Construction method of lower limb arteriosclerosis obliterans model

Abstract

The invention provides a construction method of a lower limb arteriosclerosis obliterans model, and belongs to the field of model construction. The problem of low construction efficiency of the lower limb arteriosclerosis obliterans model is solved; the method specifically comprises the following steps: S1, acquiring pathological data of a patient; s2, acquiring historical medical records of a target hospital, performing primary processing on the historical medical records, determining main observation indexes of a patient, and constructing an equation F (1); s3, carrying out secondary analysis on the historical medical record, and constructing an equation F (2); according to the equation F (1) and the equation F (2), ankle systolic pressure changes and brachial artery systolic pressure changes of the patient are analyzed; s4, extracting a lesion picture in the medical examination report of the patient, and constructing a three-dimensional model of the lower limbs of the patient; summarizing and feeding back the pre-diagnosis reports; according to the method, the mathematical model and the three-dimensional model of the lower limb arteriosclerosis obliterans are constructed by acquiring and analyzing the related information of the patient with the lower limb arteriosclerosis obliterans, and the medical efficiency of the lower limb arteriosclerosis obliterans

Description

Technical Field

[0001] A method for constructing a model of lower extremity arteriosclerosis obliterans according to the present invention relates to the field of model construction. Background Art

[0002] The existing methods for constructing a model of lower extremity arteriosclerosis obliterans have the following deficiencies:

[0003] Strong data dependence: For the existing mathematical models of lower extremity arteriosclerosis obliterans, their accuracy and reliability highly depend on the integrity of the input data; if the data is biased or missing, the construction results of the model will be affected; at the same time, there is too much data used for modeling the existing mathematical models of lower extremity arteriosclerosis obliterans, and most of the data has no strong correlation with the symptom changes of lower extremity arteriosclerosis obliterans, and too much data will also cause data redundancy and overfitting of the model, wasting computing resources.

[0004] Result uncertainty: Most of the existing models of lower extremity arteriosclerosis obliterans are models constructed based on the medical records of a single patient in the past. Such models can provide certain prediction and guidance, but their results also have a certain degree of uncertainty; for example, the same condition of lower extremity arteriosclerosis obliterans may be affected by factors such as different individual differences, physical conditions, and lesion degrees of patients, making the interpretability of the model poor. It is necessary to continuously increase and update the data, and regularly retrain and validate the model to ensure its accuracy and reliability. This processing method will limit the wide application of the model in clinical practice and is not conducive to the medical work of patients with lower extremity arteriosclerosis obliterans.

[0005] High cost: Constructing and maintaining a model of lower extremity arteriosclerosis obliterans requires a large amount of funds and resources; for example, surgical instruments, detection reagents, etc.; three-dimensional models and mathematical models require the support of high-performance computers and professional software developers, and these costs may limit the wide application and in-depth research of the model. Summary of the Invention

[0006] Aiming at the deficiencies of the existing technology, the purpose of the present invention is to provide a method for constructing a model of lower extremity arteriosclerosis obliterans, aiming to solve the problem of low efficiency in constructing a model of lower extremity arteriosclerosis obliterans.

[0007] To achieve the above purpose, the present invention is implemented through the following technical solutions: A method for constructing a model of lower extremity arteriosclerosis obliterans includes:

[0008] Step S1: Obtain the medical examination report of the patient, extract the blood lipid content, blood glucose content, inflammation indicator content of the patient, and the blood flow velocity of the lower extremity artery to obtain the pathological data of the patient;

[0009] Step S2: Obtain the historical medical records of the target hospital; perform a primary processing on the historical medical records, analyze the influence of various physiological indicators on the ankle-brachial index, and combine with pathological data to determine the main observation indicators of the patient; based on Poiseuille's law, construct a mathematical equation for the arterial blood flow velocity at the lower limb lesion site, the ankle systolic blood pressure, and the brachial artery systolic blood pressure, and obtain Equation F(1);

[0010] Step S3: Conduct a secondary analysis on the historical medical records, analyze the mathematical relationship between the femoral artery blood flow velocity and the heart rate of the patient, and construct Equation F(2); perform a time series analysis on the ankle-brachial index of all patients in the historical medical records, and combine with pathological data to estimate the ankle-brachial index of the patient. Then, according to Equation F(1) and Equation F(2), analyze the changes in the ankle systolic blood pressure and the brachial artery systolic blood pressure of the patient;

[0011] Step S4: Extract the lesion pictures from the patient's medical examination report, and import them into the modeling software. Select all the continuous tomographic image data in DICOM format to generate the three-view drawings of the patient's lower limbs; according to the three-view drawings of the patient's lower limbs, perform a threshold analysis on the continuous images, extract the internal tissues of the patient's lower limbs, render and extract the femoral artery of the lower limb tissues to obtain the three-dimensional model of the patient's lower limbs; use the main observation indicators of the patient, the changes in the ankle systolic blood pressure and the brachial artery systolic blood pressure, and the three-dimensional model of the lower limbs as a preliminary diagnosis report and feedback it to the physician.

[0012] Further, the specific steps of Step S2 are as follows:

[0013] Step S21: Denote the blood lipid content of the patient as bfa, the blood glucose content as bgo, and the inflammation indicator content as hle;

[0014] Count the number of patients in the historical medical records, denoted as pa; obtain the treatment times ti(1)~ti( pa ) of all patients;

[0015] Step S22: Analyze and calculate the correlation coefficients bf (1) ~bf (pa) of the blood lipid content of the 1st to the pa-th patients with respect to the ankle-brachial index, and calculate the average value abf of bf (1) ~bf (pa) ;

[0016] The correlation coefficients bg (1) ~bg (pa) of the blood glucose content with respect to the ankle-brachial index, and calculate the average value abg of the calculated values;

[0017] The correlation coefficients hl (1) ~hl (pa) of the inflammation indicator content with respect to the ankle-brachial index, and calculate the average value ahl of the calculated values;

[0018] Step S23: Extract bf(1) ~bf (pa) The maximum value bf in (max) , the minimum value bf(min), calculate the influence coefficient qbf of blood lipid content on ankle-brachial index:

[0019]

[0020] Extract bg (1) ~bg (pa) The maximum value bg in (max) , the minimum value bg (min) , calculate the influence coefficient qbg of blood glucose content on ankle-brachial index:

[0021]

[0022] Extract hl (1) ~hl (pa) The maximum value hl in (max) , the minimum value hl (min) , calculate the influence coefficient qhl of inflammatory indicator content on ankle-brachial index:

[0023]

[0024] Among them, bf (z) , bg (z) and hl (z) respectively represent the correlation coefficient of blood lipid content on ankle-brachial index, the influence coefficient of blood glucose content on ankle-brachial index, and the influence coefficient of inflammatory indicator content on ankle-brachial index corresponding to the z-th patient.

