Intestinal tract cleaning guiding method and system

Abstract

The invention provides an intestinal tract cleaning guiding method and system, and the method comprises the steps: obtaining the intestinal tract cleaning preparation information and intestinal tract cleaning record information of a patient, and recognizing the excretion frequency and excrement images of the patient based on the intestinal tract cleaning record information; identifying the preparation adaptation degree of the patient and the excretion degree of the patient corresponding to the excretion state of each excretion picture; based on the excretion degree of the patient corresponding to the excretion state of each excretion picture, predicting a predicted cleaning completion time point of the patient through an excretion prediction strategy, and when the predicted cleaning completion time point exceeds a preset time point threshold value, generating intestinal tract cleaning guide information of the patient; and replacing the new intestinal tract cleaning preparation information with the intestinal tract cleaning preparation information, and returning to execute the steps until the predicted cleaning completion time point does not exceed a preset time point threshold value, and completing the intestinal tract cleaning guidance task. By adopting the scheme, the guiding accuracy of the intestinal tract cleaning process can be improved.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence and analysis and prediction technology, and in particular to an intestinal cleaning guidance method and system. Background Art

[0002] With the continuous development of medical technology, intelligent medical technology has gradually replaced traditional medical technology and become an important research and development direction of medical technology today. The auxiliary, guiding and guiding methods of intelligent medical technology in the medical process are the research and development focus of intelligent medical technology. For example, during the preoperative preparation of patients, patients are required to perform intestinal cleansing to avoid affecting the operation, thereby affecting the success rate and effect of the operation. Therefore, how to ensure that the patient's intestinal cleansing is completed, or to guide medical staff to perform intestinal cleansing and medication for patients is the current research focus.

[0003] The traditional method of intestinal cleaning guidance is to manually observe the patient's bowel movements, feelings, and excrement to manually judge the patient's intestinal cleaning effect. However, since manual judgment is affected by manual experience and subjective considerations, the guidance accuracy of the intestinal cleaning process is low. Summary of the invention

[0004] The main purpose of the present invention is to provide an intestinal cleaning guidance method and system, aiming to solve the problem in the prior art that the judgment accuracy of intestinal cleaning effect is low due to the influence of manual judgment on manual experience and manual subjective considerations.

[0005] To achieve the above object, the present invention provides an intestinal cleaning guidance method, the method comprising:

[0006] Acquire the patient's intestinal cleaning preparation information and the patient's intestinal cleaning record information, and identify the patient's defecation frequency and the patient's excrement picture of each defecation based on the intestinal cleaning record information;

[0007] Based on the intestinal cleaning preparation information and the defecation frequency, the preparation adaptation degree of the patient is identified through a preparation analysis strategy, and based on each excrement picture, the excretion degree of the patient corresponding to the excrement state of each excrement picture is identified through an image feature recognition strategy;

[0008] Based on the patient's excretion degree corresponding to the excretion state of each excretion picture, the predicted cleaning completion time point of the patient is predicted through the excretion prediction strategy, and when the predicted cleaning completion time point exceeds the preset time point threshold, the intestinal cleaning guidance information of the patient is generated based on the patient's preparatory adaptation degree and the patient's excretion degree;

[0009] Obtain new intestinal cleaning preparation information obtained by the medical staff when executing the intestinal cleaning guidance information, and replace the intestinal cleaning preparation information with the new intestinal cleaning preparation information, and return to execute the step of obtaining the patient's intestinal cleaning record information, until the predicted cleaning completion time point does not exceed the preset time point threshold, and the intestinal cleaning guidance task is completed.

[0010] Optionally, the identifying the patient's defecation frequency and the feces picture of each defecation of the patient based on the intestinal cleaning record information includes:

[0011] Based on the intestinal cleaning record information, the excretion time point of each excretion of the patient and the initial excrement picture of the patient at each excretion are obtained, and based on the excretion time point of each excretion, the average excretion interval duration is calculated;

[0012] Based on the average defecation interval duration and the total number of defecation times of the patient, the defecation frequency of the patient is calculated, and for the initial defecation picture of each defecation, based on the picture content of the initial defecation picture of the defecation, the excretion edge information in the initial defecation picture is identified by an image edge recognition algorithm;

[0013] The image content surrounded by the excrement edge information is used as the excrement picture of the excrement.

[0014] Optionally, the identifying the patient's preparation adaptation degree through a preparation analysis strategy based on the intestinal cleaning preparation information and the defecation frequency includes:

[0015] Extracting catalyst information of the patient's intestinal cleaning catalyst and dosage information of the intestinal cleaning catalyst from the intestinal cleaning preparation information, and querying the normal excretion frequency of the intestinal cleaning catalyst in a catalyst database based on the catalyst information and the dosage information;

[0016] Based on the normal excretion frequency of the intestinal cleansing catalyst and the excretion frequency of the patient, the excretion frequency deviation value of the patient is calculated, and based on the excretion frequency deviation value, the preparatory adaptation degree of the patient is identified through a preparatory analysis algorithm.

[0017] Optionally, the step of identifying the patient's excretion degree corresponding to the excretion state of each excretion picture by an image feature recognition strategy based on each excretion picture includes:

[0018] For each excrement picture, based on the excrement picture, identifying the image features of each feature type of the excrement picture through an image feature recognition network;

[0019] Based on the image features of each feature type, identifying the image feature value of each feature type, and based on the image feature value of each feature type, identifying the excrement state of the excrement image by using an excrement state identification strategy;

[0020] In the excrement database, the excretion degree corresponding to the excrement state is queried to obtain the patient's excretion degree corresponding to the excrement state of the excrement picture.

