Customized health conditioning scheme generation system for traditional Chinese medicine four-diagnosis instrument

Abstract

The invention discloses a customized health conditioning scheme generation system for a traditional Chinese medicine four-diagnosis instrument, and relates to the technical field of traditional Chinese medicine conditioning scheme generation, and the system comprises a scheme analysis module, a dynamic parameter optimization module and a scheme display module. The scheme analysis module extracts key parameters and solves data conflicts through multi-format data analysis and standardization processing; the dynamic parameter optimization module is used for correcting the dosage of medicinal materials according to geographical, solar and environmental factors, optimizing decoction parameters and improving the precipitation rate of effective components; and the scheme display module is used for calculating priorities through multi-dimensional evaluation indexes and displaying scheme elements in a grading manner. By introducing genuine production areas and space-time parameter correction factors, the fluctuation of the content of effective components is remarkably reduced, and by dynamically optimizing a decoction scheme, the scientificity and the curative effect of a traditional Chinese medicine conditioning scheme are improved, and technical support is provided for modern diagnosis and treatment of traditional Chinese medicine.

Description

Technical Field

[0001] This invention relates to the field of TCM conditioning program generation technology, specifically a TCM four diagnostic instruments customized health conditioning program generation system. Background Technology

[0002] The Four Diagnostic Methods Instrument (TCM Four Diagnostic Instrument) is a medical device based on traditional Chinese medicine theory and combined with modern technology. It is used to collect and analyze a patient's tongue appearance, pulse, complexion, and medical history, thus providing a scientific basis for TCM diagnosis and treatment. In recent years, with the advancement of TCM modernization, the TCM Four Diagnostic Instrument has gradually become more widely used in clinical practice, becoming one of the important tools for TCM diagnosis and treatment. However, despite its excellent performance in data collection and preliminary diagnosis, the TCM Four Diagnostic Instrument still has significant shortcomings in generating TCM treatment plans, especially in the selection of medicinal materials and the design of decoction procedures.

[0003] First, in the selection of medicinal materials, traditional systems fail to fully consider the authenticity of the materials and their correlation with spatiotemporal parameters. Authentic medicinal materials refer to those produced within a specific geographical region, possessing specific quality and efficacy; their effective component content is often significantly affected by factors such as the production environment, climate conditions, and harvesting time. However, existing TCM conditioning regimen generation systems often select medicinal materials based solely on their names and basic effects, neglecting crucial factors such as origin and harvesting season. Studies have shown that ignoring these factors can lead to fluctuations in the effective component content of medicinal materials exceeding 30%, thereby affecting the efficacy and safety of TCM conditioning regimens.

[0004] Secondly, traditional Chinese medicine (TCM) decoction methods mostly follow a fixed pattern, failing to personalize the treatment based on the physical properties of the herbs. Different herbs exhibit significant differences in texture, density, and dissolution rate, directly impacting the extraction efficiency of active ingredients. For example, harder herbs require longer decoction times to fully release their active ingredients, while faster-dissolving herbs may extract their active ingredients more quickly. However, existing decoction methods fail to adequately consider these differences, resulting in extraction rates that can vary by up to 45%. This variation not only affects the efficacy and safety of TCM but may also lead to decreased patient adherence to the treatment plan.

[0005] Furthermore, traditional Chinese medicine (TCM) treatment plan generation systems also have shortcomings in data processing and plan presentation. Existing systems lack effective fusion and conflict resolution mechanisms when processing multi-source data, resulting in insufficient data accuracy and reliability. Simultaneously, in terms of plan presentation, they lack intuitive visualization methods, failing to provide clinicians and patients with clear and easy-to-understand interpretations. These problems further limit the application scope and promotional value of traditional TCM treatment plan generation systems. Therefore, there is an urgent need for a new type of TCM treatment plan generation system that can comprehensively consider geographical origin, spatiotemporal parameters, the physical properties of medicinal materials, and data processing optimization to improve the scientific rigor, effectiveness, and safety of TCM treatment plans.

