Multi-mode ophthalmology auxiliary diagnosis nursing follow-up visit system

Abstract

The invention relates to a multi-mode ophthalmology auxiliary diagnosis and nursing follow-up visit system which comprises a multi-mode ophthalmology basic data collection module used for obtaining a patient identifier when a patient inquires for the first time, obtaining new multi-mode ophthalmology basic data of the patient in each disease course stage according to the patient identifier, and sending the new multi-mode ophthalmology basic data to a follow-up visit module; determining auxiliary information of the new multi-mode ophthalmology basic data, and storing the new multi-mode ophthalmology basic data and the auxiliary information; the whole-course auxiliary diagnosis module is used for determining an auxiliary diagnosis decision according to the multi-mode ophthalmology basic data and the auxiliary information; the whole-course nursing follow-up visit module is used for determining a follow-up visit level and generating a nursing follow-up visit scheme according to the multi-mode ophthalmology basic data and auxiliary information; and the output module is used for outputting a nursing follow-up scheme and / or an auxiliary diagnosis decision according to the follow-up level, so that the auxiliary diagnosis nursing follow-up of the whole disease course stage can be realized, and the auxiliary accuracy of each disease course stage is ensured.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and particularly to a multimodal ophthalmic assisted diagnosis, nursing and follow-up system. Background Art

[0002] As a serious visual impairment disease, irreversible blinding eye diseases have a great impact on patients' daily life, work, psychological state, social relations, etc., seriously affecting the quality of life of patients, and have become an important issue of concern to individuals, families and the whole society. In recent years, with the continuous development of genetics and cytology, stem cell transplantation and gene therapy have become new directions and research hotspots for the treatment of irreversible blinding eye diseases.

[0003] The current ophthalmic assisted diagnosis, nursing and follow-up system only targets patients who have undergone stem cell transplantation and gene therapy surgery, such as observing the operated eye, providing medication guidance, life care, preventing complications, following up, etc., to ensure that the basic needs of patients are met.

[0004] The patients of the current ophthalmic assisted diagnosis, nursing and follow-up system are only in-hospital and post-discharge patients, and there may be insufficient information about patients before hospitalization. However, the pre-hospital information will also affect the assisted diagnosis results during and after hospitalization, which makes the current ophthalmic assisted diagnosis, nursing and follow-up system have poor assisted accuracy. Summary of the Invention

[0005] (I) Technical Problems to be Solved

[0006] In order to solve the above problems, the present invention provides a multimodal ophthalmic assisted diagnosis, nursing and follow-up system.

[0007] (II) Technical Solutions

[0008] In order to achieve the above object, the main technical solutions adopted by the present invention include: a multimodal ophthalmic assisted diagnosis, nursing and follow-up system, which includes: a multimodal ophthalmic basic data collection module, a full-course assisted diagnosis module, a full-course nursing and follow-up module, and an output module;

[0009] Among them, the multimodal ophthalmic basic data collection module is used to obtain the patient identifier when the patient first visits, and after obtaining the new multimodal ophthalmic basic data of the patient at each disease stage according to the patient identifier, determine the auxiliary information of the new multimodal ophthalmic basic data, and store the new multimodal ophthalmic basic data and the auxiliary information; wherein, the disease stage is the pre-hospital stage, the in-hospital stage, or the post-discharge stage;

[0010] The full-course assisted diagnosis module is used to determine the assisted diagnosis decision according to the multimodal ophthalmic basic data and the auxiliary information stored by the multimodal ophthalmic basic data collection module;

[0011] The nursing follow-up module for the entire course of the disease is used to determine the follow-up level and generate a nursing follow-up plan based on the multi-modal basic ophthalmological data and auxiliary information stored in the multi-modal basic ophthalmological data collection module;

[0012] The output module is used to output the nursing follow-up plan generated by the nursing follow-up module for the entire course of the disease and / or the auxiliary diagnosis decision obtained from the auxiliary diagnosis module for the entire course of the disease according to the follow-up level.

[0013] Optionally, the modalities of the basic ophthalmological data include: text modality, image modality, imaging modality, audio modality;

[0014] Determine the auxiliary information of the new multi-modal basic ophthalmological data, including:

[0015] Determine the generation time of the new multi-modal basic ophthalmological data where i is the patient identifier and j is the identifier of the patient's basic ophthalmological data;

[0016] Determine the disease course stage of the new multi-modal basic ophthalmological data

[0017] Determine the summary of the new multi-modal basic ophthalmological data according to the modality of the new multi-modal basic ophthalmological data and the auxiliary diseases

[0018] According to the summary Determine the associated data from the multi-modal basic ophthalmological data already stored by the patient;

[0019] Extract the key attribute values from the new multi-modal basic ophthalmological data and the associated data;

[0020] Form a description of the new multi-modal basic ophthalmological data based on the key attribute values in the new multi-modal basic ophthalmological data and the associated data

[0021] The and Form the auxiliary information of the new multi-modal basic ophthalmological data.

[0022] Optionally, form a description of the new multi-modal basic ophthalmological data based on the key attribute values in the new multi-modal basic ophthalmological data and the associated data including:

[0023] Determine the comparison data by taking the associated data with the closest production time to as the comparison data;

[0024] Identify the key attributes that only appear in the new multimodal ophthalmic basic data and the key attributes that only appear in the comparison data as abnormal key attributes; identify the key attributes that appear in both the new multimodal ophthalmic basic data and the comparison data as common key attributes;

[0025] For the abnormal key attributes, determine the weights of each abnormal key attribute, and form abnormal triples with the abnormal key attributes whose weights are greater than the preset abnormal weight threshold. Among them, any abnormal triple is <identifier of the data to which it belongs, abnormal key attribute, value of the abnormal key attribute>;

[0026] For the common key attributes, determine the first key attribute value of each common key attribute in the new multimodal ophthalmic basic data and the second key attribute value in the comparison data; form abnormal quadruples with the common key attributes whose degree of change between the first key attribute value and the second key attribute value meets the preset abnormal degree. Among them, any abnormal quadruple is <common key attribute, corresponding first key attribute value, corresponding second key attribute value, abnormal trend>;

[0027] Form the description of the new multimodal ophthalmic basic data with the abnormal triples and abnormal quadruples

[0028] Optionally, determine the weights of each abnormal key attribute, including:

[0029] For any abnormal key attribute u, determine its weight through the following steps:

[0030] Determine the theoretical correlation degree between u and theoretical correlation degree

[0031] Among all the multimodal ophthalmic basic data with the diagnosed disease being determine the probability of u appearing where, is the number of occurrences of u in all the multimodal ophthalmic basic data of all patients with the diagnosed disease being and is the total number of all the multimodal ophthalmic basic data of all patients with the diagnosed disease being ;

[0032] Determine the comparison patients according to all the abstracts of the patients;

[0033] Among all the multimodal ophthalmic basic data of the comparison patients, the diagnosed disease is and the probability of u appearing where, is the number of cases with the diagnosed disease being in all the multimodal ophthalmic basic data of the comparison patients, To compare the total number of all multimodal ophthalmic basic data of a patient, Among all the multimodal ophthalmic basic data of the patient to be compared, the diagnosed disease is And the number of occurrences of u;

[0034] Determine the degree of patient association between u and Between

[0035] Determine the weight of any abnormal key attribute u as Where max{} is the maximum value function.

[0036] Optionally, after determining the first key attribute value of each common key attribute in the new multimodal ophthalmic basic data and the second key attribute value in the comparison data, it further includes:

[0037] For any common key attribute v, if its first key attribute value or second key attribute value is not within the standard value range of v, then determine that the change degree between the first key attribute value and the second key attribute value of v meets the preset abnormal degree;

[0038] If both the first key attribute value and the second key attribute value of v are within the standard value range of v, then determine the third key attribute value of v in each associated data of the non-comparison data; determine the first difference between the first key attribute value and each third key attribute value; determine the second difference between the first key attribute value and the second key attribute value; determine the first standard deviation of all first differences; determine the second standard deviation of all first differences and second differences; if the ratio of the first standard deviation to the second standard deviation is less than the preset standard deviation ratio threshold, then determine that the change degree between the first key attribute value and the second key attribute value of v meets the preset abnormal degree; if the ratio of the first standard deviation to the second standard deviation is not less than the preset standard deviation ratio threshold, but |second difference - mean of first differences| / second difference is greater than the preset difference ratio threshold, then determine that the change degree between the first key attribute value and the second key attribute value of v meets the preset abnormal degree.