[0021] Optionally, the predicted cleaning completion time point of the patient is predicted based on the patient's excretion degree corresponding to the excretion state of each excretion picture, through an excretion prediction strategy, including:

[0022] According to the time sequence of the excretion time points corresponding to each excretion picture, distribution processing is performed on the excretion degree of the patient corresponding to the excretion state corresponding to each excretion picture to obtain the excretion degree distribution information of the patient;

[0023] Generate a curve of the patient's excretion degree change by a curve fitting strategy, and calculate a target excretion time point corresponding to a target excretion degree when the patient completes excretion by a curve trend fitting algorithm based on the excretion degree change curve;

[0024] The target excretion time point is used as the patient's predicted cleaning completion time point.

[0025] Optionally, generating the intestinal cleaning guidance information of the patient based on the patient's preparation adaptation degree and the patient's excretion degree includes:

[0026] Based on the patient's excretion level, identifying the patient's remaining excretion volume, and based on the catalyst meter information, identifying the catalyst type of the intestinal cleansing catalyst;

[0027] Based on the preparatory adaptation degree, the dosage information of the catalyst type, and the remaining excretion amount, in the catalyst database, through a catalyst adaptation network, a target catalyst type of the patient and new dosage information of the target catalyst type are generated, and allergy information of the patient is collected;

[0028] Based on the target catalyst type, the new dosage information of the target catalyst type, and the patient's allergy information, the target intestinal cleansing catalyst of the patient is screened through a catalyst screening strategy, and the target intestinal cleansing catalyst and the new dosage information are used as the patient's intestinal cleaning guidance information.

[0029] In addition, to achieve the above-mentioned purpose, the present invention also provides an intestinal cleaning guidance system, the intestinal cleaning guidance system comprising:

[0030] An acquisition module, used to acquire the patient's intestinal cleaning preparation information and the patient's intestinal cleaning record information, and based on the intestinal cleaning record information, identify the patient's excretion frequency and the patient's excrement picture for each excretion;

[0031] an identification module, for identifying the patient's preparation adaptation degree through a preparation analysis strategy based on the intestinal cleaning preparation information and the excretion frequency, and identifying the patient's excretion degree corresponding to the excretion state of each excretion picture through an image feature recognition strategy based on each excretion picture;

[0032] A guidance module, for predicting the predicted cleaning completion time point of the patient based on the excretion degree of the patient corresponding to the excretion state of each excretion picture through an excretion prediction strategy, and generating intestinal cleaning guidance information for the patient based on the patient's preparatory adaptation degree and the patient's excretion degree when the predicted cleaning completion time point exceeds a preset time point threshold;

[0033] An iteration module is used to obtain new intestinal cleaning preparation information obtained by the medical staff when executing the intestinal cleaning guidance information, and replace the intestinal cleaning preparation information with the new intestinal cleaning preparation information, and return to execute the step of obtaining the intestinal cleaning record information of the patient, until the predicted cleaning completion time point does not exceed the preset time point threshold, and the intestinal cleaning guidance task is completed.

[0034] Optionally, the acquisition module is specifically used to:

[0035] Based on the intestinal cleaning record information, the excretion time point of each excretion of the patient and the initial excrement picture of the patient at each excretion are obtained, and based on the excretion time point of each excretion, the average excretion interval duration is calculated;

[0036] Based on the average defecation interval duration and the total number of defecation times of the patient, the defecation frequency of the patient is calculated, and for the initial defecation picture of each defecation, based on the picture content of the initial defecation picture of the defecation, the excretion edge information in the initial defecation picture is identified by an image edge recognition algorithm;

[0037] The image content surrounded by the excrement edge information is used as the excrement picture of the excrement.

[0038] Optionally, the identification module is specifically used to:

[0039] Extracting catalyst information of the patient's intestinal cleaning catalyst and dosage information of the intestinal cleaning catalyst from the intestinal cleaning preparation information, and querying the normal excretion frequency of the intestinal cleaning catalyst in a catalyst database based on the catalyst information and the dosage information;

[0040] Based on the normal excretion frequency of the intestinal cleansing catalyst and the excretion frequency of the patient, the excretion frequency deviation value of the patient is calculated, and based on the excretion frequency deviation value, the preparatory adaptation degree of the patient is identified through a preparatory analysis algorithm.

[0041] Optionally, the identification module is specifically used to:

[0042] For each excrement picture, based on the excrement picture, identifying the image features of each feature type of the excrement picture through an image feature recognition network;

[0043] Based on the image features of each feature type, identifying the image feature value of each feature type, and based on the image feature value of each feature type, identifying the excrement state of the excrement image by using an excrement state identification strategy;

[0044] In the excrement database, the excretion degree corresponding to the excrement state is queried to obtain the patient's excretion degree corresponding to the excrement state of the excrement picture.

[0045] Optionally, the guidance module is specifically used to:

[0046] According to the time sequence of the excretion time points corresponding to each excretion picture, distribution processing is performed on the excretion degree of the patient corresponding to the excretion state corresponding to each excretion picture to obtain the excretion degree distribution information of the patient;

[0047] Generate a curve of the patient's excretion degree change by a curve fitting strategy, and calculate a target excretion time point corresponding to a target excretion degree when the patient completes excretion by a curve trend fitting algorithm based on the excretion degree change curve;

[0048] The target excretion time point is used as the patient's predicted cleaning completion time point.

[0049] Optionally, the guidance module is specifically used to:

[0050] Based on the patient's excretion level, identifying the patient's remaining excretion volume, and based on the catalyst meter information, identifying the catalyst type of the intestinal cleansing catalyst;

[0051] Based on the preparatory adaptation degree, the dosage information of the catalyst type, and the remaining excretion amount, in the catalyst database, through a catalyst adaptation network, a target catalyst type of the patient and new dosage information of the target catalyst type are generated, and allergy information of the patient is collected;

[0052] Based on the target catalyst type, the new dosage information of the target catalyst type, and the patient's allergy information, the target intestinal cleansing catalyst of the patient is screened through a catalyst screening strategy, and the target intestinal cleansing catalyst and the new dosage information are used as the patient's intestinal cleaning guidance information.