[0006] To address the aforementioned shortcomings, a technical solution is provided. Summary of the Invention

[0007] The purpose of this invention is to solve the problems of traditional Chinese medicine conditioning program generation systems, which fail to consider the authenticity and spatiotemporal parameters of medicinal materials, resulting in excessive fluctuations in the content of effective components, and the use of fixed decoction programs that ignore the differences in the physical characteristics of medicinal materials, leading to inconsistent extraction rates of effective components. In response, this invention proposes a customized health conditioning program generation system based on the four diagnostic instruments of traditional Chinese medicine.

[0008] The objective of this invention can be achieved through the following technical solutions: A system for generating customized health conditioning plans using traditional Chinese medicine diagnostic instruments includes: The scheme analysis module is used to analyze the initial scheme, extract and standardize key parameters from multi-format data, integrate multi-source data and resolve conflicts, and provide a foundation for subsequent processing. The dynamic parameter optimization module is used to adjust the dosage of medicinal materials based on geographical, seasonal, and environmental factors, optimize decoction parameters, and output a correction plan with visual evidence. The solution display module is used to construct multi-dimensional evaluation indicators to calculate the priority total score, generate scores through decision matrix and calculated distance, and display the elements of the modified solution in a hierarchical manner.

[0009] Furthermore, the execution steps of the scheme parsing module are as follows: First, the initial plan is analyzed; Input initial scheme parameters: Set the medicinal material composition matrix, where each element includes the medicinal material code, initial dosage, and medicinal material composition matrix. ,in Representative medicinal material code, This represents the initial dosage; it also sets the basic cooking parameters, including the total cooking time. And the curve of temperature changing over time ; Feature extraction: Obtaining geographic coordinates from patient information and the current timestamp t accurate to the solar term; where These represent longitude and latitude, respectively; environmental parameters, including temperature, are collected in real time. air humidity and water hardness ; Establish a set of correction factors: Geographical correction factor: Geographical correction factor The calculation formula is as follows: ,in Indicates the distance from the main producing area; This is a preset reference distance for the main producing areas; Solar Term Correction Factor: Solar Term Correction Factor It is calculated using the natural exponential function, through the formula: In the formula, For the current timestamp accurate to the solar term; Optimal harvesting season It is a constant.

[0010] Furthermore, the specific steps for the scheme parsing module to parse the initial scheme are as follows: First, the initial plan is analyzed. The plan formats include: text data: prescription documents, electronic medical records, free text descriptions; structured data: database records, JSON / XML format; image data: scanned copies of handwritten prescriptions, photos of medicine packaging labels; For text-based data, optical character recognition and natural language processing are used to extract text information, supporting a TCM terminology database; for image-based data, a YOLOv5 model is used to train medicinal herb identification and locate the names and dosage areas of medicinal herbs in prescriptions; structured data is directly mapped to fields. Parameter extraction and standardization: Define key parameters, including: herbal name, dosage, and decoction method; The BiLSTM-CRF model is used to annotate the entities of medicinal materials, dosage, and decoction methods in the text; at the same time, it is dynamically linked to the database of safe dosage of medicinal materials to trigger anomaly warnings. To address the fusion and conflicts of multi-source data, the following methods are used: Priority rules: structured data > image data > text data; fuzzy matching algorithm: calculates descriptive similarity; manual review interface: highlights conflicting items and provides historical prescription references.

[0011] Furthermore, the reference distance of the aforementioned traditional producing areas and the best harvest season The determination process is as follows: The elevation, slope, and aspect parameters of the authentic producing areas were obtained through GIS; historical data from meteorological stations, including average annual temperature, precipitation, and sunshine duration, were integrated, with a time span of ≥20 years; and surface soil samples from the producing areas were collected to determine pH value, organic matter content, and 12 trace elements. DBSCAN clustering was performed on the quality of medicinal materials (i.e., the content of effective components) and geographical parameters to delineate the boundaries of the core authentic region; with the core region as the center, the maximum radiation radius was calculated by expanding outward according to environmental similarity. : ,in The initial expansion radius is calculated through buffer analysis; The average effective ingredient content within the buffer zone; The highest content of effective ingredients in medicinal materials from the core authentic producing areas; Medicinal herb samples were collected from candidate production areas to test the content of active ingredients; a geographical distance-mass decay model was established. ,in The concentration of components in the core area; The attenuation coefficient is defined as follows: For when Distance at time; Optimal harvesting season The determination process is as follows: Fixed sample plots were set up in the traditional producing areas, and medicinal material samples were collected according to the solar terms; the detection indicators were: effective components, dry matter accumulation, and secondary metabolite content. The component content variation curve over time is modeled using Gaussian process regression; the first derivative of the curve is calculated, and the peak point, i.e., the optimal harvest period, is found when the derivative is zero; formula derivation: ;in This is the optimal time for harvesting; To find the parameter values ​​that maximize the function within the time interval t; The first derivative of the effective ingredient content C with respect to time t is zero; Key parameters: accumulated temperature, calculating the effective accumulated temperature from germination to harvest; photoperiod index: combined with the diurnal variation rate; establishing a multiple linear regression model: ;in This is the intercept term of the regression model; The regression coefficients represent the weights of the influence of accumulated temperature and photoperiod on harvesting time, respectively. This is the error term; The effective accumulated temperature is calculated as follows: ,in , and These are the highest and lowest temperatures of the day, respectively. The model is trained using historical data to predict the optimal harvesting window.

