Big data-based hepatobiliary surgery treatment scheme screening system and method

Abstract

The invention relates to the technical field of hepatobiliary surgery treatment scheme screening, and particularly discloses a hepatobiliary surgery treatment scheme screening system and method based on big data, and the system comprises a processing module which is used for processing all types of treatment information of all reference hepatobiliary surgery treatment schemes of a current patient based on all types of treatment information of all reference hepatobiliary surgery treatment schemes of the current patient; obtaining safety evaluation values, effectiveness evaluation values and economic evaluation values of all the reference hepatobiliary surgery treatment schemes of the current patient; the construction module is used for obtaining a treatment scheme analysis matrix of the current patient based on the safety evaluation values, the effectiveness evaluation values and the economical evaluation values of all the reference hepatobiliary surgery treatment schemes of the current patient; and the screening module is used for obtaining the optimal screening hepatobiliary surgery treatment scheme of the current patient based on the treatment scheme analysis matrix of the current patient. According to the method, the safety, the effectiveness and the economical efficiency of the treatment scheme are comprehensively considered, accurate screening of the optimal hepatobiliary surgery treatment scheme of the patient is achieved, and the scientificity and the efficiency of medical decision making are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of screening of hepatobiliary surgery treatment plans, and particularly relates to a system and method for screening hepatobiliary surgery treatment plans based on big data. Background Art

[0002] At present, there are a wide variety of hepatobiliary surgery diseases, including cholecystitis, gallstones, liver cancer, liver cirrhosis and other diseases, and the treatment plans for each disease may be different. At the same time, with the continuous progress of medical technology, new treatment methods and techniques are constantly emerging, making the selection of hepatobiliary surgery treatment plans more complex and diverse. There are differences in factors such as the nature of the lesion, the diameter length of the lesion, and the lesion location area of each patient, and these factors will affect the selection of the treatment plan. At the same time, when selecting a hepatobiliary surgery treatment plan, doctors need to comprehensively consider multiple factors, including the safety, effectiveness, and economy of the treatment plan. However, these factors are often difficult to directly quantify, and there may be a trade-off relationship between different factors. For example, some treatment plans may have high effectiveness, but may be poor in terms of safety or economy; while other treatment plans may perform well in terms of safety and economy, but may be slightly lower in effectiveness. Therefore, a technical method that can comprehensively consider the safety, effectiveness, and economy of treatment plans and quantify them is needed. This method can help doctors more objectively and accurately evaluate the advantages and disadvantages of different treatment plans, so as to select the most suitable treatment plan for patients. At the same time, this method can also improve the transparency and repeatability of treatment plan selection, and reduce the subjectivity and uncertainty of doctors when selecting treatment plans.

[0003] However, the existing screening systems and methods for hepatobiliary surgery treatment plans based on big data only achieve automatic identification and classification, reduce labor costs, and transform the generation of the transfer dataset into a binary min-max game problem through the generative adversarial model technology of the recognition module, so as to obtain the transfer dataset more effectively and provide it to the liver tumor discrimination network for training to obtain better results under a larger training set. It does not consider aspects of comprehensive safety, effectiveness, and economy to screen out the most suitable hepatobiliary surgery treatment plan for the current patient. For example, the patent with the publication number "CN110070125A" and the patent name "A Screening Method and System for Hepatobiliary Surgery Treatment Plans Based on Big Data Analysis", its method includes the following steps: hepatobiliary image acquisition module, condition input module, central control module, image classification module, recognition module, big data processing module, retrieval module, matching module, printing module, display module. The above patent can obtain accurate classification results through the image classification module, reduce the interference of noise, and achieve automatic identification and classification, reducing labor costs; at the same time, through the generative adversarial model technology of the recognition module, the generation of the transfer dataset is transformed into a binary min-max game problem, so as to obtain the transfer dataset more effectively and provide it to the liver tumor discrimination network for training to obtain better results under a larger training set. However, this patent only achieves automatic identification and classification, reduces labor costs, and transforms the generation of the transfer dataset into a binary min-max game problem through the generative adversarial model technology of the recognition module, so as to obtain the transfer dataset more effectively and provide it to the liver tumor discrimination network for training to obtain better results under a larger training set. It does not consider aspects of comprehensive safety, effectiveness, and economy to screen out the most suitable hepatobiliary surgery treatment plan for the current patient.

[0004] Therefore, the present invention proposes a screening system and method for hepatobiliary surgery treatment plans based on big data. Summary of the Invention

[0005] The present invention provides a screening system and method for hepatobiliary surgery treatment plans based on big data, which is used to obtain the safety evaluation value, effectiveness evaluation value and economy evaluation value of all reference hepatobiliary surgery treatment plans for the current patient according to all types of treatment information of all reference hepatobiliary surgery treatment plans for the current patient, realizing the separate quantification of the treatment safety, treatment effectiveness and treatment economy of each reference hepatobiliary surgery treatment plan for the current patient. Furthermore, according to the safety evaluation value, effectiveness evaluation value and economy evaluation value of all reference hepatobiliary surgery treatment plans for the current patient, all plotting coordinate points of each reference hepatobiliary surgery treatment plan for the current patient are obtained, which is convenient for the subsequent construction of the treatment plan analysis matrix of the current patient. According to all the plotting coordinate points of all reference hepatobiliary surgery treatment plans for the current patient, the treatment plan analysis matrix of the current patient is obtained. Furthermore, according to the treatment plan analysis matrix of the current patient, the screening priority value of each reference hepatobiliary surgery treatment plan for the current patient is obtained, realizing the quantification of the priority degree of each reference hepatobiliary surgery treatment plan for the current patient as the best screened hepatobiliary surgery treatment plan. Finally, according to the screening priority values of all reference hepatobiliary surgery treatment plans for the current patient, the best screened hepatobiliary surgery treatment plan for the current patient is obtained, realizing the screening of the most suitable hepatobiliary surgery treatment plan for the current patient in terms of comprehensive safety, effectiveness and economy.

[0006] The present invention provides a screening system for hepatobiliary surgery treatment plans based on big data, including:

[0007] An acquisition module, configured to obtain all reference patients of the current patient based on all types of basic information of the current patient and a preset database, and obtain all reference hepatobiliary surgery treatment plans of the current patient based on all reference patients of the current patient;

[0008] A processing module, configured to obtain the safety evaluation value, effectiveness evaluation value and economy evaluation value of all reference hepatobiliary surgery treatment plans of the current patient based on all types of treatment information of all reference hepatobiliary surgery treatment plans of the current patient;

[0009] A construction module, configured to obtain all plotting coordinate points of each reference hepatobiliary surgery treatment plan of the current patient based on the safety evaluation value, effectiveness evaluation value and economy evaluation value of all reference hepatobiliary surgery treatment plans of the current patient, and obtain the treatment plan analysis matrix of the current patient based on all the plotting coordinate points of all reference hepatobiliary surgery treatment plans of the current patient;

[0010] A screening module, configured to obtain the screening priority value of each reference hepatobiliary surgery treatment plan of the current patient based on the treatment plan analysis matrix of the current patient, and obtain the best screened hepatobiliary surgery treatment plan of the current patient based on the screening priority values of all reference hepatobiliary surgery treatment plans of the current patient.

