storage medium and terminal | |
| CN111883222B (en) | Text data error detection method and device, terminal equipment and storage medium | |
| CN110648764A (en) | Method and device for obtaining clinical data prediction model, readable medium and electronic equipment | |
| CN110400613B (en) | Follow-up patient screening method and device, readable medium and electronic equipment | |
| CN112133440A (en) | Dose calculation system, dose quality assurance system and storage medium | |
| CN110675956A (en) | Method and device for determining facial paralysis treatment scheme, readable medium and electronic equipment | |
| CN113284145B (en) | Image processing method and device, computer readable storage medium and electronic device | |
| CN112101438B (en) | Left-right eye classification method, device, server and storage medium | |
| CN109214451A (en) | A kind of classification method and equipment of brain exception | |
| US9311276B2 (en) | Methods and apparatus for analyzing test data in determining the effect of drug treatments | |
| CN107392976A (en) | Data processing method, device and equipment | |
| CN111180078A (en) | Method and device for evaluating treatment effect, readable medium and electronic equipment | |
| US20200000413A1 (en) | Method and system for automated diagnostics of none-infectious illnesses | |
| US20230005152A1 (en) | Apparatus and method for image segmentation | |
| CN110706803B (en) | Method and device for determining myocardial fibrosis, readable medium and electronic equipment | |
| CN116797521A (en) | Method and device for predicting severe pneumonia, electronic equipment and medium | |
| CN111192244B (en) | Method and system for determining tongue characteristics based on key points |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200110 |
|
| RJ01 | Rejection of invention patent application after publication |