[0053] In a third aspect, the present application provides a computer device, wherein the computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of any one of the methods in the first aspect are implemented.

[0054] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0055] In a fifth aspect, the present application provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0056] The present invention provides an intestinal cleaning guidance method and system, the method comprising: obtaining intestinal cleaning preparation information of a patient and intestinal cleaning record information of the patient, and based on the intestinal cleaning record information, identifying the patient's excretion frequency and the patient's excretion picture of each excretion; based on the intestinal cleaning preparation information and the excretion frequency, identifying the patient's preparation adaptation degree through a preparation analysis strategy, and based on each excretion picture, identifying the patient's excretion degree corresponding to the excretion state of each excretion picture through an image feature recognition strategy; based on the patient's excretion degree corresponding to the excretion state of each excretion picture, predicting the patient's predicted cleaning completion time point through an excretion prediction strategy, and when the predicted cleaning completion time point exceeds a preset time point threshold, generating the patient's intestinal cleaning guidance information based on the patient's preparation adaptation degree and the patient's excretion degree; obtaining the new intestinal cleaning preparation information obtained by the medical staff executing the intestinal cleaning guidance information, replacing the intestinal cleaning preparation information with the new intestinal cleaning preparation information, returning to the step of obtaining the patient's intestinal cleaning record information, until the predicted cleaning completion time point does not exceed the preset time point threshold, the intestinal cleaning guidance task is completed. This solution conducts a comprehensive analysis of the intestinal cleaning preparation information and intestinal cleaning record information to identify the patient's degree of adaptation to intestinal cleaning preparation, and then extracts image features from each excrement picture to identify the excrement status of each excrement picture, thereby predicting the patient's predicted cleaning completion time point as a judgment standard for intestinal cleaning guidance information, and then comprehensively generates the patient's intestinal cleaning guidance information from the two perspectives of the patient's degree of adaptation and excretion level, thereby improving the comprehensiveness and accuracy of the generated intestinal cleaning guidance information. Afterwards, the terminal repeats the above steps to adjust the patient's intestinal cleaning guidance in real time to ensure that the renewal can complete the intestinal cleaning task before the preset time point threshold, thereby improving the judgment accuracy of intestinal cleaning, thereby comprehensively improving the guidance accuracy of the intestinal cleaning process. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the scheme in the present application, a brief introduction is given below to the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0058] Figure 1 is a flow chart of an intestinal cleaning guidance method provided by an embodiment of the present invention;

[0059] Figure 2 is a schematic structural diagram of an intestinal cleaning guidance system provided by an embodiment of the present invention;

[0060] Figure 3 An internal structure diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0061] The intestinal cleaning guidance method provided by the embodiment of the present invention is applied to the intestinal cleaning guidance system. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of the present application; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "including" and "having" in the specification and claims of the present application and the above-mentioned drawings and any variations thereof are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of the present application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0062] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0063] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0064] The intestinal cleaning guidance method provided by the embodiment of the present application can be applied to the application environment of dietary control. Among them, the method can be applied to a terminal, a server, or a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. Among them, the terminal can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, etc. Among them, the terminal comprehensively analyzes the intestinal cleaning preparation information and the intestinal cleaning record information to identify the patient's degree of preparation for intestinal cleaning preparation, and then extracts the image features of each excrement picture to identify the excrement state of each excrement picture, thereby predicting the patient's predicted cleaning completion time point as a judgment standard for the intestinal cleaning guidance information, and then comprehensively generates the patient's intestinal cleaning guidance information from the two perspectives of the patient's preparation adaptation degree and excretion degree, thereby improving the comprehensiveness and accuracy of the generated intestinal cleaning guidance information. After that, the terminal repeats the above steps to adjust the intestinal cleaning work of the patient in real time to ensure that the renewal can complete the intestinal cleaning task before the preset time point threshold, thereby improving the judgment accuracy of intestinal cleaning, thereby comprehensively improving the guidance accuracy of the intestinal cleaning process.

[0065] In one embodiment, Figure 1 As shown, a method for guiding intestinal cleaning is provided, which is described by taking the method applied to a terminal as an example, and includes the following steps:

[0066] Step S101, obtaining the patient's intestinal cleaning preparation information and the patient's intestinal cleaning record information, and based on the intestinal cleaning record information, identifying the patient's defecation frequency and the patient's excrement picture for each defecation.

[0067] In this embodiment, the terminal responds to the information upload operation of the medical staff, obtains the intestinal cleaning catalyst configured by the medical staff for the intestinal cleaning of the patient, and the dosage information of the intestinal cleaning catalyst, and uses the intestinal cleaning catalyst and the dosage information of the intestinal cleaning catalyst as intestinal cleaning preparation information. Among them, the intestinal cleaning catalyst can be an edible intestinal cleaning agent such as an intestinal lubricant, a laxative, and an intestinal cleaning agent of different catalyst types. The catalyst type includes, but is not limited to, a lubrication type, an excretion promotion type, an excrement decomposition type, an intestinal autonomous peristalsis type, and other types of agents used to promote the excretion of intestinal food residues. Then, the terminal responds to the patient's information upload operation, obtains the time point of each excretion of the patient after taking the intestinal cleaning catalyst, excrement photos and other information, and obtains the patient's intestinal cleaning record information. Afterwards, the terminal identifies the patient's excretion frequency and the excrement picture of each excretion of the patient based on the intestinal cleaning record information. The specific identification process will be described in detail later. The excretion frequency is the average number of excretions of the patient per unit time. The unit time is the time period preset by the staff at the terminal. The time period is, for example, 30 minutes, 1 hour, 2 hours, 3 hours, etc.