[0039] Optionally, the auxiliary diagnostic decision in the pre-hospital stage includes: performing preoperative assessment, providing diversified information introduction, health education, psychological support and preoperative preparation; among them, the information introduction includes: ward environment, disease knowledge, knowledge related to stem cell transplantation and gene therapy, and introduction of pre-treatment preparation work;

[0040] The auxiliary diagnostic decision in the in-hospital stage includes: performing nursing and management during the perioperative period of the patient, paying attention to the patient's vital signs and surgical progress, observing the changes in the patient's condition, performing condition observation, complication monitoring, medication management, pain management, diet guidance, psychological counseling, and evaluating the patient's readiness for discharge;

[0041] The auxiliary diagnostic decisions in the post - hospital stage include: conducting diversified follow - up management of patients, educating relevant knowledge, understanding the changes in patients' conditions and rehabilitation status, answering patients' consultations, and providing guidance and assistance.

[0042] Optionally, the nursing follow - up plan in the pre - hospital stage includes: conducting a baseline assessment before the patient undergoes stem cell transplantation and gene therapy surgery;

[0043] The nursing follow - up plan in the in - hospital stage includes: conducting follow - up daily to evaluate the patient's readiness for discharge;

[0044] The nursing follow - up plan in the post - hospital stage includes: if the follow - up type is short - term post - operative follow - up, evaluating the incidence of surgical complications and the patient's recovery; if the follow - up type is long - term post - operative follow - up, evaluating the long - term effects of stem cell transplantation and gene therapy surgery and the changes in the patient's quality of life; among them, if the follow - up date does not exceed three months after the patient's surgery, the follow - up type is determined as short - term post - operative follow - up, and if the follow - up date exceeds three months after the patient's surgery, the follow - up type is determined as long - term post - operative follow - up.

[0045] Optionally, the follow - up content during follow - up includes at least: vision assessment, complication assessment, quality - of - life assessment, and psychological state assessment;

[0046] Among them, the evaluation indicators for quality - of - life assessment include: overall visual condition, eye pain condition, near - distance work condition, far - distance work condition, social ability, mental health status, social role limitation, independence, color vision, and peripheral vision.

[0047] Optionally, the auxiliary information of any multimodal ophthalmic basic data j of any patient i includes: generation time Disease course stage Abstract Auxiliary diseases Description

[0048] Determine the follow - up level, including:

[0049] The follow - up level of any patient i is determined through the following steps:

[0050] Determine the multimodal ophthalmic basic data with the generation time closest to the current time as the target data;

[0051] Determine the current disease course stage as the disease course stage of the target data;

[0052] If the current disease course stage is the in - hospital stage, determine the follow - up level of patient i as the highest level;

[0053] If the current disease course stage is the post - hospital stage, determine the target generation time, and determine the follow - up type according to the target generation time; if the follow - up type is short - term postoperative follow - up, determine that the follow - up level of patient i is the highest level; if the follow - up type is long - term postoperative follow - up, determine that the follow - up level of patient i is the low level; where the target generation time is the generation time of the multimodal ophthalmic basic data that is closest to the current time and whose disease course stage is the in - hospital stage.

[0054] If the current disease course stage is the pre - hospital stage, determine the follow - up level of patient i according to the summary, auxiliary diseases, and description of the target data.

[0055] Optionally, determining the follow - up level of patient i according to the summary, auxiliary diseases, and description of the target data includes:

[0056] Estimate the operation time according to the summary, auxiliary diseases, and description of the target data;

[0057] If the estimated operation time is greater than the preset duration threshold, determine that the follow - up level of patient i is the lowest level;

[0058] If the estimated operation time is not greater than the preset duration threshold, determine the preoperative examination completion degree according to the summary and auxiliary diseases of each multimodal ophthalmic basic data j of patient i; if the completion degree is greater than the preset maximum completion degree threshold, determine that the follow - up level of patient i is the high level; if the completion degree is not greater than the preset maximum completion degree threshold, determine that the follow - up level of patient i is the medium level.

[0059] (III) Beneficial Effects

[0060] The present invention relates to a multimodal ophthalmic assisted diagnosis and nursing follow - up system, which includes: a multimodal ophthalmic basic data collection module, a full - course assisted diagnosis module, a full - course nursing follow - up module, and an output module; among them, the multimodal ophthalmic basic data collection module is used to obtain the patient identifier when the patient first consults a doctor, determine the auxiliary information of the new multimodal ophthalmic basic data after obtaining the new multimodal ophthalmic basic data of the patient at each disease course stage according to the patient identifier, and store the new multimodal ophthalmic basic data and the auxiliary information; the full - course assisted diagnosis module is used to determine the assisted diagnosis decision according to the multimodal ophthalmic basic data and the auxiliary information; the full - course nursing follow - up module is used to determine the follow - up level according to the multimodal ophthalmic basic data and the auxiliary information, and generate a nursing follow - up plan; the output module is used to output the nursing follow - up plan and / or the assisted diagnosis decision according to the follow - up level. The multimodal ophthalmic assisted diagnosis and nursing follow - up system of the present invention can realize the assisted diagnosis and nursing follow - up in the full - course stage, and ensure the accuracy of assistance at each disease course stage. Description of the Drawings

[0061] Figure 1Schematic diagram of a multimodal ophthalmic assisted diagnosis, nursing and follow-up system provided by an embodiment of the present application. Detailed implementation manners

[0062] To better explain the present invention for easy understanding, the present invention will be described in detail below with reference to the accompanying drawings through specific implementation manners.

[0063] The current ophthalmic assisted diagnosis, nursing and follow-up system only targets patients after stem cell transplantation and gene therapy surgeries, such as observing the operated eye, providing medication guidance, performing life care, preventing complications, and conducting follow-up, etc., to ensure that the basic needs of patients are met. The patients in the current ophthalmic assisted diagnosis, nursing and follow-up system are only in-hospital and post-discharge patients, and there may be insufficient information about patients before hospitalization. However, the pre-hospital information will also affect the assisted diagnosis results during and after hospitalization, which makes the assisted accuracy of the current ophthalmic assisted diagnosis, nursing and follow-up system poor.

[0064] To solve this problem, an embodiment of the present invention relates to a multimodal ophthalmic assisted diagnosis, nursing and follow-up system, which includes: a multimodal ophthalmic basic data collection module, a full-course assisted diagnosis module, a full-course nursing and follow-up module, and an output module; wherein, the multimodal ophthalmic basic data collection module is used to obtain a patient identifier when a patient first consults, determine the auxiliary information of the new multimodal ophthalmic basic data after obtaining the new multimodal ophthalmic basic data of the patient at each disease course stage according to the patient identifier, and store the new multimodal ophthalmic basic data and the auxiliary information; the full-course assisted diagnosis module is used to determine an assisted diagnosis decision according to the multimodal ophthalmic basic data and the auxiliary information; the full-course nursing and follow-up module is used to determine a follow-up level according to the multimodal ophthalmic basic data and the auxiliary information and generate a nursing and follow-up plan; the output module is used to output the nursing and follow-up plan and / or the assisted diagnosis decision according to the follow-up level. The multimodal ophthalmic assisted diagnosis, nursing and follow-up system involved in the embodiment of the present invention can realize the assisted diagnosis, nursing and follow-up in the full-course stage and ensure the assisted accuracy at each disease course stage.

[0065] See Figure 1 , this embodiment provides a multimodal ophthalmic assisted diagnosis, nursing and follow-up system, which includes: a multimodal ophthalmic basic data collection module, a full-course assisted diagnosis module, a full-course nursing and follow-up module, and an output module.

[0066] 1. Multimodal ophthalmic basic data collection module

[0067] A multi-modal ophthalmic basic data collection module is used to obtain a patient identifier when a patient first visits a doctor. After obtaining new multi-modal ophthalmic basic data of the patient at each disease stage according to the patient identifier, it determines auxiliary information of the new multi-modal ophthalmic basic data and stores the new multi-modal ophthalmic basic data and the auxiliary information.

[0068] Among them, the disease stage is the pre-hospital stage, the in-hospital stage, or the post-hospital stage.