[0025] Furthermore, the step S2 further includes:

[0026] Step S24: Obtain the blood lipid content [bfl, bfm], blood glucose content [bgl, bgm], and inflammatory indicator content [hll, hlm] of a healthy person;

[0027] Calculate the influence coefficient bb of the patient's blood lipid on the ankle-brachial index (1) :

[0028] If bfa < bfl, then bb (1) The calculation formula of is:

[0029] If bfa > bfm, then bb (1) The calculation formula of is:

[0030] If bfa ∈ [bfl, bfm], then bb (1) The value of is qbf;

[0031] Calculate the influence coefficient bb of the patient's blood glucose on the ankle-brachial index (2) :

[0032] If bga < bgl, then bb (2) The calculation formula is:

[0033] If bga > bgm, then bb (2) The calculation formula is:

[0034] If bga ∈ [bgl, bgm], then bb (2) The value is qbg;

[0035] Calculate the influence coefficient bb of the patient's inflammation indicator on the ankle-brachial index (3) :

[0036] If hla < hll, then bb (3) The calculation formula is:

[0037] If hla > hlm, then bb (3) The calculation formula is:

[0038] If hla ∈ [hll, hlm], then bb (3) The value is qhl;

[0039] Compare bb (1) , bb (2) and bb (3) Select the largest or tied largest influence coefficient among bb (1) , bb (2) and bb(3) as the key coefficient;

[0040] Take the physiological index corresponding to the key coefficient as the main observation index of the patient;

[0041] Step S25: Based on Poiseuille's law, construct a mathematical equation for the arterial blood flow velocity at the lesion site of the femoral artery in the lower limb and the ankle systolic blood pressure and the brachial artery systolic blood pressure to obtain equation F(1), and enter step S3.

[0042] Furthermore, the working steps of step S22 are as follows:

[0043] Step S221: Take ti (1) as til, and calculate the correlation coefficient bf (1) of the lipid content of the first patient with respect to the ankle-brachial index, the correlation coefficient bg (1) of the blood glucose content with respect to the ankle-brachial index, and the correlation coefficient hl (1) of the inflammation indicator content with respect to the ankle-brachial index;

[0044] Obtain the average blood lipid content bf of the first user within the first to til days (1，1) ~bf(1, til), the average blood glucose content bg (1，1) ~bg (1，til) , the average inflammatory indicator content hl(1, 1)~hl (1，til) , the ankle-brachial index br (1，1) ~br (1，til) ;

[0045] Calculate br (1，1) ~br (1，til) The sum abr;

[0046] Step S222: According to bf (1，1) ~bf (1，til) And br (1，1) ~br (1，til) Calculate bf (1) ;

[0047] Step S223: According to bg (1，1) ~bg (1，til) And br (1，1) ~br (1，til) Calculate bg (1) ; According to hl (1，1) ~hl (1，til) And br (1，1) ~br (1，til) Calculate hl(1);

[0048] Step S224: Calculate the correlation coefficient bf of the blood lipid content of the second to pa patients with respect to the ankle-brachial index (2) ~bf (pa) ;

[0049] The correlation coefficient bg of the blood glucose content with respect to the ankle-brachial index (2) ~bg (pa) ;

[0050] The correlation coefficient hl of the inflammatory indicator content with respect to the ankle-brachial index (2) ~hl (pa) .

[0051] Furthermore, the specific steps of the said Step S222 are as follows:

[0052] Step S2221: Denote the weighted coefficient of the blood lipid content of the first patient with respect to the ankle-brachial index within the first to til days as λbf (1) ~λbf (til) , and the offset coefficient as vbf;

[0053] Step S2222: Let λbf after k updates(1) ~λbf (til) The value is λbf (k) (1)~λbf (k) (til) ;

[0054] bf after the k - th update (1，1) The value of bf (k) (1，1) :

[0055] bf( k )( 1,1 ) = bf( 1,1 )×λbf( k )(1);

[0056] Similarly, the value of bf after the k - th update (1，til) The value of bf (k) (1，til) :

[0057] bf( k )( 1,til ) = bf( 1,til )×λbf( k )( til );

[0058] Step S2223: Calculate the sum gbf of bf (1，1) ~bf (1，til) and the average value abf(1); (1) Calculate the sum Abf of bf

[0059] (k) (1, 1)~bf (k) (1，til) and the average value Gbf (k) and the variance Sbf (k) ; (k) ;

[0060] Calculate the covariance Cov after k - th update (bf) (k) (k) ;

[0061]

[0062] where bf (1，y) represents the average blood lipid content of the first patient on the y - th day; bf (k) (1, y) represents the value of bf after the k - th update (1，y) ;

[0063] Define the calculation formula A - 1 - 1:

[0064] where Aλ (k) represents the combined weight after k - th update;

[0065] Step S2224: Update Aλ (k) until the relational expression A-1-2 is satisfied, and obtain the combined weight Bλ;

[0066] Relational expression A-1-2: |Aλ (k) - Aλ (k+1) | ≤ ε; where Aλ (k+1) represents the combined weight of the (k + 1)th update, and ε represents the allowable error value;

[0067] Step S2225: Denote the weighting coefficient of the first patient on the yth day as λbf (y) , and define the calculation formula A-1-3:

[0068]

[0069] Calculate the weighting coefficient λbf (1) ~λbf (til) ;

[0070] Calculate the offset coefficient vbf:

[0071]

[0072] Step S2226: Define the matrix CA: Matrix CB:

[0073] Calculate the path coefficient β (bf) :

[0074] β (bf) = [[(CB * CB T ) -1 * CB] T * CA;

[0075] The correlation coefficient bf of blood lipid content with respect to ankle-brachial index (1) :

[0076]

[0077] Furthermore, the specific steps of the said Step S25 are as follows:

[0078] Step S251: Let the total length of the lower limb artery be L (ar) ;

[0079] The length of the stenotic segment of the lower limb artery is L (st) , and the blood vessel radius is r (st) ;

[0080] The length of the normal segment of the lower limb artery is L (nr) , and the blood vessel radius is r(nr) ; where, L (nr) = L (ar) - L (st) (Equation B-1);

[0081] Record the blood viscosity as η, and assume the blood flow rate of the lower limb artery per unit time is Q (bo) ;

[0082] Step S252: Record the ankle systolic blood pressure as P (br) , and the brachial artery systolic blood pressure as P (an) ;

[0083] Calculate the pressure difference ΔP, ΔP = P (br) - P (an) (Equation B-2);

[0084] Construct Equation B-3:

[0085] where, R (to) represents the resistance during blood transportation in the lower limb artery system;

[0086] Step S253: Assume the blood flow velocity of the stenotic segment of the lower limb femoral artery is v(st):

[0087]

[0088] Substitute Equations B-1 to B-3 into v (st) to obtain Equation B-4:

[0089]

[0090] Expand the parameters in Equation B-4 to obtain Equation B-5:

[0091]

[0092] Step S254: Introduce the ankle-brachial index ABI:

[0093] Substitute ABI into Equation B-5 to obtain Equation B-6:

[0094]

[0095] Take Equation B-6 as Equation F(1).

[0096] Furthermore, the specific steps of Step S3 are as follows:

[0097] Step S31: Analyze the mathematical relationship between the blood flow velocity and heart rate of the femoral artery of all patients and construct Equation F(2);

[0098] Step S32: Based on the ARIMA(1,1,1) model, perform time series analysis on the ankle-brachial index of the 1st to the pa-th patients during the treatment time to obtain the ankle-brachial index change equation, denoted as equation F(3);

[0099] Obtain the ankle systolic blood pressure of the patient, denoted as Pba, and the brachial artery systolic blood pressure, denoted as Pak; calculate the ankle-brachial index of the patient, ABIi = Pba / Pak;

[0100] Obtain the current femoral artery blood flow velocity of the patient, denoted as vd, and the current heart rate, denoted as her;

[0101] Substitute ABIi into equation F(3) to estimate the estimated values of the patient's ankle-brachial index in the next three days: qABI (1) 、qABI (2) and qABI (3) ;

[0102] Substitute her into equation F(2) to calculate the expected femoral artery blood flow velocity of the patient, qVo;

[0103] Step S33: Determine whether (2×qABI (1) )-(qABI (2) +qABI (3) ) ≤ ε holds; where ε represents the error value;

[0104] If it holds, it indicates that the patient's condition has improved, and skip the subsequent steps;

[0105] If it does not hold, it indicates that the patient's condition has deteriorated, and analyze the change trends of the ankle systolic blood pressure and the brachial artery systolic blood pressure.