[0011] Preferably, for the hepatobiliary surgery treatment plan screening system based on big data, the acquisition module includes:

[0012] The reference patient determination sub-module is used to obtain all the reference patients of the current patient based on all types of basic information of the current patient and the preset database;

[0013] The treatment plan acquisition sub-module is used to take the hepatobiliary surgery treatment plans of each reference patient of the current patient extracted from the preset database as the reference hepatobiliary surgery treatment plans of the current patient.

[0014] Preferably, for the hepatobiliary surgery treatment plan screening system based on big data, the reference patient determination sub-module includes:

[0015] The basic information acquisition unit is used to obtain all types of basic information of the current patient, where all types of basic information include the nature of the lesion, the diameter length of the lesion, and the lesion location area;

[0016] The reference patient determination unit is used to regard the corresponding patient as the reference patient of the current patient when all types of basic information of each patient stored in the preset database correspond to all types of basic information of the current patient.

[0017] Preferably, for the hepatobiliary surgery treatment plan screening system based on big data, the processing module includes:

[0018] The preprocessing sub-module is used to obtain all types of treatment information of all the reference hepatobiliary surgery treatment plans of the current patient, where all types of treatment information include safety treatment information, effectiveness treatment information, and economic treatment information, and the safety treatment information includes the postoperative recovery time, the postoperative liver function evaluation index value, and the intraoperative blood loss, the effectiveness treatment information includes the surgical resection rate and the score assigned to the improvement of postoperative symptoms, and the economic treatment information includes the surgical cost, the hospital stay, and the subsequent treatment cost;

[0019] The processing sub-module is used to obtain the safety evaluation value, effectiveness evaluation value, and economic evaluation value of all the reference hepatobiliary surgery treatment plans of the current patient based on all types of treatment information of all the reference hepatobiliary surgery treatment plans of the current patient.

[0020] Preferably, for the hepatobiliary surgery treatment plan screening system based on big data, the processing sub-module includes:

[0021] The first processing unit is used to obtain the safety evaluation value of each reference hepatobiliary surgery treatment plan of the current patient based on the safety treatment information of all the reference hepatobiliary surgery treatment plans of the current patient, that is:

[0022]

[0023] Among them, α is the safety evaluation value of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, A is the postoperative recovery time of the safety treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, and A max is the maximum value of the postoperative recovery times of the safety treatment information of all reference hepatobiliary surgery treatment plans for the current patient. B is the postoperative liver function evaluation index value of the safety treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, and B max is the maximum value of the postoperative liver function evaluation index values of the safety treatment information of all reference hepatobiliary surgery treatment plans for the current patient. C is the intraoperative blood loss of the safety treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, and C max is the maximum value of the intraoperative blood losses of the safety treatment information of all reference hepatobiliary surgery treatment plans for the current patient. ln is the natural logarithm, and the value of the natural constant e is 2.718;

[0024] The second processing unit is used to obtain the effectiveness evaluation value of each reference hepatobiliary surgery treatment plan for the current patient based on the effectiveness treatment information of all reference hepatobiliary surgery treatment plans for the current patient, that is:

[0025]

[0026] Among them, β is the effectiveness evaluation value of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, D is the surgical resection rate of the effectiveness treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, and D max is the maximum value of the surgical resection rates of the effectiveness treatment information of all reference hepatobiliary surgery treatment plans for the current patient. E is the score assigned to the improvement of postoperative symptoms of the effectiveness treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, and E max is the maximum value of the scores assigned to the improvement of postoperative symptoms of the effectiveness treatment information of all reference hepatobiliary surgery treatment plans for the current patient;

[0027] The third processing unit is used to obtain the economic evaluation value of each reference hepatobiliary surgery treatment plan for the current patient based on the economic treatment information of all reference hepatobiliary surgery treatment plans for the current patient.

[0028] Preferably, for the hepatobiliary surgery treatment plan screening system based on big data, the method by which the third processing unit obtains the economic evaluation value of each reference hepatobiliary surgery treatment plan for the current patient based on the economic treatment information of all reference hepatobiliary surgery treatment plans for the current patient includes:

[0029]

[0030] Among them, γ is the economic evaluation value of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, F is the surgical cost of the economic treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, F max is the maximum value among the surgical costs of the economic treatment information of all reference hepatobiliary surgery treatment plans for the current patient, G is the length of hospital stay of the economic treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, G max is the maximum value among the lengths of hospital stay of the economic treatment information of all reference hepatobiliary surgery treatment plans for the current patient, H is the follow-up treatment cost of the economic treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, H max is the maximum value among the follow-up treatment costs of the economic treatment information of all reference hepatobiliary surgery treatment plans for the current patient.

[0031] Preferably, the screening system for hepatobiliary surgery treatment plans based on big data, the construction module, includes:

[0032] The first construction sub-module is used to take the safety evaluation value of each reference hepatobiliary surgery treatment plan of the current patient as the abscissa value, and the effectiveness evaluation value of the corresponding reference hepatobiliary surgery treatment plan of the current patient as the ordinate value to obtain the first coordinate point of the corresponding reference hepatobiliary surgery treatment plan of the current patient. Take the safety evaluation value of each reference hepatobiliary surgery treatment plan of the current patient as the abscissa value, and the economic evaluation value of the corresponding reference hepatobiliary surgery treatment plan of the current patient as the ordinate value to obtain the second coordinate point of the corresponding reference hepatobiliary surgery treatment plan of the current patient. Take the effectiveness evaluation value of each reference hepatobiliary surgery treatment plan of the current patient as the abscissa value, and the economic evaluation value of the corresponding reference hepatobiliary surgery treatment plan of the current patient as the ordinate value to obtain the third coordinate point of the corresponding reference hepatobiliary surgery treatment plan of the current patient. Obtain the first coordinate point, the second coordinate point and the third coordinate point of each reference hepatobiliary surgery treatment plan of the current patient, and take the first coordinate point, the second coordinate point and the third coordinate point of each reference hepatobiliary surgery treatment plan of the current patient as all the drawing coordinate points of each reference hepatobiliary surgery treatment plan of the current patient;

[0033] The second construction sub-module is used to obtain the treatment plan analysis matrix of the current patient based on all the drawing coordinate points of all the reference hepatobiliary surgery treatment plans of the current patient.