[0069] In specific implementation, whenever a new patient comes for a consultation, the multi-modal ophthalmic assisted diagnosis, nursing, and follow-up system provided in this embodiment will assign an identity identifier to the patient, that is, the patient identifier, and obtain the basic information of the patient, such as name, age, gender, contact information, hospital admission number, diagnosis, medical history, previous surgical history, family history, etc. The basic information is used as the first piece of multi-modal ophthalmic basic data of the user and is collected by the multi-modal ophthalmic basic data collection module. Subsequently, every time the patient has new multi-modal ophthalmic basic data (such as a diagnosis form, a vision examination form, a fundus B-ultrasound image, a fundus B-ultrasound report, an electrocardiogram, an examination video, an interrogation voice, etc.), it will be collected by the multi-modal ophthalmic basic data collection module.

[0070] In addition, the modalities of the ophthalmic basic data include: text modality (such as a diagnosis form, a vision examination form, a fundus B-ultrasound report, etc.), image modality (such as a fundus B-ultrasound image, an electrocardiogram, etc.), video modality (such as an examination video, etc.), and audio modality (such as an interrogation voice, etc.).

[0071] Whenever the multi-modal ophthalmic basic data collection module obtains a new piece of multi-modal ophthalmic basic data, it will process it to obtain the auxiliary information of the data, and then store the data and the auxiliary information. In this way, the multi-modal ophthalmic basic data collection module will store all the collected multi-modal ophthalmic basic data and the auxiliary information corresponding to the data.

[0072] Among them, the auxiliary information is used to characterize the core content of the ophthalmic basic data. Through the auxiliary information, the situation of the ophthalmic basic data can be generally understood. For example, if there is no need to understand in detail, the auxiliary information can be used. If detailed understanding is required, then the multi-modal ophthalmic basic data can be viewed. Since the amount of data of the auxiliary information is much smaller than that of the multi-modal ophthalmic basic data, processing through the auxiliary information can significantly improve the processing speed while ensuring the accuracy of processing.

[0073] The auxiliary information includes but is not limited to: the generation time of the ophthalmic basic data, the disease stage, the abstract, the auxiliary diseases, and the description.

[0074] For any new piece of multi-modal ophthalmic basic data (such as ophthalmic basic data j), the determination process of its auxiliary information is as follows:

[0075] 101. Determine the generation time of the new multimodal ophthalmic basic data

[0076] Where i is the patient identifier and j is the identifier of the patient's ophthalmic basic data.

[0077] Taking the new multimodal ophthalmic basic data (i.e., ophthalmic basic data j) as the diagnosis certificate of the new text modality as an example, after the doctor completes the diagnosis certificate and confirms the upload, the upload completion time is the generation time of the ophthalmic basic data j

[0078] 102. Determine the disease course stage of the new multimodal ophthalmic basic data

[0079] The disease course stage can be determined from the system that uploads the multimodal ophthalmic basic data. During the patient consultation, the outpatient process will be carried out. When the outpatient doctor deems hospitalization necessary, the hospitalization procedures will be handled. All subsequent treatments will be prescribed by the inpatient doctor. When it is confirmed that the patient can be discharged, the discharge procedures will be handled. The treatments for reexamination will again be prescribed by the outpatient doctor, but the doctor will mark that this outpatient visit is a post-hospitalization reexamination.

[0080] The systems used for outpatient and inpatient services are different. Therefore, for all the data of diagnoses and examinations obtained from the inpatient system The disease course stage is the in-hospital stage. For the data of diagnoses and tests obtained from the outpatient system, if the doctor marks a post-hospitalization reexamination, then determine its disease course stage As the post-hospital stage. If the doctor does not mark a post-hospitalization reexamination, then determine its disease course stage As the pre-hospital stage.

[0081] 103. Determine the abstract and auxiliary diseases of the new multimodal ophthalmic basic data according to the modality of the new multimodal ophthalmic basic data And auxiliary diseases

[0082] 1) Abstract It is obtained through the existing AI model. For example, for the ophthalmic basic data in audio modality, through the existing speech recognition model, it is converted into text. Then, through the existing AI model, the semantics in the text are recognized to obtain the abstract of the text. For the ophthalmic basic data in text modality, directly through the existing AI model, its semantics are recognized to obtain the abstract. If it is the ophthalmic basic data in image modality, since the image consists of multiple frames of images, for each frame of image, the content in each frame of image can be recognized through the existing content recognition model, and then through the existing AI model, the content of all frames of images is integrated to obtain the abstract of the video. If it is the ophthalmic basic data in image modality, the content in each frame of image can be recognized through the existing content recognition model to obtain the abstract of the image.

[0083] summary It can represent the core content of new multimodal ophthalmic basic data (such as ophthalmic basic data j).

[0084] 2) Auxiliary diseases It is the possible disease of the new multimodal basic ophthalmology data (such as basic ophthalmology data j). The corresponding doctor will mark it in the diagnosis certificate and report (such as written in the diagnosis). If the disease is marked in the new multimodal basic ophthalmology data (such as basic ophthalmology data j), the auxiliary disease If the new multimodal ophthalmological basic data (such as ophthalmological basic data j) does not have the disease marked, the disease marked by the doctor when prescribing the examination is obtained and determined as the auxiliary disease. If none of the marked conditions are present, then the auxiliary condition here Is empty.

[0085] 104, according to the abstract Relevant data are determined from the patient's stored multimodal basic ophthalmic data.

[0086] The patient here is the patient for which the new multimodal ophthalmological basic data (such as ophthalmological basic data j) is generated, that is, in step 104 , associated data will be determined from the multimodal ophthalmological basic data stored for the same patient.

[0087] This step can be implemented by existing solutions. For example, determine the summary of the patient's stored multimodal basic ophthalmological data (for the convenience of description, this summary is named as the stored data summary), determine The similarity between the stored data summaries is determined, and the stored multimodal basic ophthalmological data of the patient whose similarity is greater than a preset similarity threshold is determined as the associated data.

[0088] Because the abstract The core content of the new multimodal ophthalmological basic data (such as ophthalmological basic data j) is represented. Therefore, by obtaining the associated data through the summary, the content relevance of the associated data and the new multimodal ophthalmological basic data (such as ophthalmological basic data j) can be guaranteed, ensuring the comparability between the associated data and the new multimodal ophthalmological basic data (such as ophthalmological basic data j).

[0089] In addition, the similarity threshold can be determined by existing methods, such as the similarity threshold is a pre-set empirical value, determined according to the accuracy of multimodal ophthalmology-assisted diagnosis, nursing and follow-up. The larger the value, the higher the accuracy of the associated data, and the higher the accuracy of multimodal ophthalmology-assisted diagnosis, nursing and follow-up. For example, the similarity threshold is obtained by a trained big data model. This embodiment does not limit the method for determining the similarity threshold.

[0090] 105. Extract the key attribute values from the new multimodal ophthalmic basic data and associated data.

[0091] The key attributes of each multimodal ophthalmic basic data can be the same or different, which are determined according to the content of the multimodal ophthalmic basic data. Even for the same key attribute, the key attribute values in different multimodal ophthalmic basic data can be the same or different.

[0092] This step can be implemented based on the maintained key attribute database. All key attributes are stored in the key attribute database, and the values of the key attributes that appear in the ophthalmic basic data j are obtained from the key attribute database.

[0093] 106. Form a description of the new multimodal ophthalmic basic data based on the key attribute values in the new multimodal ophthalmic basic data and associated data.

[0094] Description Includes a description of the important information of the new multimodal ophthalmic basic data (i.e., ophthalmic basic data j). Through the description It is also possible to know the data information of the new multimodal ophthalmic basic data (i.e., ophthalmic basic data j).

[0095] For the same multimodal ophthalmic basic data, including the abstract and the description Both can reflect the core information of the multimodal ophthalmic basic data. The difference between the two is that the abstract objectively reflects the content of the multimodal ophthalmic basic data from the dimension of the content itself. The description reflects the content that needs to be concerned in the multimodal ophthalmic basic data from the dimension of the content meaning.

[0096] For example, for a vision of 4.6, the abstract only reflects the vision itself (e.g., reflects 4.6), and the description reflects the content that needs to be concerned (e.g., if the previous vision was 4.4 and the current vision is 4.6, then the description reflects the improvement in vision).

[0097] The specific implementation process of step 106 is as follows:

[0098] 106-1. Determine the comparison data as the associated data with the most recent production time.

[0099] ​Among them, the associated data is obtained in step 104. The associated data is the data similar to the new multimodal ophthalmic basic data (such as ophthalmic basic data j) among all the data of the same patient. Among all the associated data, the latest associated data (i.e., the associated data with the production time closest to the closest associated data) is determined as the comparison data.

[0100] 106-2, determine the key attributes that only appear in the new multimodal ophthalmic basic data and the key attributes that only appear in the comparison data as abnormal key attributes. Determine the key attributes that appear in both the new multimodal ophthalmic basic data and the comparison data as common key attributes.