[0106] Furthermore, the subsequent steps of step S33 are as follows:

[0107] Step S34: Substitute Pak and qABI (1) ~qABI (3) into equation F(1) to calculate the first estimated values of the patient's femoral artery blood flow velocity in the next three days, aVo (1) 、aVo (2) and aVo (3) ;

[0108] Calculate the estimated values of the patient's ankle systolic blood pressure in the next three days: bPba (1) 、bPba (2) and bPba(3);

[0109] Substitute bPba (1) ~bPba (3) and ABIi into equation F(1) to calculate the second estimated values of the patient's femoral artery blood flow velocity in the next three days, bVo (1), bVo (2) and bVo (3) ;

[0110] Step S35: Define relation C-4:

[0111] |(aVo (1) + aVo (2) + aVo (3) ) - (3 × qVo)| ≥ |(bVo (1) + bVo (2) + bVo (3) ) - (3 × qVo)|

[0112] Judge whether relation C-4 holds;

[0113] If relation C-4 holds, it indicates that the patient's ankle systolic blood pressure is abnormal. Compare the magnitudes of (aVo (1) + aVo(2)) and (aVo (2) + aVo (3) );

[0114] If (aVo (1) + aVo (2) ) ≥ (aVo (2) + aVo (3) ), it indicates that the patient's ankle systolic blood pressure has decreased;

[0115] If (aVo (1) + aVo (2) ) < (aVo (2) + aVo (3) ), it indicates that the patient's ankle systolic blood pressure has increased;

[0116] If relation C-4 does not hold, it indicates that the patient's brachial artery systolic blood pressure is abnormal. Compare the magnitudes of (bVo (1) + bVo (2) ) and (bVo (2) + bVo (3) );

[0117] If (bVo (1) + bVo (2) ) ≥ (bVo (2) + bVo (3) ), it indicates that the patient's brachial artery systolic blood pressure has decreased;

[0118] If (bVo (1) + bVo (2) ) < (bVo (2) + bVo (3) ), it indicates that the patient's brachial artery systolic blood pressure has increased.

[0119] Further, the specific steps of step S31 are as follows:

[0120] Step S311: Obtain the femoral artery blood flow velocity of a healthy person and record it as Vo;

[0121] Record the time as t, and record the femoral artery blood flow velocity of the patient at time t as v(t); record the patient's heart rate as hr, and record the cardiac cycle as Th, Th = 60 / hr;

[0122] Based on the Fourier series of a single harmonic, construct formula C-1:

[0123]

[0124] Among them, aa represents the Fourier coefficient of the cosine term, bb represents the Fourier coefficient of the sine term, and the initial values of aa and bb are both 1;

[0125] Step S312: Obtain the treatment times ti (1) ~ti (pa) ;

[0126] Obtain the average heart rate hr (1) ~hr (1，1) ~hr (1，ti(1)) and the average femoral artery blood flow velocity vt (1，1) ~vt (1，ti(1)) ;

[0127] Similarly, for the p-th patient, the average heart rate hr (pa) ~hr (pa，1) ~hr (pa，ti(pa)) and the average femoral artery blood flow velocity vt (pa，1) ~vt (pa，ti (pa)).

[0128] 10. A method for constructing a model of lower limb arteriosclerosis obliterans according to claim 9, wherein the subsequent steps of step S312 are as follows:

[0129] Step S313: For the m-th patient, the treatment time is ti (m) , the average heart rate of the m-th patient on the n-th day is hr (m，n) and the average femoral artery blood flow velocity is vt (m，n) ;

[0130] Record the Fourier coefficient of the cosine term corresponding to the m-th patient as aa (m) , and define calculation formula C-2:

[0131]

[0132] Calculate the cosine-term Fourier coefficients aa corresponding to the 1st to the pa-th patients (1) ~aa (pa) ;

[0133] Step S314: Denote the sine-term Fourier coefficients corresponding to the m-th patient as bb (m) , and define calculation formula C-3:

[0134]

[0135] Calculate the sine-term Fourier coefficients bb corresponding to the 1st to the pa-th patients (1) ~bb (pa) ;

[0136] Calculate the averages of aa (1) ~aa (pa) and bb (1) ~bb (pa) respectively, and substitute them into formula C-1 to obtain equation F(2).

[0137] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0138] Guiding clinical treatment: The mathematical model constructed by the present invention can integrate various risk factors, such as the degree of lower limb artery calcification, blood lipid, blood condition, changes in ankle systolic blood pressure, brachial artery systolic blood pressure, etc., analyze the changes of various physiological indicators of patients, provide reference information for clinicians, enable doctors to understand the pathological process and lesion degree of patients, and doctors can formulate more personalized treatment plans, improve the treatment effect, and reduce the risk of complications.

[0139] Predicting disease progression: The mathematical model constructed by the present invention can analyze various physiological indicators in patients in the short term, predict the changes in the main ankle systolic blood pressure and brachial artery systolic blood pressure that affect lower limb arteriosclerosis obliterans, help doctors detect and intervene in the development trend of lower limb arteriosclerosis obliterans in a timely manner, and improve the treatment effect of patients.

[0140] Providing a research platform: The lower limb arteriosclerosis obliterans model provides an important research platform for scientific research personnel, enabling them to deeply explore the pathogenesis and pathological process of the disease; through the model, scientific research personnel can observe the progression and changes of the disease under different conditions, and provide a scientific basis for formulating effective treatment strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0141] By reading the following detailed description of the non-restrictive embodiments with reference to the accompanying drawings, other features, objectives, and advantages of the present invention will become more obvious:

[0142] Figure 1 It is a schematic diagram of the method of the present invention;

[0143] Figure 2 Schematic diagram of the mathematical model of the present invention;

[0144] Figure 3 Schematic diagram of the three-dimensional model of the lower limb of the present invention. Specific implementation manners

[0145] To make the above objects, features and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific implementation manners.