[0034] Preferably, the screening system for hepatobiliary surgery treatment plans based on big data, the second construction sub-module, includes:

[0035] A preprocessing unit for taking the distance between the first coordinate point and the second coordinate point of each reference hepatobiliary surgery treatment plan of the current patient as the first distance of each reference hepatobiliary surgery treatment plan of the current patient, taking the distance between the first coordinate point and the third coordinate point of each reference hepatobiliary surgery treatment plan of the current patient as the second distance of each reference hepatobiliary surgery treatment plan of the current patient, and taking the distance between the second coordinate point and the third coordinate point of each reference hepatobiliary surgery treatment plan of the current patient as the third distance of each reference hepatobiliary surgery treatment plan of the current patient;

[0036] A construction unit for defining the ordinal numbers starting from 1 for all reference hepatobiliary surgery treatment plans of the current patient in the order of the first distance of the reference hepatobiliary surgery treatment plans from large to small, obtaining the ordinal definition result of all reference hepatobiliary surgery treatment plans of the current patient, and obtaining the treatment plan analysis matrix of the current patient based on the first distance, second distance, third distance and ordinal definition result of all reference hepatobiliary surgery treatment plans of the current patient, that is:

[0037]

[0038] where δ is the treatment plan analysis matrix of the current patient, and τ n1 is the value of the first distance of the reference hepatobiliary surgery treatment plan with the ordinal number n defined for the current patient, and τ n2 is the value of the second distance of the reference hepatobiliary surgery treatment plan with the ordinal number n defined for the current patient, and τ n3 is the value of the third distance of the reference hepatobiliary surgery treatment plan with the ordinal number n defined for the current patient, and n is the total number of all reference hepatobiliary surgery treatment plans of the current patient.

[0039] Preferably, a screening system for hepatobiliary surgery treatment plans based on big data, a screening module, includes:

[0040] A screening priority value calculation sub-module for obtaining the screening priority value of each reference hepatobiliary surgery treatment plan of the current patient based on the treatment plan analysis matrix of the current patient, that is:

[0041]

[0042] where μ is the screening priority value of the currently calculated reference hepatobiliary surgery treatment plan of the current patient, τ1 is the value of the first distance of the currently calculated reference hepatobiliary surgery treatment plan of the current patient, τ2 is the value of the second distance of the currently calculated reference hepatobiliary surgery treatment plan of the current patient, τ3 is the value of the third distance of the currently calculated reference hepatobiliary surgery treatment plan of the current patient, Let \(r\) be the rank of the treatment plan analysis matrix for the current patient, \(\sigma_1\) be the standard deviation of the values of the first distance of all reference hepatobiliary surgery treatment plans for the current patient, \(\sigma_2\) be the standard deviation of the values of the second distance of all reference hepatobiliary surgery treatment plans for the current patient, \(\sigma_3\) be the standard deviation of the values of the third distance of all reference hepatobiliary surgery treatment plans for the current patient, \(\ln\) be the natural logarithm, and the value of the natural constant \(e\) is 2.718;

[0043] A screening sub-module, configured to screen out the reference hepatobiliary surgery treatment plan with the largest priority value from all the reference hepatobiliary surgery treatment plans of the current patient, and use it as the best screened hepatobiliary surgery treatment plan for the current patient.

[0044] The present invention provides a method for screening hepatobiliary surgery treatment plans based on big data, which is applied to any one of the hepatobiliary surgery treatment plan screening systems based on big data in Embodiments 1 to 9, and includes:

[0045] S1: Based on all the class-based information of the current patient and a preset database, obtain all the reference patients of the current patient, and based on all the reference patients of the current patient, obtain all the reference hepatobiliary surgery treatment plans of the current patient;

[0046] S2: Based on all the class-based treatment information of all the reference hepatobiliary surgery treatment plans of the current patient, obtain the safety evaluation value, effectiveness evaluation value, and economic evaluation value of all the reference hepatobiliary surgery treatment plans of the current patient;

[0047] S3: Based on the safety evaluation value, effectiveness evaluation value, and economic evaluation value of all the reference hepatobiliary surgery treatment plans of the current patient, obtain all the plotted coordinate points of each reference hepatobiliary surgery treatment plan of the current patient, and based on all the plotted coordinate points of all the reference hepatobiliary surgery treatment plans of the current patient, obtain the treatment plan analysis matrix of the current patient;

[0048] S4: Based on the treatment plan analysis matrix of the current patient, obtain the screening priority value of each reference hepatobiliary surgery treatment plan of the current patient, and based on the screening priority values of all the reference hepatobiliary surgery treatment plans of the current patient, obtain the best screened hepatobiliary surgery treatment plan of the current patient.

[0049] The beneficial effects of the present invention compared with the prior art are as follows: According to all types of treatment information of all reference hepatobiliary surgery treatment plans for the current patient, the safety evaluation value, effectiveness evaluation value, and economy evaluation value of all reference hepatobiliary surgery treatment plans for the current patient are obtained, realizing the separate quantification of the treatment safety, treatment effectiveness, and treatment economy of each reference hepatobiliary surgery treatment plan for the current patient. Furthermore, according to the safety evaluation value, effectiveness evaluation value, and economy evaluation value of all reference hepatobiliary surgery treatment plans for the current patient, all plotting coordinate points of each reference hepatobiliary surgery treatment plan for the current patient are obtained, facilitating the subsequent construction of the treatment plan analysis matrix for the current patient. According to all the plotting coordinate points of all reference hepatobiliary surgery treatment plans for the current patient, the treatment plan analysis matrix for the current patient is obtained. Furthermore, according to the treatment plan analysis matrix for the current patient, the screening priority value of each reference hepatobiliary surgery treatment plan for the current patient is obtained, realizing the quantification of the priority degree of each reference hepatobiliary surgery treatment plan for the current patient as the best screened hepatobiliary surgery treatment plan. Finally, according to the screening priority values of all reference hepatobiliary surgery treatment plans for the current patient, the best screened hepatobiliary surgery treatment plan for the current patient is obtained, realizing the screening of the most suitable hepatobiliary surgery treatment plan for the current patient in terms of comprehensive safety, effectiveness, and economy.

[0050] Other features and advantages of the present invention will be described in the following specification, and in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained by the structures specifically pointed out in the written application documents of the present application.

[0051] The technical solutions of the present invention will be further described in detail below through the drawings and embodiments. Description of the Drawings

[0052] The drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation to the present invention. In the drawings:

[0053] Figure 1 It is a schematic diagram of a system for screening hepatobiliary surgery treatment plans based on big data in an embodiment of the present invention;

[0054] Figure 2 It is a flowchart of a method for screening hepatobiliary surgery treatment plans based on big data in an embodiment of the present invention. Detailed Embodiments

[0055] The following describes the preferred embodiments of the present invention with reference to the drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention and are not used to limit the present invention.

[0056] Example 1:

[0057] The present invention provides a screening system for hepatobiliary surgery treatment plans based on big data. Referring to Figure 1 , including:

[0058] An acquisition module, configured to obtain all reference patients of the current patient based on all types of basic information of the current patient and a preset database, and obtain all reference hepatobiliary surgery treatment plans of the current patient based on all reference patients of the current patient;

[0059] A processing module, configured to obtain a safety evaluation value, an effectiveness evaluation value, and an economic evaluation value of all reference hepatobiliary surgery treatment plans of the current patient based on all types of treatment information of all reference hepatobiliary surgery treatment plans of the current patient;

[0060] A construction module, configured to obtain all drawing coordinate points of each reference hepatobiliary surgery treatment plan of the current patient based on the safety evaluation value, the effectiveness evaluation value, and the economic evaluation value of all reference hepatobiliary surgery treatment plans of the current patient, and obtain a treatment plan analysis matrix of the current patient based on all drawing coordinate points of all reference hepatobiliary surgery treatment plans of the current patient;

[0061] A screening module, configured to obtain a screening priority value of each reference hepatobiliary surgery treatment plan of the current patient based on the treatment plan analysis matrix of the current patient, and obtain the best screened hepatobiliary surgery treatment plan of the current patient based on the screening priority values of all reference hepatobiliary surgery treatment plans of the current patient.