[0101] The comparison data and the new multimodal ophthalmic basic data (such as ophthalmic basic data j) are two similar data of the same user. Logically, the key attributes in the two data should be the same, but the values of the same key attributes may be the same or different. If there are different key attributes in the two data, it means that this attribute is a newly added attribute or an attribute that no longer appears. These attributes need special attention, so they are named abnormal key attributes. And the key attributes that appear in both data are normal key attributes, which are named common key attributes.

[0102] 106-3, for abnormal key attributes, determine the weight of each abnormal key attribute, and form abnormal triples with the abnormal key attributes whose weights are greater than the preset abnormal weight threshold.

[0103] Among them, any abnormal triple is <the identifier of the data to which it belongs, the abnormal key attribute, the value of the abnormal key attribute>.

[0104] For abnormal key attributes, it is possible that they have little impact on the current disease. For example, sudden sinus arrhythmia appears in the electrocardiogram, but it has little impact on ophthalmic diseases and does not need much attention, so it does not need to appear in the description If the doctor wants to pay attention to this abnormal key attribute (such as sinus rhythm), he can view the new multimodal ophthalmic basic data. Therefore, this abnormal key attribute does not affect the ophthalmic auxiliary diagnosis, nursing and follow-up work of the patient. It is also possible that it has a greater impact on the current disease. At this time, this abnormal key attribute needs to be concerned and needs to appear in the description in.

[0105] Therefore, for abnormal key attributes, the weight of each abnormal key attribute will be determined. The weight reflects the degree of influence of this abnormal key attribute on the current disease. The abnormal key attributes whose weights are greater than the preset abnormal weight threshold are determined as abnormal attributes that need attention, forming abnormal triples, and the abnormal triples are put into the description Among them, the abnormal key attributes with weights not greater than the preset abnormal weight threshold are determined as abnormal attributes that do not need attention and will not appear in the description Among them.

[0106] Among them, for any abnormal key attribute u, its weight is determined through the following steps:

[0107] 201. Determine the theoretical correlation degree between u and theoretical correlation degree

[0108] Among them, is the auxiliary disease obtained in step 103.

[0109] This step can be obtained through existing models. For example, maintain a disease description library that describes the attributes of each disease and the degree of influence of each attribute on the disease. For example, the attributes of cataracts include: vision (0.2), degree of blurred vision (0.2), lens structure (0.2), etc. The numbers in parentheses are the degrees of influence. The content in the disease description library is determined by relevant doctors based on knowledge such as textbooks and papers, making the content in the disease description library highly professional and accurate.

[0110] Therefore, in step 201, the degree of influence of the u attribute under the disease can be read from the disease description library, and this degree of influence is the degree of influence of the u attribute under the disease, and this degree of influence is If there is no u attribute under the disease in the disease description library, it means there is no influence. It means there is no influence.

[0111] 202. Among all the multimodal ophthalmic basic data with the diagnosed disease being determine the probability of u appearing

[0112] Among them, is the number of occurrences of u in all the multimodal ophthalmic basic data of all patients with the diagnosed disease being the number of occurrences of u in all the multimodal ophthalmic basic data of all patients with the diagnosed disease being is the number of occurrences of u in all the multimodal ophthalmic basic data of all patients with the diagnosed disease being the total number of all the multimodal ophthalmic basic data of all patients with the diagnosed disease being

[0113] In step 202, from all the multimodal ophthalmic basic data of all patients collected by the multimodal ophthalmic basic data collection module, obtain the multimodal ophthalmic basic data with the diagnosed disease being The number of such data is Then, from the multimodal ophthalmic basic data with the diagnosed disease being obtain the multimodal ophthalmic basic data in which u appears. The number of such data is This represents that in clinical practice, patients with The probability of u appearing in the multimodal ophthalmological basic data. The larger the value, the more important u is in clinical practice. The more important u is, The greater the value.

[0114] 203, based on all the summaries of the patients, the comparison patients are determined.

[0115] The implementation method of this step can be implemented by existing methods. For example, the summaries of all multimodal basic ophthalmic data of a patient (such as patient i) are integrated to obtain an overall summary. The summaries of all multimodal basic ophthalmic data of all other patients are integrated to obtain overall summaries of other patients. The similarity between the overall summary of patient i and the overall summary of each other patient (for the convenience of description, this summary is named other overall summaries) is determined, and the patients to whom the other overall summaries whose similarity is greater than a preset similarity threshold belong are determined as comparison patients.

[0116] Because the overall summary represents the overall data content of the user, obtaining the comparison patient through the overall summary can ensure the degree of correlation between the data of the comparison patient and patient i, thereby ensuring the comparability of the comparison patient and patient i.

[0117] It should be noted that the similarity threshold here may be the same as or different from the similarity threshold in step 104 , and this embodiment does not limit the numerical relationship between the two, nor does it limit the method for determining the similarity threshold here.

[0118] 204. In comparing all the multimodal ophthalmic basic data of the patient, the confirmed disease is And the probability of u appearing

[0119] in, To compare the patient's multimodal ophthalmological basic data, the confirmed disease is The number of is the total number of all multimodal basic ophthalmic data of the patients compared, To compare the patient's multimodal ophthalmological basic data, the confirmed disease is And the number of u appears.

[0120] In step 204, all multimodal ophthalmological basic data of all patients collected by the multimodal ophthalmological basic data collection module are obtained to obtain all multimodal ophthalmological basic data of the patient to be compared. The amount of data is Then, by comparing all the multimodal ophthalmic basic data of the patient, the confirmed disease is obtained. The number of multimodal basic ophthalmological data is Then, the patient's confirmed disease is Among all the multimodal basic ophthalmology data, obtain the multimodal basic ophthalmology data with u appearing, the number is

[0121] Characterizes similar users who have probability. Characterizes similar and The probability of u appearing among users.

[0122] From the perspective of user personalization, similar and Under the condition of , the probability of u appearing in the multimodal ophthalmology basic data. This probability is a conditional probability. The larger the value, the more similar users suffer from The greater the value, the greater the possibility, indicating that u is more likely to appear in similar users. The more important u is, The greater the value.

[0123] 205, determine u and The degree of patient association

[0124] Patient Relevance It is a combination of clinical and user-personalized dimensions that characterizes u and The degree of correlation between them.

[0125] 206, determine the weight of any abnormal key attribute u as

[0126] Among them, max{} is the minimum value function

[0127] The theoretical correlation Relevance to patients The maximum value in is determined as u and The ultimate degree of correlation between .

[0128] If the weight of an abnormal key attribute is greater than the preset abnormal weight threshold, that is, the maximum value of the theoretical correlation degree of the abnormal key attribute and the patient correlation degree (that is, the maximum correlation degree of the abnormal key attribute) is greater than the preset abnormal weight threshold, it is considered that the abnormal key attribute needs to be paid attention to, and an abnormal triple is formed. The abnormal triple is placed in the description middle.

[0129] For the need in the description The abnormal key attributes reflected in (i.e., the abnormal key attributes whose weight is greater than the preset abnormal weight threshold) are described in The contents reflected in it are: in which data the abnormal key attribute appears (that is, reflected by the identifier of the data to which it belongs in the abnormal triplet), what the abnormal key attribute is (that is, reflected by the abnormal key attribute in the abnormal triplet), and what the value of the abnormal key attribute is (that is, reflected by the value of the abnormal key attribute in the abnormal triplet).

[0130] In addition, the abnormal weight threshold can be determined by existing methods, such as the abnormal weight threshold is a pre-set empirical value, which is determined according to the accuracy of multimodal ophthalmology-assisted diagnosis, nursing and follow-up. The larger the value, the higher the accuracy of the abnormal triplet formed, and the higher the accuracy of multimodal ophthalmology-assisted diagnosis, nursing and follow-up. For another example, the abnormal weight threshold is obtained by a trained big data model. This embodiment does not limit the method for determining the abnormal weight threshold.

[0131] 106-4, for common key attributes, determine the first key attribute value of each common key attribute in the new multimodal ophthalmological basic data and the second key attribute value in the comparison data. Common key attributes whose degree of change between the first key attribute value and the second key attribute value meets the preset abnormal degree are formed into an abnormal quadruple.

[0132] Among them, any abnormal quadruple is <common key attribute, corresponding first key attribute value, corresponding second key attribute value, abnormal trend>.