[0068] Step S102, based on the intestinal cleaning preparation information and the defecation frequency, the patient's preparation adaptation degree is identified through a preparation analysis strategy, and based on each excrement picture, the patient's excretion degree corresponding to the excrement state of each excrement picture is identified through an image feature recognition strategy.

[0069] In this embodiment, the terminal identifies the patient's preparatory adaptation degree through a preparatory analysis strategy based on the intestinal cleaning preparation information and the excretion frequency, and identifies the patient's excretion degree corresponding to the excretion state of each excretion picture through an image feature recognition strategy based on each excretion picture. Among them, the preparatory adaptation degree is the patient's adaptation degree to the excretion catalyst, wherein the higher the adaptation degree, the higher the excretion frequency of the patient after taking the excretion catalyst. The lower the adaptation degree, the lower the excretion frequency of the patient after taking the excretion catalyst. The specific recognition process will be described in detail later. The image feature recognition strategy includes an image feature recognition network and an excretion state recognition strategy. The specific recognition process will be described in detail later. The image feature recognition network is a convolutional neural network based on a self-attention mechanism.

[0070] Step S103, based on the patient's excretion degree corresponding to the excretion state of each excretion picture, the patient's predicted cleaning completion time point is predicted through the excretion prediction strategy, and when the predicted cleaning completion time point exceeds the preset time point threshold, the patient's intestinal cleaning guidance information is generated based on the patient's preparatory adaptation degree and the patient's excretion degree.

[0071] In this embodiment, the terminal predicts the patient's predicted cleaning completion time point based on the patient's excretion degree corresponding to the excretion state of each excretion picture through the excretion prediction strategy, and generates the patient's intestinal cleaning guidance information based on the patient's preparatory adaptation degree and the patient's excretion degree when the predicted cleaning completion time point exceeds the preset time point threshold. Among them, the excretion prediction strategy is to obtain the excretion degree distribution information after distribution fitting of the excretion degree corresponding to the excretion state of the excretion picture recorded at each time point, and then perform trend prediction to obtain the prediction strategy for the time point when intestinal cleaning is completed. The specific prediction process will be described in detail later. Among them, the intestinal cleaning guidance information includes the target intestinal cleaning catalyst and the new dosage information of the target intestinal cleaning catalyst.

[0072] Step S104, obtain new intestinal cleaning preparation information obtained by the medical staff when executing the intestinal cleaning guidance information, and replace the intestinal cleaning preparation information with the new intestinal cleaning preparation information, and return to execute the step of obtaining the patient's intestinal cleaning record information, until the predicted cleaning completion time point does not exceed the preset time point threshold, and the intestinal cleaning guidance task is completed.

[0073] In this embodiment, the terminal sends the intestinal cleaning guidance information to the medical staff client, so that the medical staff obtains new intestinal cleaning preparation information after performing the intestinal cleaning preparation process on the patient again. The new intestinal cleaning preparation information replaces the intestinal cleaning preparation information, and returns to the step of obtaining the patient's intestinal cleaning record information until the predicted cleaning completion time point does not exceed the preset time point threshold, and the intestinal cleaning guidance task is completed. Among them, the above-mentioned return execution process is an iterative process, that is, when the predicted cleaning completion time point does not exceed the preset time point threshold, this solution will iteratively execute steps S101 to S103, so as to adjust the patient's intestinal cleaning guidance information in a cyclic, real-time manner. The above-mentioned iterative process is stopped until the intestinal cleaning guidance task is completed.

[0074] Based on the above scheme, the patient's degree of adaptation to intestinal cleaning preparation is identified by comprehensively analyzing the intestinal cleaning preparation information and the intestinal cleaning record information, and then the excrement status of each excrement picture is identified by extracting image features from each excrement picture, thereby predicting the patient's predicted cleaning completion time point as a judgment standard for intestinal cleaning guidance information, and then comprehensively generating the patient's intestinal cleaning guidance information from the two perspectives of the patient's degree of adaptation and excretion level, thereby improving the comprehensiveness and accuracy of the generated intestinal cleaning guidance information. Afterwards, the terminal repeats the above steps to adjust the patient's intestinal cleaning work guidance in real time, ensuring that the patient can complete the intestinal cleaning task before the preset time point threshold, thereby improving the judgment accuracy of intestinal cleaning, and thus comprehensively improving the guidance accuracy of the intestinal cleaning process.

[0075] Optionally, based on the intestinal cleaning record information, the patient's defecation frequency and the patient's feces picture of each defecation are identified, including: based on the intestinal cleaning record information, the defecation time point of the patient at each defecation and the patient's initial feces picture at each defecation are obtained, and based on the defecation time point of each defecation, the average defecation interval duration is calculated; based on the average defecation interval duration and the patient's total number of defecation times, the patient's defecation frequency is calculated, and for the initial feces picture of each defecation, based on the picture content of the initial feces picture of the defecation, the feces edge information in the initial feces picture is identified through an image edge recognition algorithm; the image content surrounded by the feces edge information is used as the feces picture of the defecation.

[0076] In this embodiment, the terminal obtains the patient's excretion time point at each excretion and the patient's initial excrement picture at each excretion based on the intestinal cleaning record information, and calculates the average excretion interval duration based on the excretion time point of each excretion. The excretion time point of each excretion is the time point of each excretion of the patient calculated from the moment after the patient completes the intestinal cleaning preparation information.