[0146] Please refer to Figure 1 and Figure 3 , a method for constructing a model of lower limb arteriosclerosis obliterans includes:

[0147] Step S1: Obtain the medical examination report of a patient with (lower limb arteriosclerosis obliterans), and extract the blood lipid content, blood glucose content, inflammation indicator content in the patient's (blood) and the blood flow velocity of the lower limb artery to obtain the pathological data of the patient;

[0148] Step S2: (Construct a mathematical model of the change of the patient's physiological indexes) Obtain the historical medical records of the target hospital; perform a first processing on the historical medical records, analyze the influence of various physiological indexes on the ankle-brachial index, and combine with the pathological data to determine the main observation indexes of the patient; based on Poiseuille's law, construct a mathematical equation for the arterial blood flow velocity at the lower limb lesion site of a patient with (lower limb arteriosclerosis obliterans) and the ankle systolic pressure and the brachial artery systolic pressure to obtain Equation F(1);

[0149] It should be noted that the "target hospital" in the present invention refers to: a municipal hospital that uses the present invention (a method for constructing a model of lower limb arteriosclerosis obliterans) to construct a "model of lower limb arteriosclerosis obliterans";

[0150] Please refer to Figure 2 , the specific steps of Step S2 are as follows:

[0151] Step S21: Obtain the medical records related to "(lower limb arteriosclerosis obliterans)" in the target hospital as historical medical records; count the number of patients in the historical medical records, denoted as pa;

[0152] Obtain the treatment time of the 1st to the pa-th patients, denoted as ti (1) ~ti (pa) (unit: days);

[0153] Denote the blood lipid content in the patient's (blood) as bfa, the blood glucose content as bgo, and the inflammation indicator content as hle;

[0154] Step S22: Analyze and calculate the correlation coefficient bf of the blood lipid content corresponding to the 1st to the pa-th patients in the (historical medical records) with respect to the ankle-brachial index (1) ~bf(pa) , calculate bf (1) ~bf (pa) and calculate the average value abf of bf;

[0155] (In blood) the correlation coefficient bg of blood glucose content with respect to the ankle-brachial index (1) ~bg (pa) , calculate the average value abg;

[0156] (In blood) the correlation coefficient hl of the inflammation indicator content with respect to the ankle-brachial index (1) ~hl (pa) , calculate the average value ahl;

[0157] Step S221: Take ti (1) as til, and calculate the correlation coefficient bf of the blood lipid content (in the historical medical record) of the first patient with respect to the ankle-brachial index (1) , the correlation coefficient bg of the blood glucose content (in blood) with respect to the ankle-brachial index (1) and the correlation coefficient hl of the inflammation indicator content (in blood) with respect to the ankle-brachial index (1) ;

[0158] Obtain the average blood lipid content bf(1, 1)~bf (in blood) of the first user from the 1st to the tilth day, (1，til) the average blood glucose content bg (1，1) ~bg (1，til) , the average inflammation indicator content hl (1，1) ~hl (1，til) , the ankle-brachial index br (1，1) ~br (1，til) ;

[0159] Calculate the sum abr of br (1，1) ~br (1，til) ;

[0160] Step S222: According to bf (1，1) ~bf (1，til) and br (1，1) ~br (1，til) , calculate bf (1) ;

[0161] Step S2221: Denote the weighted coefficient of the blood lipid content (in the historical medical record) of the first patient from the 1st to the tilth day with respect to the ankle-brachial index as λbf (1) ~λbf (til) , and denote the offset coefficient as vbf;

[0162] λbf (1) ~λbf (til) The initial value of λbf is 1, and the initial value of vbf is 0;

[0163] Step S2222: Calculate λbf (1) ~λbf (til) and the specific values of vbf;

[0164] Let the value of λbf (1) ~λbf (til) after the k-th update be λbf (k) (1) ~λbf (k) (til); (k is a natural number);

[0165] The value of bf after the k-th update (1，1) is bf (k) (1，1) bf (k) (1，1) = bf (1，1) ×λbf(k)(1);

[0166] The value of bf after the k-th update (1，2) is bf (k) (1，2) bf (k) (1，2) = bf (1，2) ×λbf(k)(2);

[0167] And so on, the value of bf after the k-th update (1，til) is bf (k) (1，til) bf (k) (1，til) = bf (1，til) ×λbf (k) (til) ;

[0168] Step S2223: Calculate the sum gbf (1，1) ~bf (1，til) and the average abf(1); (1) Calculate the sum Abf

[0169] of bf (k) (1，1) ~bf (k) (1，til) the average Gbf (k) and the variance Sbf (k) ; (k) ;

[0170] Calculate the k-th update covariance Cov (1，1) ~bf (1，til) with respect to bf (k) (1，1) ~bf (k) (1，til) of bf (bf)(k) ;

[0171]

[0172] wherein, bf (1，y) represents the average blood lipid content in the blood of the first patient on the y-th day (in the historical medical record); bf (k) (1，y) represents the value of bf (1，y) after k updates; the value range of y is: 1 to til;

[0173] Define calculation formula A-1-1:

[0174] wherein, Aλ (k) represents the combined weight of k updates;

[0175] Step S2224: Set the value of k to 1, and update Aλ (k) (according to the rules corresponding to steps S2421 to S2423) until the relational expression A-1-2 is satisfied;

[0176] The relational expression A-1-2 is: |Aλ (k) - Aλ (k+1) | ≤ ε; wherein, Aλ (k+1) represents the combined weight of the (k + 1)-th update; ε represents the allowable error value; (the value of ε is 0.01, and customers or relevant technical personnel can adjust the value of ε according to actual needs)

[0177] Record the combined weight that satisfies the relational expression A-1-2 as Bλ;

[0178] Step S2225: Denote the weighted coefficient of the blood lipid content of the first patient on the y-th day (in the blood) with respect to the ankle-brachial index as λbf (y) , and define calculation formula A-1-3:

[0179]

[0180] (According to calculation formula A-1-3) Calculate the weighted coefficients λbf (1) ~λbf (til) of the blood lipid content of the first patient on the 1st to til-th days (in the blood) with respect to the ankle-brachial index;

[0181] Calculate the offset coefficient vbf:

[0182]

[0183] Step S2226: Define a (til×1) empty matrix and fill it in sequentially with bf (1，1) ~bf (1，til)and br (1，1) ~br (1，til) to obtain matrix CA and matrix CB:

[0184] Matrix CA: Matrix CB:

[0185] Calculate the path coefficient β of the blood lipid content corresponding to the first patient (in the historical medical records) with respect to the ankle-brachial index (bf) : β (bf) = [[(CB * CB T ) -1 * CB] T * CA; where T represents the transpose of the matrix, * represents matrix multiplication, and -1 represents the inverse of the matrix;

[0186] Calculate the correlation coefficient bf of the blood lipid content corresponding to the first patient (in the historical medical records) with respect to the ankle-brachial index (1) :

[0187]

[0188] Step S223: Repeat the same steps of bf (1) According to bg (1，1) ~bg (1，til) and br (1，1) ~br (1，til) Calculate bg (1) ; According to hl (1，1) ~hl (1，til) and br(1, 1)~br (1，til) Calculate hl (1) ;

[0189] Step S224: Repeat the same steps of calculating bf (1) 、bg (1) hl (1) to calculate the correlation coefficients bf of the blood lipid content corresponding to the 2nd to pa-th patients (in the historical medical records) with respect to the ankle-brachial index (2) ~bf (pa) ;

[0190] (in the blood) The correlation coefficient bg of the blood glucose content with respect to the ankle-brachial index (2) ~bg (pa) ;

[0191] (in the blood) The correlation coefficient hl of the inflammatory indicator content with respect to the ankle-brachial index (2) ~hl(pa);

[0192] Step S23: Extract the maximum value bf in bf (1) ~bf (pa) ​(max) , the minimum value bf(min), calculate the influence coefficient qbf of blood lipid content (in the blood) on the ankle-brachial index:

[0193]