[0133] For common key attributes, their appearance is normal, but their specific values ​​may be normal or abnormal. For normal values, there is no need to pay too much attention to them and they do not need to appear in the description. For abnormal values, those that require attention should appear in the description middle.

[0134] Therefore, in 106-4, the first key attribute value of the common key attribute in the new multimodal ophthalmology basic data (such as denoted as ) and the second key attribute value in the comparison data (such as ). Where v is the identifier of the common key attribute.

[0135] if and If the degree of change does not meet the preset abnormality level, the value of the common key attribute v is considered normal and does not need to be paid too much attention, so it does not need to appear in the description If and If the degree of change of meets the preset abnormal degree, the value of the common key attribute x is considered abnormal and needs attention. Therefore, an abnormal quadruple of the common key attribute v is formed and the abnormal quadruple is put into the description middle.

[0136] For any common key attribute v, the process of determining whether the degree of change between the first key attribute value and the second key attribute value meets the preset abnormality degree is as follows:

[0137] 1) If the first key attribute value or the second key attribute value is not within the standard value interval of v, it is determined that the degree of change of the first key attribute value and the second key attribute value of v meets the preset abnormality degree.

[0138] That is to say, and If there is a value in that exceeds the standard value range of v, the value is abnormal, and v needs to be paid attention to. Therefore, it is determined that the degree of change between the first key attribute value and the second key attribute value of v meets the preset abnormal degree.

[0139] Among them, the standard value range is the existing standard value range, such as the standard value range of intraocular pressure is 10~21mmHg.

[0140] 2) If the first key attribute value and the second key attribute value of v are both within the standard value range of v, the following steps are used to determine whether the preset abnormality level is met.

[0141] (1) Determine the third key attribute value of v in each associated data of the non-matching data.

[0142] In step 106-1, a nearest one is selected from the associated data as comparison data, and the other comparison data are the associated data of the non-comparison data. Here, the value of the common key attribute v in each associated data of the non-comparison data is determined, and each value is the third key attribute value.

[0143] (2) Determine a first difference between the first key attribute value and each third key attribute value.

[0144] For example, for any third key attribute value Wherein, y is the third key attribute value identifier.

[0145] First Difference

[0146] The first difference represents the change between the first key attribute value and each third key attribute value, and the difference may be positive (ie, the value increases) or negative (ie, the value decreases).

[0147] (3) Determine a second difference between the first key attribute value and the second key attribute value.

[0148] Second difference

[0149] The second difference represents the change between the first key attribute value and the second key attribute value, and the difference may be positive (ie, the value increases) or negative (ie, the value decreases).

[0150] (4) Determine the first standard deviation of all first differences.

[0151] The first standard deviation is all The standard deviation is obtained using the existing calculation formula.

[0152] The first standard deviation represents the fluctuation of the value of the common key attribute v in the new multimodal ophthalmic basic data (i.e., the first key attribute value) and the value of the common key attribute v in each associated data of the non-compared data (i.e., each third key attribute value). The larger the first standard deviation, the greater the volatility of the first key attribute value and the third key attribute value, that is, the difference between the value of the common key attribute v in the new multimodal ophthalmic basic data and the associated data of each non-compared data is unstable, sometimes large and sometimes small.

[0153] (5) Determine the second standard deviation of all first differences and second differences.

[0154] All first differences are the differences between the value of the common key attribute v in the new multimodal ophthalmology basic data (i.e., the first key attribute value) and the value of the common key attribute v in each associated data of the non-comparison data (i.e., each third key attribute value). The second differences are the differences between the value of the common key attribute v in the new multimodal ophthalmology basic data (i.e., the first key attribute value) and the common key attribute v

[0155] The difference between the value (i.e., the second key attribute value) in the comparison data. All first differences and second differences constitute the difference between the value of the common key attribute v in the new multimodal ophthalmic basic data (i.e., the first key attribute value) and the value of the common key attribute v in each associated data.

[0156] The second standard deviation is all and The standard deviation is obtained using the existing calculation formula.

[0157] The second standard deviation represents the fluctuation of the difference between the value of the common key attribute v in the new multimodal ophthalmic basic data (i.e., the first key attribute value) and the value of the common key attribute v in each associated data. The larger the second standard deviation, the greater the volatility of the first key attribute value and the third key attribute value and the second key attribute value, that is, the difference between the value of the common key attribute v in the new multimodal ophthalmic basic data and each associated data is unstable, sometimes large and sometimes small.

[0158] (6) If the ratio of the first standard deviation to the second standard deviation is less than a preset standard deviation ratio threshold, it is determined that the degree of change between the first key attribute value and the second key attribute value of v meets the preset abnormality degree.

[0159] The first standard deviation does not include the change in the most recent v value (i.e., the difference between the first key attribute value and the second key attribute value). ) when v in the new multimodal ophthalmological basic data and the changes in the values ​​in each associated data of each non-comparison data. The second standard deviation is the change of the most recent v value (that is, the difference between the first key attribute value and the second key attribute value). ) after adding the value of v in the new multimodal ophthalmological basic data and the change fluctuation of the value in each associated data. The ratio of the first standard deviation to the second standard deviation represents the change of the most recent v value (i.e., adding ) on the overall change of the v value. The larger the ratio of the first standard deviation to the second standard deviation, the more stable the v value is after adding the most recent change in the v value. The smaller the ratio of the first standard deviation to the second standard deviation, the greater the fluctuation of the v value is after adding the most recent change in the v value.

[0160] Therefore, if the ratio of the first standard deviation to the second standard deviation is less than the preset standard deviation ratio threshold, it means that the most recent change in the v value has an abnormal impact on the fluctuation of the v value, and then determines that the degree of change between the first key attribute value and the second key attribute value of v meets the preset abnormality level.

[0161] (7) If the ratio of the first standard deviation to the second standard deviation is not less than the preset standard deviation ratio threshold, but |second difference - mean of the first difference| / second difference is greater than the preset difference ratio threshold, then it is determined that the degree of change between the first key attribute value and the second key attribute value of v meets the preset abnormality degree.

[0162] If the ratio of the first standard deviation to the second standard deviation is not less than the preset standard deviation ratio threshold, it means that the most recent change in the v value has a normal effect on the fluctuation of the v value. This normality can only be said to be normal overall, but it is impossible to judge whether the most recent fluctuation is normal from a microscopic perspective. Therefore, the relationship between |the second difference - the mean of the first difference| / the second difference and the preset difference ratio threshold is further determined.

[0163] |Second difference - average of the first difference| / The second difference indicates the degree of influence of the most recent change in v value. If this degree is greater than the preset difference ratio threshold, it means that judging from the change in the most recent v value alone, the degree of change is large and needs attention. Therefore, it is determined that the degree of change between the first key attribute value and the second key attribute value of v meets the preset abnormality level.

[0164] Among them, the standard deviation ratio threshold can be determined by existing methods. For example, the standard deviation ratio threshold is a pre-set empirical value, which is determined according to the accuracy of multimodal ophthalmology-assisted diagnosis, nursing and follow-up. The larger the value, the more stringent the condition of whether to meet the preset abnormality degree, and the higher the accuracy of multimodal ophthalmology-assisted diagnosis, nursing and follow-up. For another example, the standard deviation ratio threshold is obtained by a trained big data model. This embodiment does not limit the method for determining the standard deviation ratio threshold.

[0165] In addition, for The common key attribute embodied in (i.e., the common key attribute whose degree of change between the first key attribute value and the second key attribute value satisfies the preset abnormal degree) is described in The contents reflected in it are: what is the common key attribute (i.e. reflected by the common key attribute in the abnormal quadruple), what is the value of the abnormal key attribute in the new multimodal ophthalmic basic data (i.e. reflected by the corresponding first key attribute value in the abnormal quadruple), what is the value of the abnormal key attribute in the comparison data (i.e. reflected by the corresponding second key attribute value in the abnormal quadruple), and the overall changing trend of the common key attribute (i.e. reflected by the abnormal trend in the abnormal quadruple).

[0166] The abnormal trend can be obtained by evaluating the first key attribute value, the second key attribute value and all the third key attribute values ​​using an existing trend evaluation scheme (such as an existing trend evaluation method). The abnormal trend characterizes the change trend of the value of the common key attribute in each multi-modal basic ophthalmological data.

[0167] 106-5, Description of new multimodal basic ophthalmological data formed by abnormal triples and abnormal quadruples

[0168] 107, will and Forming new multimodal auxiliary information of basic ophthalmic data.