[0077] Based on the average excretion interval and the total number of excretions of the patient, the terminal calculates the number of excretions per unit time of the patient according to the unit time preset in the terminal, and obtains the excretion frequency of the patient. Then, for the initial excretion picture of each excretion, the terminal identifies the excretion edge information in the initial excretion picture based on the picture content of the initial excretion picture of the excretion through an image edge recognition algorithm. Among them, the image edge recognition algorithm is an edge detection algorithm based on the Sobel operator. Finally, the terminal uses the image content surrounded by the excretion edge information as the excretion picture of the excretion.

[0078] Based on the above scheme, after image edge recognition, excrement pictures are screened, which can effectively reduce the interference and influence of non-excrement pictures on subsequent image feature recognition, thereby improving the screening accuracy of excrement pictures.

[0079] Optionally, based on the intestinal cleaning preparation information and the excretion frequency, the patient's preparation adaptation degree is identified through a preparation analysis strategy, including: extracting the catalyst information of the patient's intestinal cleaning catalyst and the dosage information of the intestinal cleaning catalyst from the intestinal cleaning preparation information, and based on the catalyst information and the dosage information, querying the normal excretion frequency of the intestinal cleaning catalyst in the catalyst database; based on the normal excretion frequency of the intestinal cleaning catalyst and the patient's excretion frequency, calculating the patient's excretion frequency deviation value, and based on the excretion frequency deviation value, identifying the patient's preparation adaptation degree through a preparation analysis algorithm.

[0080] In this embodiment, the terminal extracts the catalyst information of the patient's intestinal cleaning catalyst and the dosage information of the intestinal cleaning catalyst from the intestinal cleaning preparation information, and based on the catalyst information and the dosage information, queries the normal excretion frequency of the intestinal cleaning catalyst in the catalyst database. The catalyst database includes normal excretion frequency ranges corresponding to different intestinal catalysts under different dosage ranges, wherein the normal excretion frequency range corresponding to the dosage range includes the normal excretion frequency corresponding to each dosage information. Then, based on the above correspondence, the terminal identifies the normal excretion frequency corresponding to the dosage information of the patient's intestinal cleaning catalyst.

[0081] Finally, the terminal subtracts the patient's excretion frequency from the normal excretion frequency of the intestinal cleaning catalyst to obtain the patient's excretion frequency deviation value. The excretion frequency deviation value has positive and negative values. A positive value indicates that the normal excretion frequency is greater than the patient's excretion frequency; a negative value indicates that the normal excretion frequency is not greater than the patient's excretion frequency. Then, based on the excretion frequency deviation value, the terminal identifies the patient's preparatory adaptation degree through a preparatory analysis algorithm. The preparatory analysis algorithm is a ratio between the excretion frequency deviation value and the preparatory adaptation degree. The terminal obtains the patient's preparatory adaptation degree by multiplying the excretion frequency deviation value by the preparatory analysis algorithm.

[0082] Based on the above scheme, the normal excretion frequency corresponding to the dosage information of the intestinal cleansing catalyst is queried to calculate the patient's readiness adaptation degree, thereby reducing the complex judgment process of identifying the patient's readiness adaptation degree and being able to accurately identify the patient's readiness adaptation degree, thereby effectively improving the efficiency and accuracy of identifying the patient's readiness adaptation degree.

[0083] Optionally, based on each excrement picture, an image feature recognition strategy is used to identify the patient's excretion degree corresponding to the excretion status of each excrement picture, including: for each excrement picture, based on the excrement picture, using an image feature recognition network, identifying the image features of each feature type of the excrement picture; based on the image features of each feature type, identifying the image feature value of each feature type, and based on the image feature value of each feature type, identifying the excretion status of the excrement picture through an excrement status recognition strategy; in an excrement database, querying the excretion degree corresponding to the excretion status to obtain the patient's excretion degree corresponding to the excretion status of the excrement picture.

[0084] In this embodiment, the terminal identifies the image features of each feature type of the excrement picture based on the excrement picture through an image feature recognition network. The image feature recognition network is a ResNet neural network. The feature types include, but are not limited to, excrement color type, excrement turbidity type, excrement oil measurement type, excrement morphology ratio type, etc.

[0085] Afterwards, the terminal identifies the image feature value of each feature type based on the image feature of each feature type, and identifies the excrement state of the excrement image through the excrement state recognition strategy based on the image feature value of each feature type. The excrement state includes but is not limited to a formed state, a thin and soft state, a thick liquid state, a thin liquid state, a turbid liquid state, and a pure liquid state. When the excrement state is closer to a pure liquid state, it indicates that the intestinal cleaning task is closer to completion, and when the excrement state is closer to a formed state, it indicates that the intestinal cleaning task is closer to 0.

[0086] Then, the terminal searches the excretion database for the excretion degree corresponding to the excretion state, and obtains the excretion degree of the patient corresponding to the excretion state of the excretion picture. The excretion database includes the corresponding relationship between each excretion state and the excretion degree.

[0087] Based on the above scheme, the excretion status of the patient is identified to determine the excretion degree of the patient, thereby improving the comprehensiveness and accuracy of the identification of the patient's excretion degree.

[0088] Optionally, based on the patient's excretion degree corresponding to the excretion state of each excretion picture, an excretion prediction strategy is used to predict the patient's predicted cleaning completion time point, including: distributing the patient's excretion degree corresponding to the excretion state corresponding to each excretion picture according to the time sequence of the excretion time points corresponding to each excretion picture, to obtain the patient's excretion degree distribution information; generating the patient's excretion degree change curve through a curve fitting strategy, and based on the excretion degree change curve, calculating the target excretion time point corresponding to the target excretion degree when the patient completes excretion through a curve trend fitting algorithm; and using the target excretion time point as the patient's predicted cleaning completion time point.