[0062] In this embodiment, the current patient is a patient who applies the screening system for hepatobiliary surgery treatment plans based on big data at the current moment to determine the best screened hepatobiliary surgery treatment plan.

[0063] In this embodiment, the preset database is a database storing all types of basic information of a large number of (hepatobiliary surgery) patients and information such as hepatobiliary surgery treatment plans in advance.

[0064] In this embodiment, the reference patients are some patients in the preset database that need to be referred to for analyzing and determining the best screened hepatobiliary surgery treatment plan of the current patient.

[0065] In this embodiment, the reference hepatobiliary surgery treatment plans are some hepatobiliary surgery treatment plans that need to be referred to for analyzing and determining the best screened hepatobiliary surgery treatment plan of the current patient.

[0066] In this embodiment, the safety evaluation value is a numerical value evaluated to characterize the treatment safety of each reference hepatobiliary surgery treatment plan of the current patient.

[0067] In this embodiment, the effectiveness evaluation value is a value evaluated to characterize the treatment effectiveness of each reference hepatobiliary surgery treatment plan for the current patient.

[0068] In this embodiment, the economic evaluation value is a value evaluated to characterize the treatment economy of each reference hepatobiliary surgery treatment plan for the current patient.

[0069] In this embodiment, the plotted coordinate point is a coordinate point obtained based on the safety evaluation value, effectiveness evaluation value, and economic evaluation value of all reference hepatobiliary surgery treatment plans for the current patient, and is used to construct the treatment plan analysis matrix of the current patient.

[0070] In this embodiment, the treatment plan analysis matrix of the current patient is a matrix used to analyze and calculate the screening priority value of each reference hepatobiliary surgery treatment plan for the current patient.

[0071] In this embodiment, the screening priority value is a value that comprehensively considers the aspects of safety, effectiveness, and economy, and characterizes the priority degree of each reference hepatobiliary surgery treatment plan for the current patient as the best screened hepatobiliary surgery treatment plan.

[0072] In this embodiment, the best screened hepatobiliary surgery treatment plan for the current patient is the reference hepatobiliary surgery treatment plan that is comprehensively the best when treating the current patient and is screened from all reference hepatobiliary surgery treatment plans of the current patient.

[0073] The beneficial effects of the above technology are as follows: According to all types of treatment information of all reference hepatobiliary surgery treatment plans of the current patient, the safety evaluation value, effectiveness evaluation value, and economic evaluation value of all reference hepatobiliary surgery treatment plans of the current patient are obtained, realizing the separate quantification of the treatment safety, treatment effectiveness, and treatment economy of each reference hepatobiliary surgery treatment plan for the current patient. Furthermore, based on the safety evaluation value, effectiveness evaluation value, and economic evaluation value of all reference hepatobiliary surgery treatment plans of the current patient, all plotted coordinate points of each reference hepatobiliary surgery treatment plan for the current patient are obtained, facilitating the subsequent construction of the treatment plan analysis matrix of the current patient. According to all plotted coordinate points of all reference hepatobiliary surgery treatment plans of the current patient, the treatment plan analysis matrix of the current patient is obtained. Furthermore, based on the treatment plan analysis matrix of the current patient, the screening priority value of each reference hepatobiliary surgery treatment plan for the current patient is obtained, realizing the quantification of the priority degree of each reference hepatobiliary surgery treatment plan for the current patient as the best screened hepatobiliary surgery treatment plan. Finally, based on the screening priority values of all reference hepatobiliary surgery treatment plans of the current patient, the best screened hepatobiliary surgery treatment plan for the current patient is obtained, realizing the screening of the most suitable hepatobiliary surgery treatment plan for the current patient in terms of comprehensive safety, effectiveness, and economy.

[0074] Example 2:

[0075] Based on the system for screening hepatobiliary surgery treatment plans using big data in Example 1, the acquisition module includes:

[0076] A reference patient determination sub-module, configured to obtain all reference patients of the current patient based on all types of basic information of the current patient and a preset database;

[0077] A treatment plan acquisition sub-module, configured to use the hepatobiliary surgery treatment plans of each reference patient of the current patient extracted from the preset database as the reference hepatobiliary surgery treatment plans of the current patient.

[0078] The beneficial effects of the above technology are as follows: According to the preset database and each reference patient of the current patient, the reference hepatobiliary surgery treatment plans of the current patient are obtained, which is convenient for subsequent screening of the best hepatobiliary surgery treatment plan for the current patient.

[0079] Example 3:

[0080] Based on the system for screening hepatobiliary surgery treatment plans using big data in Example 2, the reference patient determination sub-module includes:

[0081] A basic information acquisition unit, configured to obtain all types of basic information of the current patient, where all types of basic information include the nature of the lesion, the diameter length of the lesion focus, and the lesion location area;

[0082] A reference patient determination unit, configured to use the patient corresponding to the current patient as the reference patient of the current patient when all types of basic information of each patient stored in the preset database correspond to all types of basic information of the current patient.

[0083] In this embodiment, the nature of the lesion is the nature of the hepatobiliary surgery lesion of the patient, such as tumor, stone, inflammation, etc.

[0084] In this embodiment, the diameter length of the lesion focus is the size of the longest transverse diameter of the lesion focus (such as tumor, stone, inflammation area, etc.) observed in medical images (such as ultrasound, CT, MRI, etc.), and the unit of the diameter length of the lesion focus is millimeter (mm).

[0085] In this embodiment, the lesion location area is the specific location of the hepatobiliary surgery lesion of the patient in the liver or biliary system determined by imaging technology. In this embodiment, all regions of the liver and gallbladder have been pre-divided.

[0086] In this embodiment, corresponding to the same means that each type of basic information of each patient stored in the preset database is the same as the corresponding type of basic information of the current patient.

[0087] The beneficial effects of the above technology are as follows: The specific information items of all categories of basic information of the current patient are clarified, and a specific method for obtaining all reference patients of the current patient based on all categories of basic information of the current patient and a preset database is given in detail.