[0169] 2. Auxiliary diagnosis module for the entire course of disease

[0170] The auxiliary diagnosis module for the entire course of the disease is used to determine auxiliary diagnosis decisions based on the multimodal basic ophthalmological data and auxiliary information stored in the multimodal basic ophthalmological data collection module.

[0171] The auxiliary diagnosis module for the whole course of the disease can integrate the existing multiple analysis methods, based on the multimodal ophthalmological basic data and auxiliary information stored in the multimodal ophthalmological basic data collection module. For example, the Delphi expert inquiry method is adopted to invite ophthalmological clinical experts and nursing experts to conduct expert inquiries, and form nursing standards for the whole course of the disease before, during and after hospitalization, including the quality standards, safety standards, service standards, health guidelines, etc. of nursing work, to form auxiliary diagnosis decisions and ensure the standardization and standardization of nursing work.

[0172] For example, the Delphi expert inquiry method uses the subject group discussion method to develop a preliminary draft of the full-course nursing model for patients with blinding eye diseases in the research ward based on the data collected in the early stage, conducts expert consultation with ophthalmic clinical experts and nursing experts, and forms a full-course nursing plan before, during and after hospital.

[0173] For example, the auxiliary diagnosis decision content is:

[0174] ●The auxiliary diagnosis module of the whole course of disease determines the auxiliary diagnosis decision in the pre-hospital stage, including:

[0175] Conduct preoperative assessment and provide diversified information, health education, psychological support and preoperative preparation.

[0176] The information introduced includes: ward environment, disease knowledge, knowledge related to stem cell transplantation and gene therapy, and introduction to pre-treatment preparations.

[0177] In specific practice, the auxiliary diagnosis decision-making in the pre-hospital stage can be: preoperative evaluation, diversified health education, psychological support and preoperative preparation, etc., to ensure that patients can successfully receive stem cell transplantation and gene therapy. Detailed introduction to the research ward environment, disease knowledge, knowledge related to stem cell transplantation and gene therapy, and pre-treatment preparation.

[0178] ●The auxiliary diagnosis module of the whole course of disease determines the auxiliary diagnosis decision in the hospital stage, including:

[0179] Provide perioperative care and management for patients, pay attention to patients' vital signs and surgical progress, observe changes in patients' conditions, conduct condition observation, complication monitoring, medication management, pain management, dietary guidance, psychological counseling, and assess patients' readiness for discharge.

[0180] In specific practice, auxiliary diagnosis decisions in the hospital stage can implement the concept of accelerated recovery, help patients recover quickly, and accurately implement perioperative care and management of patients. Pay close attention to the patient's vital signs and surgical progress. Closely observe changes in the patient's condition, conduct condition observation, complication monitoring, medication management, pain management, diet guidance, psychological counseling, etc. to promote patient recovery. Assess the patient's readiness for discharge before discharge and provide guidance based on patient needs.

[0181] ● The auxiliary diagnosis module of the whole course of disease determines the auxiliary diagnosis decision in the post-hospital stage, including:

[0182] Carry out diversified follow-up management of patients, disseminate relevant knowledge, understand the changes in patients' conditions and recovery status, respond to patient consultations, and provide guidance and assistance.

[0183] In practice, auxiliary diagnosis and decision-making in the post-hospital stage can be carried out through a variety of methods such as telephone, in-hospital heals system, online and offline nursing consultation clinics, etc. Follow-up management of patients, use the heals system to push disease education knowledge, and send follow-up questionnaires regularly. If patients encounter disease problems after surgery, they can use the nursing clinic for consultation to understand the patient's condition changes and recovery status, and provide necessary guidance and help.

[0184] The auxiliary diagnosis decision determined by the auxiliary diagnosis module of the whole course of illness can refine the nursing plan of the whole course of illness into a specific nursing process, clarify the nursing focus, nursing measures and nursing time of each stage, and ensure the orderly progress of nursing work. At the same time, the auxiliary diagnosis decision also includes the nursing standards of the whole course of illness nursing model, including the quality standards, safety standards, service standards, etc. of nursing work, to ensure the standardization and standardization of nursing work.

[0185] 3. Nursing follow-up module for the entire course of illness

[0186] The whole-course nursing follow-up module is used to determine the follow-up level and generate a nursing follow-up plan based on the multimodal basic ophthalmological data and auxiliary information stored in the multimodal basic ophthalmological data collection module.

[0187] The nursing follow-up module for the whole course of illness can integrate the existing multiple analysis methods and generate a nursing follow-up plan based on the multimodal basic ophthalmology data and auxiliary information stored in the multimodal basic ophthalmology data collection module. For example, a professional nursing team provides a nursing follow-up plan for the whole course of illness for patients in accordance with the full course of illness nursing model. This nursing follow-up plan can explore a new nursing model for the whole course of illness in a research ward with ophthalmology characteristics by evaluating the visual acuity, complication rate, quality of life, and psychological status indicators of patients with irreversible blinding eye diseases.

[0188] For example, the nursing follow-up plan in the pre-hospital stage includes: baseline assessment before patients undergo stem cell transplantation and gene therapy surgery. For example, baseline assessment before patients undergo stem cell transplantation and gene therapy surgery, including vision, quality of life and psychological status.

[0189] The nursing follow-up plan during the in-hospital stage includes: daily follow-up to assess the patient's readiness for discharge.

[0190] The nursing follow-up plan in the post-hospital stage includes: if the follow-up type is short-term follow-up after surgery, the incidence of surgical complications and the patient's recovery will be evaluated (such as follow-up at 1 week, 1 month, and 3 months after surgery to evaluate the incidence of surgical complications and the patient's recovery). If the follow-up type is long-term follow-up after surgery, the long-term effect of stem cell transplantation and gene therapy surgery and the change in the patient's quality of life will be evaluated (such as long-term follow-up at 6 months, 1 year, and 2 years after surgery to observe the long-term effect of stem cell transplantation and gene therapy surgery and the change in the patient's quality of life).

[0191] Among them, if the follow-up date does not exceed three months after the patient's surgery, the follow-up type is determined to be short-term postoperative follow-up. If the follow-up date exceeds three months after the patient's surgery, the follow-up type is determined to be long-term postoperative follow-up.

[0192] In addition, the follow-up content during the follow-up visit at least includes but is not limited to: vision assessment, complication assessment, quality of life assessment and psychological status assessment.

[0193] Among them, vision assessment includes regularly evaluating the patient's vision changes through a vision test chart, and recording the vision data before, after, and at each follow-up time point. In addition, the current recovery status of the example can be obtained by comparing with the best corrected visual acuity. For example, a vision test is performed at each follow-up time point to record the patient's vision changes.

[0194] The best corrected visual acuity can be measured by the international standard visual acuity chart and converted into standard logarithmic visual acuity (Logarithm of the Minimum Angle of Resolution, LogMAR) for data statistical analysis. The higher the LogMAR value, the worse the visual acuity.

[0195] Complication assessment includes recording complications that occur during the entire course of care, such as infection, rejection, etc. For example, at each follow-up time point, observe and record the complications that occur during the follow-up.

[0196] The evaluation indicators of quality of life assessment include: overall visual condition, eye pain, near work, long-distance work, social ability, mental health status, social role limitations, independence, color vision and peripheral vision, which can be achieved through the vision-related quality of life questionnaire (such as VFQ-25). For example, the vision-related quality of life questionnaire (such as VFQ-25) is used to evaluate the changes in the patient's quality of life after vision improvement (mainly reflecting vision-related quality of life), including overall visual condition, eye pain, near work, long-distance work, social function, mental health status, social role limitations, independence, color vision and peripheral vision. The scoring method is based on the patient's subjective experience assessment, divided into 5 levels, 0 to 4 points, respectively, representing the degree to which the patient can complete this item 0, 25%, 50%, 75% and 100%. The total score ranges from 0 to 100 points. The higher the total score, the better the vision-related quality of life.

[0197] Mental status assessment can be achieved through the Hospital Anxiety and Depression Scale (HADS). HADS is a recognized self-report scale for screening anxiety and depression. It was developed by Zigmond and Snaith in 1983 to assess anxiety and depression in clinical or hospital patients. Due to its established validity and reliability, HADS has been translated into multiple languages ​​for use around the world. HADS consists of an anxiety subscale (HADS-A) and a depression subscale (HADS-D), each with 7 items. Each item uses the Liker 4-level scoring system. The total score range of the anxiety subscale and the depression subscale is 0 to 21 points. 7 points is set as the cutoff value for judging whether anxiety or depression is combined. 8 to 10 points can be preliminarily judged as combined with mild anxiety or depression, 11 to 14 points can be preliminarily judged as combined with moderate anxiety or depression, and 15 to 21 points can be preliminarily judged as combined with severe anxiety or depression.