[0089] In this embodiment, the terminal performs distribution processing on the excretion degree of the patient corresponding to the excretion state corresponding to each excretion picture according to the time sequence of the excretion time point corresponding to each excretion picture, and obtains the excretion degree distribution information of the patient. The excretion degree distribution information is a discrete point distribution table with the excretion time point as the horizontal axis and the excretion degree as the vertical axis.

[0090] Then, the terminal uses a curve fitting strategy to perform discrete point curve fitting on the above discrete point distribution table to obtain the patient's excretion degree change curve. After that, based on the excretion degree change curve, the terminal uses a curve trend fitting algorithm to calculate the target excretion time point corresponding to the target excretion degree when the patient completes excretion. Among them, the curve trend fitting algorithm is the LM iterative algorithm. Among them, the target excretion degree is the excretion degree preset by the medical staff in the terminal. The excretion degree can be 100%, 90%, or any excretion degree value.

[0091] Finally, the terminal uses the target excretion time point as the patient's predicted cleaning completion time point.

[0092] Based on the above scheme, the patient's target excretion time point is predicted by curve fitting, avoiding the problem of discrete points interfering with the prediction accuracy, thereby improving the recognition accuracy of the predicted cleaning completion time point.

[0093] Optionally, based on the patient's preparatory adaptation degree and the patient's excretion degree, intestinal cleaning guidance information is generated for the patient, including: based on the patient's excretion degree, identifying the patient's remaining excretion volume, and based on the catalyst meter information, identifying the catalyst type of the intestinal cleaning catalyst; based on the preparatory adaptation degree, the dosage information of the catalyst type, and the remaining excretion volume, in the catalyst database, through the catalyst adaptation network, the patient's target catalyst type and new dosage information of the target catalyst type are generated, and the patient's allergy information is collected; based on the target catalyst type, the new dosage information of the target catalyst type, and the patient's allergy information, the patient's target intestinal cleaning catalyst is screened through a catalyst screening strategy, and the target intestinal cleaning catalyst and the new dosage information are used as the patient's intestinal cleaning guidance information.

[0094] In this embodiment, the terminal identifies the remaining excretion volume of the patient based on the excretion degree of the patient. Specifically, the terminal queries the corresponding relationship between each excretion degree and the remaining excretion volume in the excretion database based on the excretion degree of the patient, and obtains the remaining excretion volume corresponding to the excretion degree of the patient. Then, the terminal identifies the catalyst type of the intestinal cleansing catalyst based on the catalyst meter information.

[0095] Based on the prepared adaptation degree, the dosage information of the catalyst type, and the remaining excretion, the terminal generates the patient's target catalyst type and new dosage information of the target catalyst type in the catalyst database through the catalyst adaptation network, and collects the patient's allergy information. Among them, the catalyst adaptation network is a neural network based on reinforcement learning. Among them, the allergy information is the allergy information to different substances.

[0096] Then, the terminal screens the target intestinal cleaning catalyst for the patient through a catalyst screening strategy based on the target catalyst type, the new dosage information of the target catalyst type, and the patient's allergic information. Specifically, the terminal screens each first intestinal cleaning catalyst among each intestinal cleaning catalyst belonging to the target catalyst type based on the target catalyst type and the new dosage information of the target catalyst type, and based on the content information in each first intestinal cleaning catalyst, screens each second intestinal cleaning catalyst corresponding to the substance that does not contain the patient's allergic information, and screens the second intestinal cleaning catalyst containing the least irritating substance in each second intestinal cleaning catalyst as the target intestinal cleaning catalyst. Among them, the terminal presets the material information of each irritating substance and the irritation degree of each irritating substance, and then, the terminal screens the second intestinal cleaning catalyst that does not contain irritating substances or contains the least irritating substances in each second intestinal cleaning catalyst as the target intestinal cleaning catalyst. Finally, the terminal uses the target intestinal cleaning catalyst and the new dosage information as the intestinal cleaning guidance information for the patient.

[0097] In addition to the target intestinal cleaning catalyst that the patient needs to take and the new dosage information of the target intestinal cleaning catalyst, the intestinal cleaning guidance information can also generate the range of edible foods, the range of contraindicated products (duration of emergency products and types of contraindicated products), and auxiliary catalytic behaviors (such as exercise frequency, walking frequency, rest interval duration, etc.) after the patient takes the target intestinal cleaning catalyst according to the information stored in the catalyst database of the target intestinal cleaning catalyst. In addition, the new dosage information includes not only the dosage value of the target intestinal cleaning catalyst, but also the time interval and time point of taking the target intestinal cleaning catalyst.

[0098] Based on the above scheme, through the analysis of catalyst types and dosage information, it is ensured that when the intestinal cleansing catalyst is used for the patient, it can be distinguished from the current intestinal catalyst, and the dosage can be determined based on the current dosage information of the intestinal cleansing catalyst, thereby effectively reducing the side effects of the intestinal cleansing catalyst on the patient while ensuring that the intestinal cleansing effect of the patient is effectively improved. Then, this scheme screens the target intestinal cleansing catalyst from the two perspectives of the patient's allergy information and irritating substances, which can further reduce the side effects of the intestinal cleansing catalyst on the patient and improve the accuracy, reliability, and practicality of the intestinal cleaning guidance information for the patient.

[0099] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0100] Based on the same inventive concept, the embodiment of the present application also provides an intestinal cleaning guidance system for implementing the intestinal cleaning guidance method involved above. The implementation scheme for solving the problem provided by the system is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more intestinal cleaning guidance system embodiments provided below can refer to the limitations of the intestinal cleaning guidance method above, and will not be repeated here.