[0194] Extract bg (1) ~bg (pa) The maximum value bg in (max) , the minimum value bg (min) , calculate the influence coefficient qbg of blood glucose content (in the blood) on the ankle-brachial index:

[0195]

[0196] Extract hl (1) ~hl (pa) The maximum value hl in (max) , the minimum value hl (min) , calculate the influence coefficient qhl of the content of inflammatory indicators (in the blood) on the ankle-brachial index:

[0197]

[0198] Among them, bf (z) , bg (z) and hl (z) , respectively represent the correlation coefficient of the blood lipid content (in the blood) of the z-th patient corresponding to the ankle-brachial index, the influence coefficient of the blood glucose content (in the blood) on the ankle-brachial index, and the influence coefficient of the content of inflammatory indicators (in the blood) on the ankle-brachial index in the historical medical record; the value range of z is 1~pa;

[0199] Step S24: Obtain the blood lipid content [bfl, bfm] (in the blood) of a healthy person, the blood glucose content [bgl, bgm] (in the blood), and the content of inflammatory indicators [hll, hlm] (in the blood);

[0200] Calculate the influence coefficient bb of the patient's blood lipid on the ankle-brachial index (1) :

[0201] If bfa < bfl, then bb (1) The calculation formula of is:

[0202] If bfa > bfm, then bb (1) The calculation formula of is:

[0203] If bfa ∈ [bfl, bfm], then bb (1) The value of is qbf;

[0204] Calculate the influence coefficient bb of the patient's blood glucose on the ankle-brachial index(2) :

[0205] If bga < bgl, then bb (2) The calculation formula of is:

[0206] If bga > bgm, then bb (2) The calculation formula of is:

[0207] If bga ∈ [bgl, bgm], then bb (2) The value of is qbg;

[0208] Calculate the influence coefficient bb of the patient's inflammatory indicator on the ankle-brachial index (3) :

[0209] If hla < hll, then bb (3) The calculation formula of is:

[0210] If hla > hlm, then bb (3) The calculation formula of is:

[0211] If hla ∈ [hll, hlm], then bb (3) The value of is qhl;

[0212] Compare bb (1) , bb (2) and bb (3) to select the largest or tied largest influence coefficient among bb (1) , bb (2) and bb(3) as the key coefficient;

[0213] Take the physiological indicators corresponding to the key coefficient (i.e., blood lipid, blood glucose, inflammatory indicator) as the main observation indicators of the patient;

[0214] Step S25: Based on Poiseuille's law, construct a mathematical equation for the arterial blood flow velocity at the femoral artery lesion site of the lower limb (for patients with lower limb arteriosclerosis obliterans) and the ankle systolic blood pressure and the brachial artery systolic blood pressure to obtain equation F(1);

[0215] Step S251: (Divide the femoral artery of the lower limb into "lower limb artery stenosis segment" and "lower limb artery normal segment") Assume the total length of the lower limb artery is L (ar) ;

[0216] The length of the stenosis segment of the lower limb artery is L (st) , and the blood vessel radius is r (st) ;

[0217] The length of the normal segment of the lower limb artery is L (nr), the blood vessel radius is r (nr) ; where, L (nr) = L (ar) - L (st) (Formula B-1);

[0218] Denote the blood viscosity as η, and assume the blood flow rate of the lower limb artery per unit time is Q (bo) ;

[0219] It should be noted that the "stenotic segment of the femoral artery in the lower limb" in the present invention refers to: the part of the femoral artery in the lower limb where the lumen becomes narrow due to arteriosclerosis, plaque formation, or thrombosis, etc., and the arterial blood vessel with a significant increase in blood flow resistance, that is, the diseased part;

[0220] The "normal segment of the femoral artery in the lower limb" refers to: the part of the femoral artery in the lower limb that is not affected by arteriosclerosis or other diseases, and the arterial blood vessel with a smooth blood vessel wall, a normal lumen diameter, and a small blood flow resistance, that is, the non-diseased part;

[0221] Step S252: Denote the ankle systolic blood pressure of (a patient with lower limb arteriosclerosis obliterans) as P (br) , and denote the brachial artery systolic blood pressure as P (an) ;

[0222] Calculate the pressure difference ΔP, ΔP = P (br) - P (an) (Formula B-2);

[0223] Construct Formula B-3:

[0224] (to) where, R

[0225] Step S253: Assume the blood flow velocity of the stenotic segment of the femoral artery in the lower limb of (a patient with lower limb arteriosclerosis obliterans) is v (st) (unit: milliliters per minute):

[0226] Substitute Formulas B-1 to B-3 into v (st) to obtain Formula B-4:

[0227]

[0228] Expand the parameters in Formula B-4 to obtain Formula B-5:

[0229]

[0230] Step S254: Introduce the ankle-brachial index ABI:

[0231] Substitute ABI into Equation B-5 to obtain Equation B-6:

[0232]

[0233] Take Equation B-6 as Equation F(1).

[0234] Step S3: Perform a secondary analysis of historical medical records, analyze the mathematical relationship between the femoral artery blood flow velocity and heart rate of the patient, and construct Equation F(2); perform a time series analysis on the ankle-brachial index of all patients in the historical medical records, and estimate the ankle-brachial index of the patient (in the short term) in combination with pathological data, and then analyze the changes in the ankle systolic blood pressure and brachial artery systolic blood pressure of the patient (in the short term) according to Equation F(1) and Equation F(2);

[0235] It should be noted that the distribution of the arteries in the lower extremities of the human body: The aorta branches into the common iliac arteries in the abdominal cavity, and the common iliac arteries are divided into the internal iliac artery and the external iliac artery; the external iliac artery continues to extend downward and becomes the femoral artery, which is the main blood supply artery of the lower extremities; the femoral artery continues to extend below the inguinal ligament and branches into multiple arteries, including the popliteal artery; what this invention mainly studies is the "femoral artery".

[0236] The specific steps of Step S3 are as follows:

[0237] Step S31: Analyze the mathematical relationship between the femoral artery blood flow velocity and heart rate of all patients (in the historical medical records), and construct Equation F(2);

[0238] Step S311: Obtain the femoral artery blood flow velocity of a healthy human body and denote it as Vo;

[0239] Denote time as t, the femoral artery blood flow velocity of the patient at time t as v(t); denote the heart rate of the patient as hr, and the cardiac cycle as Th, Th = 60 / hr;

[0240] Based on the Fourier series of a single harmonic wave, construct Equation C-1:

[0241]

[0242] Among them, aa represents the Fourier coefficient of the cosine term, bb represents the Fourier coefficient of the sine term, and the initial values of aa and bb are both 1;

[0243] Step S312: Obtain the treatment time ti (1) ~ti (pa) (unit: days);

[0244] Obtain the average heart rate hr (1) corresponding to the 1st to ti (1，1) days of the 1st patient (in the historical medical records) (1，ti(1))(Unit: beats per minute) and the average femoral artery blood flow velocity vt(1, 1) to vt (1，ti(1)) (Unit: milliliters per minute);

[0245] For the 2nd patient, the average heart rate hr (2) corresponding to the 1st to the ti (2，1) days is hr (2，ti(2)) (Unit: beats per minute) and the average femoral artery blood flow velocity vt (2，1) to vt (2，ti(2)) (Unit: milliliters per minute);