[0088] Example 4:

[0089] Based on Example 1, in the hepatobiliary surgery treatment plan screening system based on big data, the processing module includes:

[0090] A preprocessing sub-module, which is used to obtain all categories of treatment information of all reference hepatobiliary surgery treatment plans of the current patient. All categories of treatment information include safety treatment information, effectiveness treatment information, and economic treatment information. The safety treatment information includes the postoperative recovery time, the value of postoperative liver function evaluation indicators, and the intraoperative blood loss. The effectiveness treatment information includes the surgical resection rate and the score assigned to the improvement of postoperative symptoms. The economic treatment information includes the surgical cost, the length of hospital stay, and the subsequent treatment cost;

[0091] A processing sub-module, which is used to obtain the safety evaluation value, effectiveness evaluation value, and economic evaluation value of all reference hepatobiliary surgery treatment plans of the current patient based on all categories of treatment information of all reference hepatobiliary surgery treatment plans of the current patient.

[0092] In this example, the postoperative recovery time is the time required for the patient to recover after using each reference hepatobiliary surgery treatment plan to perform surgical treatment on the corresponding patient (if the reference hepatobiliary surgery treatment plan is not in the form of surgery, the postoperative recovery time is the time required for the patient to cure the hepatobiliary disease).

[0093] In this example, the value of postoperative liver function evaluation indicators is the value that can characterize the quality of the liver function of the corresponding patient evaluated by the attending physician according to various liver function evaluation indicators (such as alanine aminotransferase, aspartate aminotransferase, total bilirubin, etc.) after using each reference hepatobiliary surgery treatment plan to treat the corresponding patient.

[0094] In this example, the intraoperative blood loss is the amount of blood lost by the patient during the operation after using each reference hepatobiliary surgery treatment plan to perform surgical treatment on the corresponding patient (if the reference hepatobiliary surgery treatment plan is not in the form of surgery, the intraoperative blood loss is 0).

[0095] In this example, the surgical resection rate is the quotient of the area of the patient's lesions (such as tumors, stones, inflammatory areas, etc.) eliminated (observed through medical imaging, such as ultrasound) after using each reference hepatobiliary surgery treatment plan to treat the corresponding patient and the area of the patient's lesions (such as tumors, stones, inflammatory areas, etc.) before treatment.

[0096] In this embodiment, the score assigned to the improvement of postoperative symptoms is the value of the improvement degree of liver function before and after treatment of each corresponding patient by each reference hepatobiliary surgery treatment plan evaluated by the attending physician according to various liver function evaluation indicators (such as alanine aminotransferase, aspartate aminotransferase, total bilirubin, etc.).

[0097] In this embodiment, the surgical cost is the surgical cost required by the patient when each reference hepatobiliary surgery treatment plan is used for surgical treatment of the corresponding patient (if the reference hepatobiliary surgery treatment plan is not in the form of surgery, the surgical cost is the cost required for the initial cure of the patient's hepatobiliary lesions).

[0098] In this embodiment, the length of hospital stay is the number of days of hospitalization required by the patient when each reference hepatobiliary surgery treatment plan is used for the treatment of the corresponding patient.

[0099] In this embodiment, the subsequent treatment cost is the reexamination cost and complication treatment cost required by the patient after each reference hepatobiliary surgery treatment plan is used for the treatment of the corresponding patient.

[0100] The beneficial effects of the above technology are as follows: The specific information items of all types of treatment information of all reference hepatobiliary surgery treatment plans for the current patient are clarified, which is convenient for obtaining the safety evaluation value, effectiveness evaluation value and economic evaluation value of all reference hepatobiliary surgery treatment plans for the current patient according to all types of treatment information of all reference hepatobiliary surgery treatment plans for the current patient.

[0101] Embodiment 5:

[0102] On the basis of Embodiment 4, the processing sub-module of the screening system for hepatobiliary surgery treatment plans based on big data includes:

[0103] The first processing unit is used to obtain the safety evaluation value of each reference hepatobiliary surgery treatment plan for the current patient based on the safety treatment information of all reference hepatobiliary surgery treatment plans for the current patient, that is:

[0104]

[0105] Among them, α is the safety evaluation value of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, A is the postoperative recovery time of the safety treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, and A max is the maximum value of the postoperative recovery time of the safety treatment information of all reference hepatobiliary surgery treatment plans for the current patient, and B is the postoperative liver function evaluation index value of the safety treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, and B maxis the maximum value among the postoperative liver function evaluation index values of the safety treatment information of all reference hepatobiliary surgery treatment plans for the current patient, C is the intraoperative blood loss of the safety treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, C max is the maximum value among the intraoperative blood losses of the safety treatment information of all reference hepatobiliary surgery treatment plans for the current patient, ln is the natural logarithm, and the value of the natural constant e is 2.718;

[0106] The second processing unit is used to obtain the effectiveness evaluation value of each reference hepatobiliary surgery treatment plan for the current patient based on the effectiveness treatment information of all reference hepatobiliary surgery treatment plans for the current patient, that is:

[0107]

[0108] where β is the effectiveness evaluation value of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, D is the surgical resection rate of the effectiveness treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, D max is the maximum value among the surgical resection rates of the effectiveness treatment information of all reference hepatobiliary surgery treatment plans for the current patient, E is the score assigned to the improvement of postoperative symptoms of the effectiveness treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, E max is the maximum value among the scores assigned to the improvement of postoperative symptoms of the effectiveness treatment information of all reference hepatobiliary surgery treatment plans for the current patient;

[0109] The third processing unit is used to obtain the economic evaluation value of each reference hepatobiliary surgery treatment plan for the current patient based on the economic treatment information of all reference hepatobiliary surgery treatment plans for the current patient.

[0110] The beneficial effects of the above technology are: According to all types of treatment information of all reference hepatobiliary surgery treatment plans for the current patient, the safety evaluation value, effectiveness evaluation value and economic evaluation value of all reference hepatobiliary surgery treatment plans for the current patient are obtained, realizing the separate quantification of the treatment safety, treatment effectiveness and treatment economy of each reference hepatobiliary surgery treatment plan for the current patient, which is convenient for the subsequent determination of coordinate points.

[0111] Example 6:

[0112] On the basis of Example 5, for the hepatobiliary surgery treatment plan screening system based on big data, the method by which the third processing unit obtains the economic evaluation value of each reference hepatobiliary surgery treatment plan for the current patient based on the economic treatment information of all reference hepatobiliary surgery treatment plans for the current patient includes:

[0113]

[0114] Among them, γ is the economic evaluation value of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, F is the surgical cost of the economic treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, and F max is the maximum value among the surgical costs of the economic treatment information of all reference hepatobiliary surgery treatment plans for the current patient. G is the length of hospital stay of the economic treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, and G max is the maximum value among the lengths of hospital stay of the economic treatment information of all reference hepatobiliary surgery treatment plans for the current patient. H is the follow-up treatment cost of the economic treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, and H max is the maximum value among the follow-up treatment costs of the economic treatment information of all reference hepatobiliary surgery treatment plans for the current patient.

[0115] The beneficial effects of the above technology are as follows: According to the economic treatment information of all reference hepatobiliary surgery treatment plans for the current patient, the economic evaluation value of each reference hepatobiliary surgery treatment plan for the current patient is obtained, realizing the accurate quantification of the treatment economy of each reference hepatobiliary surgery treatment plan for the current patient.