[0198] For example, relevant scales were used to assess patients' vision-related quality of life and psychological status at each follow-up time point.

[0199] In addition, after obtaining the nursing follow-up plan, the follow-up level will be determined. For example, the follow-up level for any patient i is determined by the following steps:

[0200] 301 , determine the multimodal basic ophthalmological data whose generation time is closest to the current time as the target data.

[0201] The target data is the most recent multimodal basic ophthalmological data of any patient i.

[0202] Among them, the auxiliary information of any multimodal basic ophthalmic data j of any patient i includes: generation time Disease stage summary Auxiliary diseases describe

[0203] 302, determining the current disease course stage as the disease course stage of the target data.

[0204] Disease stage in target data That is, the current stage of the disease.

[0205] 303. If the current disease course stage is the in-hospital stage, the follow-up level of patient i is determined to be the highest level.

[0206] 304. If the current stage of the disease course is the post-hospital stage, the target generation time is determined, and the follow-up type is determined according to the target generation time.

[0207] Among them, the target generation time is the generation time of the multimodal basic ophthalmological data that is closest to the current time and the disease course stage is the in-hospital stage (that is, the multimodal basic ophthalmological data generated in the most recent in-hospital stage).

[0208] The type of follow-up can be obtained from the nursing follow-up plan in the post-hospital stage. The type of follow-up is short-term postoperative follow-up or long-term postoperative follow-up.

[0209] If the follow-up type is short-term follow-up after surgery, the follow-up level of patient i is determined to be the highest level.

[0210] If the follow-up type is long-term follow-up after surgery, the follow-up level of patient i is determined to be low level.

[0211] 305, if the current stage of the disease course is the pre-hospital stage, the follow-up level of patient i is determined according to the summary, auxiliary symptoms, and description of the target data.

[0212] For example, the follow-up level of patient i is determined according to the summary, auxiliary symptoms, and description of the target data through the following steps:

[0213] 305-1, estimate the operation time based on the summary, auxiliary symptoms and description of the target data.

[0214] This step can push the summary, auxiliary symptoms, and description of the target data to the relevant doctors, who will estimate the operation time based on the operation schedule and ward conditions and then obtain the operation time.

[0215] 305-2, if the estimated operation time is greater than the preset time threshold, the follow-up level of patient i is determined to be the lowest level.

[0216] The duration threshold can be determined by an existing method, such as a preset empirical value, such as 30 days. If the estimated operation time is greater than the preset duration threshold, it is considered that patient i will not undergo surgery recently and the condition is not very serious, so the follow-up level of patient i is determined to be the lowest level.

[0217] 305-3, if the estimated operation time is not greater than the preset time threshold, then:

[0218] 1) Determine the degree of completion of the preoperative examination based on the summary of each multimodal basic ophthalmic data j of patient i and auxiliary symptoms.

[0219] The completion degree of the preoperative examination can be achieved through a pre-designed completion list to determine whether all the examinations, data, and indicators marked in the completion list have been completed. The quotient of the number of unfinished items in the completion list and the total number of items in the completion list is determined as the completion degree of the preoperative examination.

[0220] 2) If the degree of completion is greater than the preset maximum degree of completion threshold, the follow-up level of patient i is determined to be high.

[0221] The maximum completion threshold can be determined by existing methods, such as a preset experience value, such as 98%. If the completion degree is greater than the preset maximum completion threshold, it is considered that patient i has the conditions for surgery, or the difference between the conditions for surgery and the conditions for surgery is small and can be completed before the surgery date, so the follow-up level of patient i is determined to be high.

[0222] 3) If the degree of completion is not greater than the preset maximum degree of completion threshold, the follow-up level of patient i is determined to be medium.

[0223] If the completion degree is not greater than the preset maximum completion degree threshold, it is considered that patient i is still far from being qualified for surgery and needs a certain amount of time to prepare. Therefore, the follow-up level of patient i is determined to be medium.

[0224] 4. Output module.

[0225] The output module is used to output the nursing follow-up plan generated by the nursing follow-up module of the whole course of illness and / or the auxiliary diagnosis decision obtained by the auxiliary diagnosis module of the whole course of illness according to the follow-up level.

[0226] The output module can output the nursing follow-up plan generated by the nursing follow-up module for the whole course of the disease and / or the auxiliary diagnosis decision obtained by the auxiliary diagnosis module for the whole course of the disease according to the settings of the relevant doctors. If the doctor sets a certain period (such as three days), the nursing follow-up plan for the next three days of nursing follow-up and / or the auxiliary diagnosis decision for the next three days of surgery are output every day.

[0227] When multiple users' follow-up plans and / or auxiliary diagnosis decisions need to be output on the same day, they can be output in descending order of follow-up level. The higher the follow-up level, the more urgent it is, so it needs to be output earlier.

[0228] The multimodal ophthalmological auxiliary diagnosis, nursing and follow-up system provided in this embodiment can implement a full-course nursing model before, during and after hospitalization for patients with irreversible blinding eye diseases undergoing stem cell transplantation and gene therapy, provide personalized, comprehensive and full-course nursing services for patients with irreversible blinding eye diseases, and explore their impact on the patients' quality of life, complications and psychological conditions; at the same time, the multimodal ophthalmological auxiliary diagnosis, nursing and follow-up system provided in this embodiment can provide an efficient and high-quality full-course nursing model, providing a reference and basis for clinical nursing practice.

[0229] The multimodal ophthalmology auxiliary diagnosis and nursing follow-up system provided in this embodiment will cover the entire process of patients before, during and after hospitalization, including preoperative evaluation, intraoperative support, postoperative care and discharge follow-up, providing a highly individualized nursing model that integrates patient resources under limited resources. Provide patients with high-quality nursing throughout the process, strengthen their disease management awareness and compliance with medical advice, promote patients' maximum rehabilitation and improve their quality of life, and ultimately achieve the goal of improving patients' quality of life.

[0230] The present embodiment relates to a multimodal ophthalmic auxiliary diagnosis and nursing follow-up system, which includes: a multimodal ophthalmic basic data collection module, an auxiliary diagnosis module for the entire course of disease, a nursing follow-up module for the entire course of disease, and an output module; wherein the multimodal ophthalmic basic data collection module is used to obtain a patient identification when the patient is first consulted, and after obtaining new multimodal ophthalmic basic data of the patient at each stage of the course of disease according to the patient identification, the auxiliary information of the new multimodal ophthalmic basic data is determined, and the new multimodal ophthalmic basic data and the auxiliary information are stored; the auxiliary diagnosis module for the entire course of disease is used to determine an auxiliary diagnosis decision according to the multimodal ophthalmic basic data and the auxiliary information; the nursing follow-up module for the entire course of disease is used to determine a follow-up level and generate a nursing follow-up plan according to the multimodal ophthalmic basic data and the auxiliary information; the output module is used to output a nursing follow-up plan and / or an auxiliary diagnosis decision according to the follow-up level, so as to realize auxiliary diagnosis and nursing follow-up at all stages of the course of disease and ensure the auxiliary accuracy at each stage of the course of disease.

[0231] It should be clear that the present invention is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present invention.

[0232] It should also be noted that the exemplary embodiments mentioned in the present invention describe some methods or systems based on a series of steps or devices. However, the present invention is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiments, or in a different order from the embodiments, or several steps can be performed simultaneously.

[0233] Finally, it should be noted that the above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some or all of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A multimodal ophthalmology auxiliary diagnosis and nursing follow-up system, characterized in that: The system includes: a multimodal basic ophthalmological data collection module, a full-course auxiliary diagnosis module, a full-course nursing follow-up module, and an output module; The multimodal basic ophthalmological data collection module is used to obtain the patient identification when the patient is consulted for the first time, obtain the new multimodal basic ophthalmological data of the patient at each stage of the disease course according to the patient identification, determine the auxiliary information of the new multimodal basic ophthalmological data, and store the new multimodal basic ophthalmological data and the auxiliary information; wherein the disease course stage is the pre-hospital stage, the in-hospital stage, or the post-hospital stage; The auxiliary diagnosis module for the whole course of the disease is used to determine the auxiliary diagnosis decision based on the multimodal basic ophthalmology data and auxiliary information stored in the multimodal basic ophthalmology data collection module; The whole course nursing follow-up module is used to determine the follow-up level and generate the nursing follow-up plan according to the multimodal ophthalmological basic data and auxiliary information stored in the multimodal ophthalmological basic data collection module; The output module is used to output the nursing follow-up plan generated by the nursing follow-up module of the whole course of illness and / or the auxiliary diagnosis decision obtained by the auxiliary diagnosis module of the whole course of illness according to the follow-up level.