[0246] And so on, for the pa-th patient, the average heart rate hr (pa) corresponding to the 1st to the ti (pa，1) days is hr (pa，ti(pa)) (Unit: beats per minute) and the average femoral artery blood flow velocity vt (pa，1) to vt (pa，ti(pa)) (Unit: milliliters per minute);

[0247] Step S313: For the m-th patient, the treatment time is ti (m) , and the average heart rate of the m-th patient on the n-th day is hr (m，n) (Unit: beats per minute) and the average femoral artery blood flow velocity is vt (m，n) (Unit: milliliters per minute); The value range of m is: 1 to pa; The value range of n is: 1 to ti( m );

[0248] Denote the cosine-term Fourier coefficient corresponding to the m-th patient in (the historical medical records) as aa (m) , and define calculation formula C-2:

[0249]

[0250] (According to calculation formula C-2) Calculate the cosine-term Fourier coefficients aa (1) to aa (pa) corresponding to the 1st to the pa-th patients in (the historical medical records);

[0251] Step S314: Denote the sine-term Fourier coefficient corresponding to the m-th patient in (the historical medical records) as bb (m) , and define calculation formula C-3:

[0252]

[0253] (According to calculation formula C-3) Calculate the sine-term Fourier coefficients bb (1) to bb (pa) corresponding to the 1st to the pa-th patients in (the historical medical records);

[0254] Calculate aa separately (1) ~aa (pa) and bb (1) ~bb (pa) Take the average value and substitute it into formula C-1 to obtain equation F(2);

[0255] Step S32: Based on the ARIMA(1,1,1) model, perform time series analysis on the ankle-brachial index of the 1st to pa-th patients during the treatment time in (historical medical records) to obtain the change equation of the ankle-brachial index of (patients with lower extremity arteriosclerosis obliterans), denoted as equation F(3);

[0256] Obtain the ankle systolic blood pressure of the patient in (medical examination report) denoted as Pba, and the brachial artery systolic blood pressure denoted as Pak; calculate the ankle-brachial index ABIi of the patient, ABIi = Pba / Pak;

[0257] Obtain the current femoral artery blood flow velocity of the patient denoted as vd, and the current heart rate denoted as her;

[0258] Substitute ABIi into equation F(3) to estimate the estimated value of the patient's ankle-brachial index in the next three days (short term): qABI (1) 、qABI (2) and qABI (3) ;

[0259] Substitute her into equation F(2) to calculate the expected femoral artery blood flow velocity qVo of the patient;

[0260] Step S33: Determine whether (2×qABI (1) )-(qABI (2) +qABI (3) )≤ε holds; where ε represents the error value (the value of ε is 0.1; users or relevant technical personnel can adjust the value of ε according to actual needs).

[0261] If it holds, it means that the patient's condition has improved, and the ankle systolic blood pressure and brachial artery systolic blood pressure tend to normal levels in the short term, and skip the subsequent steps;

[0262] If it does not hold, it means that the patient's condition has deteriorated, analyze the change trend of the ankle systolic blood pressure and brachial artery systolic blood pressure, and enter step S34;

[0263] Step S34: Take Pak as P in equation F(1) (br) ,take qABI (1) ~qABI(3) as ABI in equation F(1), and calculate the first estimated value aVo of the patient's femoral artery blood flow velocity in the next three days (short term) (1) 、aVo (2) and aVo (3) ;

[0264] Calculate the estimated value of the patient's ankle systolic blood pressure in the past three days (short term): bPba (1) , bPba(2) and bPba (3) ; where bPba (1) = Pak × qABI (1) , bPba (2) = Pak × qABI(2), bPba (3) = Pak × qABI (3) ;

[0265] Take bPba (1) to bPba (3) as P in equation F(1) (br) , take ABIi as ABI in equation F(1), and calculate the secondary estimated value bVo of the femoral artery blood flow velocity of the patient in the past three days (short term) (1) , bVo (2) and bVo (3) ;

[0266] Step S35: Define relationship C-4:

[0267] |(aVo (1) + aVo (2) + aVo (3) ) - (3 × qVo)| ≥ |(bVo (1) + bVo (2) + bVo (3) ) - (3 × qVo)|

[0268] Judge whether relationship C-4 holds;

[0269] If relationship C-4 holds, it means that the patient's ankle systolic blood pressure is abnormal. Compare the magnitudes of (aVo (1) + aVo (2) ) and (aVo (2) + aVo (3) );

[0270] If (aVo (1) + aVo (2) ) ≥ (aVo (2) + aVo (3) ), it means that the patient's ankle systolic blood pressure has decreased and the arterial wall blockage of the patient's femoral artery has worsened;

[0271] If (aVo (1) + aVo (2) ) < (aVo (2) + aVo (3) ), it means that the patient's ankle systolic blood pressure has increased and the arterial wall calcification of the patient's femoral artery has worsened;

[0272] If the relational expression C-4 does not hold, it indicates that the patient's brachial artery systolic blood pressure is abnormal. Compare (bVo (1) +bVo (2) ) and (bVo (2) +bVo (3) ).

[0273] If (bVo (1) +bVo (2) ) ≥ (bVo (2) +bVo (3) ), it indicates that the patient's brachial artery systolic blood pressure has decreased, presenting symptoms of low blood pressure;

[0274] If (bVo (1) +bVo (2) ) < (bVo (2) +bVo (3) ), it indicates that the patient's brachial artery systolic blood pressure has increased, presenting symptoms of high blood pressure.

[0275] Step S4: (Construct a three-dimensional model of the patient's lower limb lesion site) Extract the lesion pictures (X-ray pictures or CT pictures) from the patient's medical examination report and import them into Mimics software. Cover and select all the continuous tomographic image data in DICOM format (in Mimics software) to generate the three views of the patient's lower limb; according to the three views of the patient's lower limb, perform threshold analysis on the continuous images, extract the internal tissues of the patient's lower limb, render and extract the femoral artery of the lower limb tissues to obtain the three-dimensional model of the patient's lower limb; use the patient's main observation indicators, (short-term) changes in ankle systolic blood pressure and brachial artery systolic blood pressure, and the three-dimensional model of the lower limb as a preliminary diagnosis report and feedback it to the doctor.

[0276] It should be noted that the "blood lipid content, blood glucose content, inflammation indicator content, blood flow velocity of the lower limb artery, ankle-brachial index, ankle systolic blood pressure, and brachial artery systolic blood pressure" in the present invention are all sample demonstrations of the physiological indicators for judging "lower limb arteriosclerosis obliterans". Users or relevant technical personnel can adjust the above-mentioned physiological indicators according to actual needs.