[0116] Example 7:

[0117] Based on the hepatobiliary surgery treatment plan screening system based on big data in Example 1, the construction module includes:

[0118] The first construction sub-module is used to take the safety evaluation value of each reference hepatobiliary surgery treatment plan of the current patient as the abscissa value, and the effectiveness evaluation value of the corresponding reference hepatobiliary surgery treatment plan of the current patient as the ordinate value to obtain the first coordinate point of the corresponding reference hepatobiliary surgery treatment plan of the current patient. Take the safety evaluation value of each reference hepatobiliary surgery treatment plan of the current patient as the abscissa value, and the economic evaluation value of the corresponding reference hepatobiliary surgery treatment plan of the current patient as the ordinate value to obtain the second coordinate point of the corresponding reference hepatobiliary surgery treatment plan of the current patient. Take the effectiveness evaluation value of each reference hepatobiliary surgery treatment plan of the current patient as the abscissa value, and the economic evaluation value of the corresponding reference hepatobiliary surgery treatment plan of the current patient as the ordinate value to obtain the third coordinate point of the corresponding reference hepatobiliary surgery treatment plan of the current patient. Obtain the first coordinate point, the second coordinate point and the third coordinate point of each reference hepatobiliary surgery treatment plan of the current patient, and take the first coordinate point, the second coordinate point and the third coordinate point of each reference hepatobiliary surgery treatment plan of the current patient as all the plotted coordinate points of each reference hepatobiliary surgery treatment plan of the current patient;

[0119] A second construction sub-module, configured to obtain an analysis matrix of the treatment plan for the current patient based on all the plotted coordinate points of all the reference hepatobiliary surgery treatment plans of the current patient.

[0120] The beneficial effects of the above technologies are as follows: According to the safety evaluation value, effectiveness evaluation value, and economy evaluation value of all the reference hepatobiliary surgery treatment plans of the current patient, all the plotted coordinate points of each reference hepatobiliary surgery treatment plan of the current patient are obtained, which facilitates the subsequent construction of the analysis matrix of the treatment plan for the current patient. Based on all the plotted coordinate points of all the reference hepatobiliary surgery treatment plans of the current patient, an analysis matrix of the treatment plan for the current patient is obtained, reducing the influence of subjective judgment in the subsequent determination process of screening the best hepatobiliary surgery treatment plan and enhancing the scientificity and objectivity of the decision-making process.

[0121] Example 8:

[0122] Based on the hepatobiliary surgery treatment plan screening system based on big data in Example 7, the second construction sub-module includes:

[0123] A preprocessing unit, configured to regard the distance between the first coordinate point and the second coordinate point of each reference hepatobiliary surgery treatment plan of the current patient as the first distance of each reference hepatobiliary surgery treatment plan of the current patient, regard the distance between the first coordinate point and the third coordinate point of each reference hepatobiliary surgery treatment plan of the current patient as the second distance of each reference hepatobiliary surgery treatment plan of the current patient, and regard the distance between the second coordinate point and the third coordinate point of each reference hepatobiliary surgery treatment plan of the current patient as the third distance of each reference hepatobiliary surgery treatment plan of the current patient;

[0124] A construction unit, configured to define the ordinal numbers of all the reference hepatobiliary surgery treatment plans of the current patient in ascending order from 1 according to the first distance of the reference hepatobiliary surgery treatment plan, obtain the ordinal number definition result of all the reference hepatobiliary surgery treatment plans of the current patient, and obtain an analysis matrix of the treatment plan for the current patient based on the first distance, second distance, third distance, and ordinal number definition result of all the reference hepatobiliary surgery treatment plans of the current patient, that is:

[0125]

[0126] where δ is the analysis matrix of the treatment plan for the current patient, and τ n1 is the value of the first distance of the reference hepatobiliary surgery treatment plan with the ordinal number defined as n for the current patient, and τ n2 is the value of the second distance of the reference hepatobiliary surgery treatment plan with the ordinal number defined as n for the current patient, and τ n3The value of the third distance of the reference hepatobiliary surgical treatment plan defined as the ordinal number n for the current patient, where n is the total number of all reference hepatobiliary surgical treatment plans for the current patient.

[0127] The beneficial effects of the above technology are as follows: According to all the plotted coordinate points of all the reference hepatobiliary surgical treatment plans of the current patient, a treatment plan analysis matrix of the current patient is obtained. This embodiment details a specific method for constructing the treatment plan analysis matrix of the current patient.

[0128] Example 9:

[0129] Based on the big data-based hepatobiliary surgical treatment plan screening system in Example 8, the screening module includes:

[0130] A screening priority value calculation sub-module, which is used to obtain the screening priority value of each reference hepatobiliary surgical treatment plan of the current patient based on the treatment plan analysis matrix of the current patient, that is:

[0131]

[0132] where μ is the screening priority value of the currently calculated reference hepatobiliary surgical treatment plan of the current patient, τ1 is the value of the first distance of the currently calculated reference hepatobiliary surgical treatment plan of the current patient, τ2 is the value of the second distance of the currently calculated reference hepatobiliary surgical treatment plan of the current patient, τ3 is the value of the third distance of the currently calculated reference hepatobiliary surgical treatment plan of the current patient, is the rank of the treatment plan analysis matrix of the current patient, σ1 is the standard deviation of the values of the first distances of all the reference hepatobiliary surgical treatment plans of the current patient, σ2 is the standard deviation of the values of the second distances of all the reference hepatobiliary surgical treatment plans of the current patient, σ3 is the standard deviation of the values of the third distances of all the reference hepatobiliary surgical treatment plans of the current patient, ln is the natural logarithm, and the value of the natural constant e is 2.718;

[0133] A screening sub-module, which is used to select the reference hepatobiliary surgical treatment plan with the largest screening priority value within all the reference hepatobiliary surgical treatment plans of the current patient as the best screened hepatobiliary surgical treatment plan for the current patient.

[0134] The beneficial effects of the above technology are as follows: According to the treatment plan analysis matrix of the current patient, the screening priority value of each reference hepatobiliary surgical treatment plan of the current patient is obtained, realizing the quantification of the priority degree of each reference hepatobiliary surgical treatment plan of the current patient as the best screened hepatobiliary surgical treatment plan. Finally, based on the screening priority values of all the reference hepatobiliary surgical treatment plans of the current patient, the best screened hepatobiliary surgical treatment plan for the current patient is obtained, realizing the screening of the most suitable hepatobiliary surgical treatment plan for the current patient in terms of comprehensive safety, effectiveness and economy.