[0101] Further references Figure 2 , as a response to the above Figure 1 To implement the method shown, the present application provides an embodiment of a bowel cleaning guidance system 200, the bowel cleaning guidance system comprising an acquisition module 210, an identification module 220, a guidance module 230 and an iteration module 240, wherein:

[0102] The acquisition module 210 is used to acquire the patient's intestinal cleaning preparation information and the patient's intestinal cleaning record information, and identify the patient's defecation frequency and the patient's excrement picture of each defecation based on the intestinal cleaning record information;

[0103] The identification module 220 is used to identify the patient's preparation adaptation degree through a preparation analysis strategy based on the intestinal cleaning preparation information and the defecation frequency, and to identify the patient's defecation degree corresponding to the defecation state of each defecation picture through an image feature recognition strategy based on each defecation picture;

[0104] The guidance module 230 is used to predict the predicted cleaning completion time point of the patient based on the patient's excretion degree corresponding to the excretion state of each excretion picture through the excretion prediction strategy, and generate the intestinal cleaning guidance information of the patient based on the patient's preparatory adaptation degree and the patient's excretion degree when the predicted cleaning completion time point exceeds the preset time point threshold;

[0105] Iteration module 240 is used to obtain new intestinal cleaning preparation information obtained by the medical staff when executing the intestinal cleaning guidance information, and replace the intestinal cleaning preparation information with the new intestinal cleaning preparation information, and return to execute the step of obtaining the intestinal cleaning record information of the patient, until the predicted cleaning completion time point does not exceed the preset time point threshold, and the intestinal cleaning guidance task is completed.

[0106] Optionally, the acquisition module 210 is specifically configured to:

[0107] Based on the intestinal cleaning record information, the excretion time point of each excretion of the patient and the initial excrement picture of the patient at each excretion are obtained, and based on the excretion time point of each excretion, the average excretion interval duration is calculated;

[0108] Based on the average defecation interval duration and the total number of defecation times of the patient, the defecation frequency of the patient is calculated, and for the initial defecation picture of each defecation, based on the picture content of the initial defecation picture of the defecation, the excretion edge information in the initial defecation picture is identified by an image edge recognition algorithm;

[0109] The image content surrounded by the excrement edge information is used as the excrement picture of the excrement.

[0110] Optionally, the identification module 220 is specifically configured to:

[0111] Extracting catalyst information of the patient's intestinal cleaning catalyst and dosage information of the intestinal cleaning catalyst from the intestinal cleaning preparation information, and querying the normal excretion frequency of the intestinal cleaning catalyst in a catalyst database based on the catalyst information and the dosage information;

[0112] Based on the normal excretion frequency of the intestinal cleansing catalyst and the excretion frequency of the patient, the excretion frequency deviation value of the patient is calculated, and based on the excretion frequency deviation value, the preparatory adaptation degree of the patient is identified through a preparatory analysis algorithm.

[0113] Optionally, the identification module 220 is specifically configured to:

[0114] For each excrement picture, based on the excrement picture, identifying the image features of each feature type of the excrement picture through an image feature recognition network;

[0115] Based on the image features of each feature type, identifying the image feature value of each feature type, and based on the image feature value of each feature type, identifying the excrement state of the excrement image by using an excrement state identification strategy;

[0116] In the excrement database, the excretion degree corresponding to the excrement state is queried to obtain the patient's excretion degree corresponding to the excrement state of the excrement picture.

[0117] Optionally, the guidance module 230 is specifically used to:

[0118] According to the time sequence of the excretion time points corresponding to each excretion picture, distribution processing is performed on the excretion degree of the patient corresponding to the excretion state corresponding to each excretion picture to obtain the excretion degree distribution information of the patient;

[0119] Generate a curve of the patient's excretion degree change by a curve fitting strategy, and calculate a target excretion time point corresponding to a target excretion degree when the patient completes excretion by a curve trend fitting algorithm based on the excretion degree change curve;

[0120] The target excretion time point is used as the patient's predicted cleaning completion time point.

[0121] Optionally, the guidance module 230 is specifically used to:

[0122] Based on the patient's excretion level, identifying the patient's remaining excretion volume, and based on the catalyst meter information, identifying the catalyst type of the intestinal cleansing catalyst;

[0123] Based on the preparatory adaptation degree, the dosage information of the catalyst type, and the remaining excretion amount, in the catalyst database, through a catalyst adaptation network, a target catalyst type of the patient and new dosage information of the target catalyst type are generated, and allergy information of the patient is collected;

[0124] Based on the target catalyst type, the new dosage information of the target catalyst type, and the patient's allergy information, the target intestinal cleansing catalyst of the patient is screened through a catalyst screening strategy, and the target intestinal cleansing catalyst and the new dosage information are used as the patient's intestinal cleaning guidance information.

[0125] Each module in the above-mentioned intestinal cleaning guidance system can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module.

[0126] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 3As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input system connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for guiding intestinal cleaning is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input system of the computer device can be a touch layer covered on the display screen, or a button, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0127] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0128] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the steps of any one of the methods in the first aspect are implemented.

[0129] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0130] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the steps of any one of the methods in the first aspect.

[0131] It should be noted that the patient information (including but not limited to patient device information, patient personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the patient or fully authorized by all parties.