[0277] Finally, it should be noted that the above-described embodiments are only specific embodiments of the present invention, used to illustrate the technical solutions of the present invention, rather than limiting it. The protection scope of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that any person skilled in the art within the technical scope disclosed by the present invention can still modify the technical solutions described in the foregoing embodiments, or can easily think of changes, or make equivalent replacements for some of the technical features; and these modifications, changes or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for constructing a model of lower extremity arteriosclerosis obliterans, characterized in that The method includes: Step S1: Obtain the medical examination report of the patient, extract the blood lipid content, blood glucose content, inflammation indicator content of the patient, and the blood flow velocity of the lower limb artery to obtain the pathological data of the patient; Step S2: Obtain the historical medical records of the target hospital; perform a first - time processing on the historical medical records, analyze the influence of various physiological indicators on the ankle - brachial index, and combine with the pathological data to determine the main observation indicators of the patient; based on Poiseuille's law, construct a mathematical equation for the arterial blood flow velocity of the lower limb lesion site, the ankle systolic pressure, and the brachial artery systolic pressure to obtain equation F(1); Step S3: Perform a second - time analysis on the historical medical records, analyze the mathematical relationship between the femoral artery blood flow velocity and the heart rate of the patient, and construct equation F(2); perform a time - series analysis on the ankle - brachial index of all patients in the historical medical records, and combine with the pathological data to estimate the ankle - brachial index of the patient. Then, according to equation F(1) and equation F(2), analyze the changes in the ankle systolic pressure and the brachial artery systolic pressure of the patient; Step S4: Extract the lesion pictures from the patient's medical examination report and import them into the modeling software, select and cover all the continuous tomographic image data in DICOM format to generate the three - view drawings of the patient's lower limbs; according to the three - view drawings of the patient's lower limbs, perform threshold analysis on the continuous images, extract the internal tissues of the patient's lower limbs, render and extract the femoral artery of the lower limb tissues to obtain the three - dimensional model of the patient's lower limbs; use the main observation indicators of the patient, the changes in the ankle systolic pressure and the brachial artery systolic pressure, and the three - dimensional model of the lower limbs as a preliminary diagnosis report and feedback it to the doctor.

2. The construction method of a lower limb arteriosclerosis obliterans model according to claim 1, characterized in that, The specific steps of step S2 are as follows: In step S21, record the blood lipid content of the patient as bfa, the blood glucose content as bgo, and the inflammation indicator content as hle; Count the number of patients in the historical medical records, denoted as pa; obtain the treatment times ti(1) to ti( pa ); Step S22: Analyze and calculate the correlation coefficient bf of the blood lipid content corresponding to the first to the pa-th patients with respect to the ankle-brachial index (1) ~bf (pa) , calculate bf (1) ~bf (pa) and calculate the average value abf of bf; Coefficient of correlation bg of blood glucose level with ankle-brachial index (1) ~bg (pa) , and the calculated average value abg; Correlation coefficient hl of the inflammatory indicator content with respect to the ankle-brachial index (1) ~hl (pa) , the calculated average value ahl; Step S23: Extract bf (1) ~bf (pa) The maximum value bf (max) The minimum value bf (min) , and calculate the influence coefficient qbf of blood lipid content on ankle-brachial index: Extract bg (1) ~bg (pa) The maximum value of bg (max) The minimum value of bg (min) , calculate the influence coefficient qbg of blood glucose content on ankle-brachial index: Extract hl (1) ~hl (pa) The maximum value of hl (max) The minimum value of hl (min) , calculate the influence coefficient qhl of the content of the inflammation indicator on the ankle-brachial index.

3. The construction method of a lower limb arteriosclerosis obliterans model according to claim 2, wherein, Step S2 also includes: In step S24, obtain the blood lipid content [bfl, bfm], blood glucose content [bgl, bgm], and inflammation indicator content [hll, hlm] of a healthy person; Calculate the influence coefficient bb of the patient's blood lipid on the ankle-brachial index (1) : If bfa < bfl, then bb (1) The calculation formula of If bfa > bfm, then bb (1) The calculation formula of If bfa ∈ [bfl, bfm], then the value of bb (1) is qbf; Calculate the influence coefficient bb of the patient's blood glucose on the ankle-brachial index (2) : If bga < bgl, then bb (2) The calculation formula of is: If bga > bgm, then bb (2) The calculation formula of If bga ∈ [bgl, bgm], then the value of bb (2) is qbg; Calculate the influence coefficient bb of the patient's inflammatory indicator on the ankle-brachial index (3) : If hla < hll, then bb (3) The calculation formula of If hla > hlm, then bb (3) The calculation formula of If hla ∈ [hll, hlm], then bb (3) has a value of qhl; Compare bb (1) , bb (2) and bb (3) in terms of magnitude, select the largest influence coefficient as the key coefficient; Take the physiological indicators corresponding to the key coefficients as the main observation indicators of the patient; In step S25, based on Poiseuille's law, construct a mathematical equation for the arterial blood flow velocity of the femoral artery lesion site of the lower limb, the ankle systolic pressure, and the brachial artery systolic pressure to obtain equation F(1), and then enter step S3.

4. The construction method of a lower limb arteriosclerosis obliterans model according to claim 2, characterized in that, The working steps of step S22 are as follows: Step S221: Take ti (1) as til, and calculate the correlation coefficient bf of the lipid content corresponding to the first patient with respect to the ankle-brachial index (1) , the correlation coefficient bg of the blood glucose content with respect to the ankle-brachial index (1) , and the correlation coefficient hl of the inflammatory indicator content with respect to the ankle-brachial index (1) ; Obtain the average blood lipid content bf of the first user within the first to the tilth day (1，1) ~bf (1，til) , the average blood glucose content bg (1，1) ~bg (1，til) , the average inflammation indicator content hl (1，1) ~hl (1，til) , the ankle-brachial index br (1，1) ~br (1，til) ; Calculate br (1，1) ~br (1，til) and the sum abr; Step S222: According to bf (1，1) ~bf (1，til) and br (1，1) ~br (1，til) , calculate bf (1) ; Step S223: According to bg (1，1) ~bg (1，til) and br (1，1) ~br (1，til) Calculate bg (1) ; According to hl (1，1) ~hl (1，til) and br (1，1) ~br (1，til) Calculate hl(1); Step S224: Calculate the correlation coefficients bf of the blood lipid contents corresponding to the 2nd to the pa-th patients with respect to the ankle-brachial index (2) ~bf (pa) ; the correlation coefficient bg of the blood glucose content with respect to the ankle-brachial index (2) ~bg(pa); the correlation coefficient hl of the inflammatory indicator content with respect to the ankle-brachial index (2) ~hl (pa) .

5. The construction method of a lower limb arteriosclerosis obliterans model according to claim 4, characterized in that, The specific steps of step S222 are as follows: Step S2221: Denote the weighted coefficients of the blood lipid content of the first patient on the 1st to the tilth day with respect to the ankle-brachial index as λbf (1) ~λbf (til) , and denote the offset coefficient as vbf; Step S2222: Let the values of λbf after k updates (1) ~λbf (til) be λbf (k) (1)~λbf (k) (til) ; bf after k updates (1，1) value of bf (k) (1，1) ; Similarly, bf after k updates (1， value of til (k) (1，til) ; Step S2223: Calculate bf (1，1) ~bf (1，til) The sum gbf (1) , the average value abf(1); Calculate bf (k) (1，1) ~bf (k) (1，til) and the sum Abf (k) , the average Gbf(k), and the variance Sbf (k) ; Calculate the covariance Cov after k updates (bf) (k) ; Among them, bf (1，y) represents the average blood lipid content of the first patient on the y-th day; bf (k) (1, y) represents the value of bf after k updates (1，y) ; Define calculation formula A - 1 - 1: Among them, Aλ (k) represents the combined weight of the k-th update; Step S2224: Update Aλ (k) until the relational expression A - 1 - 2 is satisfied, and obtain the combined weight Bλ; Relationship A-1-2: |Aλ (k) - Aλ (k+1) | ≤ ε; where Aλ (k+1) represents the combined weight of the (k + 1)th update, and ε represents the allowable error value; Step S2225: Denote the weighted coefficient of the first patient on the y-th day as λbf (y) , and define calculation formula A-1-3: Calculate the weighting coefficient λbf (1) ~λbf (til) ; Calculate the offset coefficient vbf: Step S2226: Define matrix CA and matrix CB; calculate the path coefficient β of the first patient (bf) : β (bf) = [[(CB * CB T ) -1 ) * CB] T * CA; Coefficient bf of blood lipid content with respect to ankle-brachial index (1) :