[0135] Example 10:

[0136] The present invention provides a screening method for hepatobiliary surgery treatment plans based on big data, which is applied to any one of the hepatobiliary surgery treatment plan screening systems based on big data in Examples 1 to 9, with reference to Figure 2 , including:

[0137] S1: Based on all types of basic information of the current patient and a preset database, obtain all reference patients of the current patient, and based on all reference patients of the current patient, obtain all reference hepatobiliary surgery treatment plans of the current patient;

[0138] S2: Based on all types of treatment information of all reference hepatobiliary surgery treatment plans of the current patient, obtain the safety evaluation value, effectiveness evaluation value, and economic evaluation value of all reference hepatobiliary surgery treatment plans of the current patient;

[0139] S3: Based on the safety evaluation value, effectiveness evaluation value, and economic evaluation value of all reference hepatobiliary surgery treatment plans of the current patient, obtain all plotted coordinate points of each reference hepatobiliary surgery treatment plan of the current patient, and based on all plotted coordinate points of all reference hepatobiliary surgery treatment plans of the current patient, obtain the treatment plan analysis matrix of the current patient;

[0140] S4: Based on the treatment plan analysis matrix of the current patient, obtain the screening priority value of each reference hepatobiliary surgery treatment plan of the current patient, and based on the screening priority values of all reference hepatobiliary surgery treatment plans of the current patient, obtain the best screened hepatobiliary surgery treatment plan of the current patient.

[0141] The beneficial effects of the above technology are as follows: According to all types of treatment information of all reference hepatobiliary surgery treatment plans for the current patient, the safety evaluation value, effectiveness evaluation value, and economic evaluation value of all reference hepatobiliary surgery treatment plans for the current patient are obtained, realizing the separate quantification of the treatment safety, treatment effectiveness, and treatment economy of each reference hepatobiliary surgery treatment plan for the current patient. Furthermore, according to the safety evaluation value, effectiveness evaluation value, and economic evaluation value of all reference hepatobiliary surgery treatment plans for the current patient, all drawing coordinate points of each reference hepatobiliary surgery treatment plan for the current patient are obtained, facilitating the subsequent construction of the treatment plan analysis matrix for the current patient. Based on all the drawing coordinate points of all reference hepatobiliary surgery treatment plans for the current patient, the treatment plan analysis matrix for the current patient is obtained. Then, according to the treatment plan analysis matrix for the current patient, the screening priority value of each reference hepatobiliary surgery treatment plan for the current patient is obtained, realizing the quantification of the priority degree of each reference hepatobiliary surgery treatment plan for the current patient as the best screened hepatobiliary surgery treatment plan. Finally, according to the screening priority values of all reference hepatobiliary surgery treatment plans for the current patient, the best screened hepatobiliary surgery treatment plan for the current patient is obtained, realizing the screening of the most suitable hepatobiliary surgery treatment plan for the current patient in terms of comprehensive safety, effectiveness, and economy.

[0142] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention, and the present invention also intends to include these changes and modifications.

Claims

1. A screening system for hepatobiliary surgery treatment plans based on big data, characterized in that, Including: An acquisition module, configured to obtain all reference patients of the current patient based on all types of basic information of the current patient and a preset database, and obtain all reference hepatobiliary surgery treatment plans of the current patient based on all reference patients of the current patient; A processing module, configured to obtain a safety evaluation value, an effectiveness evaluation value, and an economy evaluation value of all reference hepatobiliary surgery treatment plans of the current patient based on all types of treatment information of all reference hepatobiliary surgery treatment plans of the current patient; A construction module, configured to obtain all plotted coordinate points of each reference hepatobiliary surgery treatment plan of the current patient based on the safety evaluation value, the effectiveness evaluation value, and the economy evaluation value of all reference hepatobiliary surgery treatment plans of the current patient, and obtain a treatment plan analysis matrix of the current patient based on all plotted coordinate points of all reference hepatobiliary surgery treatment plans of the current patient; A screening module, configured to obtain a screening priority value of each reference hepatobiliary surgery treatment plan of the current patient based on the treatment plan analysis matrix of the current patient, and obtain the best screened hepatobiliary surgery treatment plan of the current patient based on the screening priority values of all reference hepatobiliary surgery treatment plans of the current patient.

2. The screening system for hepatobiliary surgery treatment plans based on big data according to claim 1, wherein The acquisition module includes: A reference patient determination sub-module, configured to obtain all reference patients of the current patient based on all types of basic information of the current patient and a preset database; A plan acquisition sub-module, configured to use the hepatobiliary surgery treatment plans of each reference patient of the current patient extracted from the preset database as the reference hepatobiliary surgery treatment plans of the current patient.

3. The screening system for hepatobiliary surgery treatment plans based on big data according to claim 2, wherein The reference patient determination sub-module includes: A basic information acquisition unit, configured to obtain all types of basic information of the current patient, where all types of basic information include the nature of the lesion, the diameter length of the lesion, and the lesion location area; A reference patient determination unit, configured to use the corresponding patient as a reference patient of the current patient when all types of basic information of each patient stored in the preset database correspond to all types of basic information of the current patient.

4. The screening system for hepatobiliary surgery treatment plans based on big data according to claim 1, wherein The processing module includes: A preprocessing sub-module, configured to obtain all types of treatment information of all reference hepatobiliary surgery treatment plans of the current patient, where all types of treatment information include safety treatment information, effectiveness treatment information, and economy treatment information, and the safety treatment information includes the postoperative recovery time, the postoperative liver function evaluation index value, and the intraoperative blood loss, the effectiveness treatment information includes the surgical resection rate and the score assigned to the improvement of postoperative symptoms, and the economy treatment information includes the surgical cost, the length of hospital stay, and the subsequent treatment cost; A processing sub-module, configured to obtain a safety evaluation value, an effectiveness evaluation value, and an economy evaluation value of all reference hepatobiliary surgery treatment plans of the current patient based on all types of treatment information of all reference hepatobiliary surgery treatment plans of the current patient.

5. The screening system for hepatobiliary surgery treatment plans based on big data according to claim 4, wherein, The processing sub-module includes: A first processing unit, configured to obtain a safety evaluation value of each reference hepatobiliary surgery treatment plan of the current patient based on the safety treatment information of all reference hepatobiliary surgery treatment plans of the current patient, that is: Among them, α is the safety evaluation value of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, A is the postoperative recovery time of the safety treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, and A max is the maximum value of the postoperative recovery times of the safety treatment information of all reference hepatobiliary surgery treatment plans for the current patient, B is the postoperative liver function evaluation index value of the safety treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, and B max is the maximum value of the postoperative liver function evaluation index values of the safety treatment information of all reference hepatobiliary surgery treatment plans for the current patient, C is the intraoperative blood loss of the safety treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, and C max is the maximum value of the intraoperative blood losses of the safety treatment information of all reference hepatobiliary surgery treatment plans for the current patient, ln is the natural logarithm, and the value of the natural constant e is 2.718; A second processing unit, configured to obtain an effectiveness evaluation value for each reference hepatobiliary surgical treatment plan of the current patient based on the effectiveness treatment information of all reference hepatobiliary surgical treatment plans of the current patient, that is: Among them, β is the effectiveness evaluation value of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, D is the surgical resection rate of the effectiveness treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, D max is the maximum value among the surgical resection rates of the effectiveness treatment information of all reference hepatobiliary surgery treatment plans for the current patient, E is the score assigned to the postoperative symptom improvement of the effectiveness treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, E max is the maximum value among the scores assigned to the postoperative symptom improvement of the effectiveness treatment information of all reference hepatobiliary surgery treatment plans for the current patient; A third processing unit, configured to obtain an economy evaluation value for each reference hepatobiliary surgical treatment plan of the current patient based on the economy treatment information of all reference hepatobiliary surgical treatment plans of the current patient.