2. The system according to claim 1, characterized in that The modalities of basic ophthalmological data include: text modality, image modality, imaging modality, and audio modality; The auxiliary information for determining the new multimodal ophthalmic basic data includes: Determine the generation time of the new multi-modal ophthalmic basic data Wherein, i is the patient ID, and j is the patient's ophthalmological basic data ID; Determine the disease stage using the new multimodal ophthalmological data Determine a summary of the new multimodal ophthalmological basic data according to the modality of the new multimodal ophthalmological basic data and auxiliary diseases According to the abstract Determining related data from the stored multimodal basic ophthalmological data of the patient; Extracting key attribute values ​​from the new multimodal ophthalmological basic data and associated data; According to the new multimodal ophthalmological basic data and the key attribute values ​​in the associated data, a description of the new multimodal ophthalmological basic data is formed. Will and Auxiliary information forming the new multimodal ophthalmic basic data.

3. The system according to claim 2, characterized in that The description of the new multimodal ophthalmological basic data is formed according to the key attribute values ​​in the new multimodal ophthalmological basic data and the associated data. include: Distance between production time The most recent associated data are determined as the comparison data; Determine the key attributes that only appear in the new multimodal ophthalmological basic data and the key attributes that only appear in the comparison data as abnormal key attributes; determine the key attributes that appear in both the new multimodal ophthalmological basic data and the comparison data as common key attributes; For abnormal key attributes, determine the weight of each abnormal key attribute, and form abnormal triples with abnormal key attributes whose weights are greater than a preset abnormal weight threshold, wherein any abnormal triple is <identifier of the data, abnormal key attribute, value of the abnormal key attribute>; For common key attributes, determine the first key attribute value of each common key attribute in the new multimodal ophthalmological basic data and the second key attribute value in the comparison data; form an abnormal quadruple of common key attributes whose degree of change between the first key attribute value and the second key attribute value satisfies a preset abnormal degree, wherein any abnormal quadruple is <common key attribute, corresponding first key attribute value, corresponding second key attribute value, abnormal trend>; Abnormal triples and abnormal quadruples form the description of the new multimodal ophthalmological basic data 4. The system according to claim 3, characterized in that Determining the weight of each abnormal key attribute includes: For any abnormal key attribute u, its weight is determined by the following steps: Determine u and The degree of theoretical correlation between In the diagnosis of Determine the probability of u appearing in all multimodal ophthalmic basic data in, To diagnose the disease The number of u in the multimodal ophthalmological basic data of all patients, To diagnose the disease The total number of multimodal basic ophthalmic data of all patients; Based on all the summaries of the patients, comparison patients were identified; In comparing all the multimodal ophthalmic basic data of the patient, the confirmed disease is And the probability of u appearing in, To compare the patient's multimodal ophthalmological basic data, the confirmed disease is The number of is the total number of all multimodal basic ophthalmic data of the patients compared, To compare the patient's multimodal ophthalmological basic data, the confirmed disease is And the number of u appears; Determine u and The degree of patient association Determine the weight of any abnormal key attribute u as Among them, max{} is the maximum value function.

5. The system according to claim 3, characterized in that After determining the first key attribute value of each common key attribute in the new multimodal ophthalmological basic data and the second key attribute value in the comparison data, the method further includes: For any common key attribute v, if its first key attribute value or second key attribute value is not within the standard value interval of v, then determine whether the degree of change between the first key attribute value and the second key attribute value of v meets the preset abnormality degree; If both the first key attribute value and the second key attribute value of v are within the standard value interval of v, then determine the third key attribute value of v in each associated data of the non-matching data; determine the first difference between the first key attribute value and each third key attribute value; determine the second difference between the first key attribute value and the second key attribute value; determine the first standard deviation of all first differences; determine the second standard deviation of all first differences and second differences; if the ratio of the first standard deviation to the second standard deviation is less than a preset standard deviation ratio threshold, then determine that the degree of change between the first key attribute value and the second key attribute value of v meets the preset abnormality degree; if the ratio of the first standard deviation to the second standard deviation is not less than the preset standard deviation ratio threshold, but |second difference - mean of the first difference| / second difference is greater than the preset difference ratio threshold, then determine that the degree of change between the first key attribute value and the second key attribute value of v meets the preset abnormality degree.

6. The system according to claim 1, characterized in that The auxiliary diagnosis and decision-making in the pre-hospital stage includes: pre-operative evaluation, diversified information introduction, health education, psychological support and pre-operative preparation; the information introduction includes: ward environment, disease knowledge, knowledge related to stem cell transplantation and gene therapy, and introduction of pre-treatment preparation; The auxiliary diagnosis and decision-making in the hospital stage includes: providing perioperative care and management for patients, paying attention to patients' vital signs and surgical progress, observing changes in patients' conditions, observing conditions, monitoring complications, managing medication, pain management, dietary guidance, psychological counseling, and assessing patients' readiness for discharge; The auxiliary diagnosis decision-making in the post-hospital stage includes: conducting diversified follow-up management of patients, disseminating relevant knowledge, understanding the changes in patients' conditions and recovery status, responding to patient consultations, and providing guidance and assistance.

7. The system according to claim 1, characterized in that The nursing follow-up protocol for the described pre-hospital phase includes: baseline assessment before the patient undergoes stem cell transplantation and gene therapy procedures; The nursing follow-up program during the in-hospital stage includes: daily follow-up to assess the patient's readiness for discharge; The nursing follow-up plan for the post-hospital stage includes: if the follow-up type is short-term follow-up after surgery, the incidence of surgical complications and the patient's recovery are evaluated; if the follow-up type is long-term follow-up after surgery, the long-term effects of stem cell transplantation and gene therapy surgery and changes in the patient's quality of life are evaluated; among them, if the follow-up date does not exceed three months after the patient's surgery, the follow-up type is determined to be short-term follow-up after surgery, and if the follow-up date exceeds three months after the patient's surgery, the follow-up type is determined to be long-term follow-up after surgery.

8. The system according to claim 7, characterized in that The follow-up content during the follow-up visit should at least include: visual assessment, complication assessment, quality of life assessment, and psychological status assessment; Among them, the evaluation indicators of quality of life assessment include: overall visual condition, eye pain, close work, long-distance work, social ability, mental health status, social role limitations, independence, color vision and peripheral vision.

9. The system according to claim 7, characterized in that The auxiliary information of any multimodal ophthalmic basic data j of any patient i includes: generation time Disease stage summary Auxiliary diseases describe Determining the level of follow-up includes: The follow-up level of any patient i is determined by the following steps: Determine the multimodal basic ophthalmological data whose generation time is closest to the current time as the target data; Determine the current disease stage as the disease stage of the target data; If the current stage of the disease course is the in-hospital stage, the follow-up level of patient i is determined to be the highest level; If the current stage of the disease course is the post-hospital stage, the target generation time is determined, and the follow-up type is determined according to the target generation time; if the follow-up type is short-term postoperative follow-up, the follow-up level of patient i is determined to be the highest level; if the follow-up type is long-term postoperative follow-up, the follow-up level of patient i is determined to be a low level; wherein the target generation time is the generation time of the multimodal basic ophthalmological data that is closest to the current time and the disease course stage is the in-hospital stage; If the current stage of the disease course is the pre-hospital stage, the follow-up level of patient i is determined based on the summary, auxiliary symptoms, and description of the target data.

10. The system according to claim 9, characterized in that The step of determining the follow-up level of patient i according to the summary, auxiliary symptoms, and description of the target data includes: Estimate the duration of surgery based on the summary of target data, auxiliary symptoms, and descriptions; If the estimated operation time is greater than the preset time threshold, the follow-up level of patient i is determined to be the lowest level; If the estimated operation time is not greater than the preset time threshold, the completion degree of the preoperative examination is determined based on the summary of each multimodal basic ophthalmic data j of patient i and auxiliary symptoms; if the completion degree is greater than the preset maximum completion degree threshold, the follow-up level of patient i is determined to be high level; if the completion degree is not greater than the preset maximum completion degree threshold, the follow-up level of patient i is determined to be medium level.

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