6. The construction method of a lower extremity arteriosclerosis obliterans model according to claim 3, characterized in that, The specific steps of step S25 are as follows: Step S251: Set the total length of the lower limb artery as L (ar) ; The length of the stenotic segment of the lower limb artery is L (st) , and the vascular radius is r (st) ; The normal segment length of the lower limb artery is L (nr) , and the blood vessel radius is r (nr) ; among them, L (nr) = L (ar) - L (st) (Formula B-1); Let the blood viscosity be denoted as η, and let the blood flow rate in the lower limb artery per unit time be Q (bo) ; Step S252: Denote the ankle systolic blood pressure as P (br) , and denote the brachial artery systolic blood pressure as P (an) ; Calculate the pressure difference ΔP, ΔP = P (br) - P (an) (Equation B-2); Construct formula B - 3: Among them, R (to) represents the resistance during blood transportation in the lower limb arterial system; Step S253: Set the blood flow velocity of the stenotic segment of the femoral artery in the lower limb as v (st) : Substitute Formulas B-1 to B-3 into v (st) to obtain Formula B-4: Expand the parameters in formula B - 4 to obtain formula B - 5: Step S254: Introduce the ankle-brachial index ABI: Substitute ABI into formula B - 5 to obtain formula B - 6: Take formula B - 6 as equation F(1).

7. The construction method of a lower limb arteriosclerosis obliterans model according to claim 3, characterized in that, The specific steps of step S3 are as follows: In step S31, analyze the mathematical relationship between the femoral artery blood flow velocity and the heart rate of all patients and construct equation F(2); In step S32, based on the ARIMA(1,1,1) model, perform a time - series analysis on the ankle - brachial index of the 1st to the pa - th patients during the treatment time to obtain the ankle - brachial index change equation, denoted as equation F(3); Obtain the ankle systolic blood pressure of the patient, denoted as Pba, and the brachial artery systolic blood pressure, denoted as Pak; calculate the ankle-brachial index ABIi of the patient, ABIi = Pba / Pak; Obtain the current femoral artery blood flow velocity of the patient, denoted as vd, and the current heart rate, denoted as her; Substitute ABIi into Equation F(3) to estimate the estimated value of the patient's ankle-brachial index in the past three days: qABI (1) , qABI (2) and qABI (3) ; In the her equation F(2), calculate the expected femoral artery blood flow velocity qVo of the patient; Step S33: Determine whether (2×qABI (1) )-(qABI (2) +qABI (3) ) ≤ ε holds; where ε represents the error value; If it holds, it indicates that the patient's condition has improved, and skip the subsequent steps; If it does not hold, it indicates that the patient's condition has deteriorated, and analyze the changing trends of the ankle systolic blood pressure and the brachial artery systolic blood pressure.

8. The construction method of a lower limb arteriosclerosis obliterans model according to claim 7, characterized in that The subsequent steps of step S33 are as follows: Step S34: Substitute Pak and qABI (1) ~qABI (3) into Equation F(1) to calculate the first estimated value aVo (1) , aVo (2) and aVo (3) ; Calculate the estimated values of the patient's ankle systolic blood pressure in the last three days: bPba (1) 、bPba (2) and bPba(3); Put bPba (1) ~bPba (3) and ABIi into Equation F(1) to calculate the secondary estimated value bVo of the femoral artery blood flow velocity of the patient in the past three days (1) 、bVo (2) and bVo (3) ; Step S35: Define the relationship C-4: |(aVo (1) +aVo (2) +aVo (3) )-(3×qVo)|≥|(bVo (1) +bVo (2) +bVo (3) )-(3×qVo)| Judge whether the relationship C-4 holds; If the relational expression C - 4 holds, it indicates that the patient's ankle systolic blood pressure is abnormal. Compare the magnitudes of (aVo (1) +aVo (2) ) and (aVo (2) +aVo (3) ). If (aVo (1) + aVo (2) ) ≥ (aVo (2) + aVo (3) ), it indicates that the patient's ankle systolic blood pressure has decreased; If (aVo (1) + aVo (2) ) < (aVo (2) + aVo (3) ), it indicates that the patient's ankle systolic blood pressure has increased; If the relational expression C-4 does not hold, it indicates that the patient's brachial artery systolic blood pressure is abnormal. Compare (bVo (1) +bVo (2) ) and (bVo (2) +bVo (3) ) in terms of size; If (bVo (1) + bVo (2) ) ≥ (bVo (2) + bVo (3) ), it indicates that the patient's brachial artery systolic blood pressure has decreased; If (bVo (1) + bVo (2) ) < (bVo (2) + bVo (3) ), it indicates that the patient's brachial artery systolic blood pressure has increased.

9. The construction method of a lower limb arteriosclerosis obliterans model according to claim 7, characterized in that The specific steps of step S31 are as follows: Step S311: Obtain the femoral artery blood flow velocity of a healthy person, denoted as Vo; Denote the time as t, and the femoral artery blood flow velocity of the patient at time t as v(t); denote the patient's heart rate as hr, and the cardiac cycle as Th, Th = 60 / hr; Based on the Fourier series of a single harmonic wave, construct the formula C-1: Among them, aa represents the Fourier coefficient of the cosine term, bb represents the Fourier coefficient of the sine term, and the initial values of both aa and bb are 1; Step S312: Obtain the treatment time ti of the 1st to the pa-th patient (1) ~ti (pa) ; Obtain the average heart rate hr (1) corresponding to the first patient from the 1st to the ti (1，1) th day, i.e., hr(1, ti(1)), and the average femoral artery blood flow velocity vt (1，1) ~vt (1，ti(1)) ; Similarly, for the pa-th patient, the average heart rate hr (pa) corresponding to the 1st to the ti (pa， -th day is hr (pa，ti(pa)) 1) to hr (pa，1) and the average femoral artery blood flow velocity vt (pa，ti ~vt (pa)).

10. The construction method of a lower limb arteriosclerosis obliterans model according to claim 9, characterized in that, The subsequent steps of step S312 are as follows: Step S313: The treatment time of the m-th patient is ti (m) , the average heart rate of the m-th patient on the n-th day is hr (m，n) and the average femoral artery blood flow velocity is vt (m，n) ; Denote the cosine-term Fourier coefficient corresponding to the m-th patient as aa (m) , and define calculation formula C-2: Calculate the cosine-term Fourier coefficients aa corresponding to the 1st to the pa-th patients (1) ~aa (pa) ; Step S314: Denote the sine-term Fourier coefficient corresponding to the m-th patient as bb (m) , and define calculation formula C-3: Calculate the sine-term Fourier coefficients bb corresponding to patients from the 1st to the pa-th (1) ~bb (pa) ; Calculate aa separately (1) ~aa (pa) and bb (1) ~bb (pa) Calculate the average values of and substitute them into Equation C-1 to obtain Equation F(2).

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