6. The screening system for hepatobiliary surgery treatment plan based on big data according to claim 5, wherein The method by which the third processing unit obtains an economy evaluation value for each reference hepatobiliary surgical treatment plan of the current patient based on the economy treatment information of all reference hepatobiliary surgical treatment plans of the current patient includes: Among them, γ is the economic evaluation value of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, F is the surgical cost of the economic treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, F max is the maximum value among the surgical costs of the economic treatment information of all reference hepatobiliary surgery treatment plans for the current patient, G is the length of hospital stay of the economic treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, G max is the maximum value among the lengths of hospital stay of the economic treatment information of all reference hepatobiliary surgery treatment plans for the current patient, H is the follow-up treatment cost of the economic treatment information of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, H max is the maximum value among the follow-up treatment costs of the economic treatment information of all reference hepatobiliary surgery treatment plans for the current patient.

7. The screening system for hepatobiliary surgery treatment plans based on big data according to claim 1, wherein A construction module, including: A first construction sub-module, configured to use the safety evaluation value of each reference hepatobiliary surgical treatment plan of the current patient as the abscissa value, and the effectiveness evaluation value of the corresponding reference hepatobiliary surgical treatment plan of the current patient as the ordinate value, to obtain a first coordinate point of the corresponding reference hepatobiliary surgical treatment plan of the current patient; use the safety evaluation value of each reference hepatobiliary surgical treatment plan of the current patient as the abscissa value, and the economy evaluation value of the corresponding reference hepatobiliary surgical treatment plan of the current patient as the ordinate value, to obtain a second coordinate point of the corresponding reference hepatobiliary surgical treatment plan of the current patient; use the effectiveness evaluation value of each reference hepatobiliary surgical treatment plan of the current patient as the abscissa value, and the economy evaluation value of the corresponding reference hepatobiliary surgical treatment plan of the current patient as the ordinate value, to obtain a third coordinate point of the corresponding reference hepatobiliary surgical treatment plan of the current patient; obtain the first coordinate point, the second coordinate point, and the third coordinate point of each reference hepatobiliary surgical treatment plan of the current patient, and use the first coordinate point, the second coordinate point, and the third coordinate point of each reference hepatobiliary surgical treatment plan of the current patient as all the plotted coordinate points of each reference hepatobiliary surgical treatment plan of the current patient; A second construction sub-module, configured to obtain a treatment plan analysis matrix of the current patient based on all the plotted coordinate points of all reference hepatobiliary surgical treatment plans of the current patient.

8. The screening system for hepatobiliary surgery treatment plans based on big data according to claim 7, characterized in that, The second construction sub-module includes: A preprocessing unit, configured to use the distance between the first coordinate point and the second coordinate point of each reference hepatobiliary surgical treatment plan of the current patient as the first distance of each reference hepatobiliary surgical treatment plan of the current patient; use the distance between the first coordinate point and the third coordinate point of each reference hepatobiliary surgical treatment plan of the current patient as the second distance of each reference hepatobiliary surgical treatment plan of the current patient; use the distance between the second coordinate point and the third coordinate point of each reference hepatobiliary surgical treatment plan of the current patient as the third distance of each reference hepatobiliary surgical treatment plan of the current patient; A construction unit is used to define the ordinal numbers starting from 1 for all the reference hepatobiliary surgery treatment plans of the current patient in the order of the first distance from large to small according to the reference hepatobiliary surgery treatment plan, obtain the ordinal number definition result of all the reference hepatobiliary surgery treatment plans of the current patient, and obtain the treatment plan analysis matrix of the current patient based on the first distance, second distance, third distance and ordinal number definition result of all the reference hepatobiliary surgery treatment plans of the current patient, that is: Among them, δ is the treatment plan analysis matrix of the current patient, and τ n1 is the value of the first distance of the reference hepatobiliary surgery treatment plan with the ordinal number defined as n for the current patient, and τ n2 is the value of the second distance of the reference hepatobiliary surgery treatment plan with the ordinal number defined as n for the current patient, and τ n3 is the value of the third distance of the reference hepatobiliary surgery treatment plan with the ordinal number defined as n for the current patient, and n is the total number of all reference hepatobiliary surgery treatment plans for the current patient.

9. The screening system for hepatobiliary surgery treatment plans based on big data according to claim 8, characterized in that A screening module, including: A screening priority value calculation sub-module is used to obtain the screening priority value of each reference hepatobiliary surgery treatment plan of the current patient based on the treatment plan analysis matrix of the current patient, that is: Among them, μ is the screening priority value of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, τ1 is the numerical value of the first distance of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, τ2 is the numerical value of the second distance of the currently calculated reference hepatobiliary surgery treatment plan for the current patient, τ3 is the numerical value of the third distance of the currently calculated reference hepatobiliary surgery treatment plan for the current patient. is the rank of the treatment plan analysis matrix for the current patient, σ1 is the standard deviation of the numerical values of the first distances of all reference hepatobiliary surgery treatment plans for the current patient, σ2 is the standard deviation of the numerical values of the second distances of all reference hepatobiliary surgery treatment plans for the current patient, σ3 is the standard deviation of the numerical values of the third distances of all reference hepatobiliary surgery treatment plans for the current patient, ln is the natural logarithm, and the value of the natural constant e is 2.

718. A screening sub-module is used to regard the reference hepatobiliary surgery treatment plan with the largest screening priority value among all the reference hepatobiliary surgery treatment plans of the current patient as the best screened hepatobiliary surgery treatment plan of the current patient.

10. A screening method for hepatobiliary surgery treatment plans based on big data, characterized in that, Applied to a big data-based hepatobiliary surgery treatment plan screening system as described in any one of claims 1 to 9, including: S1: Based on all the class-based information of the current patient and the preset database, obtain all the reference patients of the current patient, and based on all the reference patients of the current patient, obtain all the reference hepatobiliary surgery treatment plans of the current patient; S2: Based on all the class-based treatment information of all the reference hepatobiliary surgery treatment plans of the current patient, obtain the safety evaluation value, effectiveness evaluation value and economy evaluation value of all the reference hepatobiliary surgery treatment plans of the current patient; S3: Based on the safety evaluation value, effectiveness evaluation value and economy evaluation value of all the reference hepatobiliary surgery treatment plans of the current patient, obtain all the plotted coordinate points of each reference hepatobiliary surgery treatment plan of the current patient, and based on all the plotted coordinate points of all the reference hepatobiliary surgery treatment plans of the current patient, obtain the treatment plan analysis matrix of the current patient; S4: Based on the treatment plan analysis matrix of the current patient, obtain the screening priority value of each reference hepatobiliary surgery treatment plan of the current patient, and based on the screening priority values of all the reference hepatobiliary surgery treatment plans of the current patient, obtain the best screened hepatobiliary surgery treatment plan of the current patient.

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