[0132] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0133] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0134] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for guiding intestinal cleaning, characterized in that: The method comprises: Acquire the patient's intestinal cleaning preparation information and the patient's intestinal cleaning record information, and identify the patient's defecation frequency and the patient's excrement picture of each defecation based on the intestinal cleaning record information; Based on the intestinal cleaning preparation information and the defecation frequency, the preparation adaptation degree of the patient is identified through a preparation analysis strategy, and based on each excrement picture, the excretion degree of the patient corresponding to the excrement state of each excrement picture is identified through an image feature recognition strategy; Based on the patient's excretion degree corresponding to the excretion state of each excretion picture, the predicted cleaning completion time point of the patient is predicted through the excretion prediction strategy, and when the predicted cleaning completion time point exceeds the preset time point threshold, the intestinal cleaning guidance information of the patient is generated based on the patient's preparatory adaptation degree and the patient's excretion degree; Obtain new intestinal cleaning preparation information obtained by the medical staff when executing the intestinal cleaning guidance information, and replace the intestinal cleaning preparation information with the new intestinal cleaning preparation information, and return to execute the step of obtaining the patient's intestinal cleaning record information, until the predicted cleaning completion time point does not exceed the preset time point threshold, and the intestinal cleaning guidance task is completed.

2. The method according to claim 1, characterized in that The step of identifying the patient's defecation frequency and a picture of the patient's excrement each time defecation is based on the intestinal cleaning record information, including: Based on the intestinal cleaning record information, the excretion time point of each excretion of the patient and the initial excrement picture of the patient at each excretion are obtained, and based on the excretion time point of each excretion, the average excretion interval duration is calculated; Based on the average defecation interval duration and the total number of defecation times of the patient, the defecation frequency of the patient is calculated, and for the initial defecation picture of each defecation, based on the picture content of the initial defecation picture of the defecation, the excretion edge information in the initial defecation picture is identified by an image edge recognition algorithm; The image content surrounded by the excrement edge information is used as the excrement picture of the excrement.

3. The method according to claim 1, characterized in that The step of identifying the patient's preparation adaptability based on the intestinal cleaning preparation information and the defecation frequency through a preparation analysis strategy includes: Extracting catalyst information of the patient's intestinal cleaning catalyst and dosage information of the intestinal cleaning catalyst from the intestinal cleaning preparation information, and querying the normal excretion frequency of the intestinal cleaning catalyst in a catalyst database based on the catalyst information and the dosage information; Based on the normal excretion frequency of the intestinal cleansing catalyst and the excretion frequency of the patient, the excretion frequency deviation value of the patient is calculated, and based on the excretion frequency deviation value, the preparatory adaptation degree of the patient is identified through a preparatory analysis algorithm.

4. The method according to claim 1, characterized in that: The method of identifying the patient's excretion degree corresponding to the excretion state of each excretion picture by an image feature recognition strategy based on each excretion picture includes: For each excrement picture, based on the excrement picture, identifying the image features of each feature type of the excrement picture through an image feature recognition network; Based on the image features of each feature type, identifying the image feature value of each feature type, and based on the image feature value of each feature type, identifying the excrement state of the excrement image by using an excrement state identification strategy; In the excrement database, the excretion degree corresponding to the excrement state is queried to obtain the patient's excretion degree corresponding to the excrement state of the excrement picture.

5. The method according to claim 4, characterized in that The predicted cleaning completion time point of the patient is predicted based on the patient's excretion degree corresponding to the excretion state of each excretion picture and through an excretion prediction strategy, including: According to the time sequence of the excretion time points corresponding to each excretion picture, distribution processing is performed on the excretion degree of the patient corresponding to the excretion state corresponding to each excretion picture to obtain the excretion degree distribution information of the patient; Generate a curve of the patient's excretion degree change by a curve fitting strategy, and calculate a target excretion time point corresponding to a target excretion degree when the patient completes excretion by a curve trend fitting algorithm based on the excretion degree change curve; The target excretion time point is used as the patient's predicted cleaning completion time point.

6. The method according to claim 3, characterized in that The step of generating the patient's intestinal cleaning guidance information based on the patient's preparation adaptation degree and the patient's excretion degree includes: Based on the patient's excretion level, identifying the patient's remaining excretion volume, and based on the catalyst meter information, identifying the catalyst type of the intestinal cleansing catalyst; Based on the preparatory adaptation degree, the dosage information of the catalyst type, and the remaining excretion amount, in the catalyst database, through a catalyst adaptation network, a target catalyst type of the patient and new dosage information of the target catalyst type are generated, and allergy information of the patient is collected; Based on the target catalyst type, the new dosage information of the target catalyst type, and the patient's allergy information, the target intestinal cleansing catalyst of the patient is screened through a catalyst screening strategy, and the target intestinal cleansing catalyst and the new dosage information are used as the patient's intestinal cleaning guidance information.

7. An intestinal cleaning guidance system, characterized in that: The system comprises: An acquisition module, used to acquire the patient's intestinal cleaning preparation information and the patient's intestinal cleaning record information, and based on the intestinal cleaning record information, identify the patient's excretion frequency and the patient's excrement picture for each excretion; an identification module, for identifying the patient's preparation adaptation degree through a preparation analysis strategy based on the intestinal cleaning preparation information and the excretion frequency, and identifying the patient's excretion degree corresponding to the excretion state of each excretion picture through an image feature recognition strategy based on each excretion picture; A guidance module, for predicting the predicted cleaning completion time point of the patient based on the excretion degree of the patient corresponding to the excretion state of each excretion picture through an excretion prediction strategy, and generating intestinal cleaning guidance information for the patient based on the patient's preparatory adaptation degree and the patient's excretion degree when the predicted cleaning completion time point exceeds a preset time point threshold; An iteration module is used to obtain new intestinal cleaning preparation information obtained by the medical staff when executing the intestinal cleaning guidance information, and replace the intestinal cleaning preparation information with the new intestinal cleaning preparation information, and return to execute the step of obtaining the intestinal cleaning record information of the patient, until the predicted cleaning completion time point does not exceed the preset time point threshold, and the intestinal cleaning guidance task is completed.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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