[0012] Furthermore, the execution steps of the dynamic parameter optimization module are as follows: The dosage correction algorithm is as follows: Basic dosage formula: ,in This is the new dosage after adjustments based on geography and solar terms; This is the initial dosage of the medicinal materials, and the starting value for adjusting the dosage; and These are geographical correction factors and solar term correction factors, respectively. Climate compensation factor: The climate compensation factor is calculated using the formula: ;in As a climate compensation factor; Real-time temperature; Air humidity; Final revised formula: ,in This is the final revised dosage of medicinal materials; This is the new dosage after adjustments based on geography and solar terms; As a climate compensation factor; This is the initial dosage of the medicinal materials; The function is a numerical constraint function, used to... The calculation results are limited to Within the range; Optimization of cooking parameters: Establishment of a multi-objective optimization model: Mathematically expressed as: The constraints are and ℃; among which This refers to the actual ingredient content; The target component content; This refers to the actual total cooking time. The base total time is the initial cooking time standard set; The maximum permissible cooking temperature; Dynamic adjustment is achieved using a fuzzy PID control algorithm: via the formula: ;in, Set the temperature value; The average of the spatiotemporal fit scores for all medicinal materials; This is a spatiotemporal fit score for a single medicinal herb, calculated based on the degree of matching between the herb and the user's spatiotemporal characteristics; then... , which is the arithmetic mean of the scores of all medicinal materials in the scheme; N is the number of all medicinal materials; The duration of the phase is ,in The duration of a stage refers to the length of a certain stage in the simmering or boiling process; Based on total duration; Water hardness; Output correction scheme: Generate difference comparison map, highlight the parameter items with correction magnitude greater than 10%; provide a visual path from spatiotemporal parameters, through the calculation process, to the adjustment result as the correction basis chain.

[0013] Furthermore, the specific operation steps of the solution demonstration module are as follows: Construction of multi-dimensional evaluation indicators: drug efficacy weighting Based on pharmacopoeia databases and clinical research data, the therapeutic efficacy levels of medicinal materials are defined as follows: ,in, The efficacy level of the i-th medicinal material; The dosage of medicinal materials is standardized to the range of 0-1; n represents the total quantity of all medicinal materials in the current health conditioning plan; m represents the quantity of toxic medicinal materials in the current health conditioning plan; Security risks Calculate the risk value of toxic medicinal materials: ,in Toxicity level; This is the actual amount used. This is the maximum permissible dosage according to the pharmacopoeia; Compliance score The calculation is based on the complexity of medication use, including the degree of matching between the decoction process, frequency, and the patient's lifestyle. ; Then calculate the total priority score according to the formula: ; Construct a decision matrix that includes all the elements of each option. Value; normalization processing; calculation of positive and negative ideal solutions; calculation of the Euclidean distance between each element and the positive and negative ideal solutions; generation of priority scores, ranging from 0 to 1. Tiered display: Red highlights indicate priority ≥ 0.8, including core treatment steps; yellow marks indicate priority ≤ 0.5, including auxiliary conditioning measures; green marks indicate priority < 0.5, including adjustable items.

[0014] Compared with the prior art, the beneficial effects of the present invention are: (1) This invention, through the scheme analysis module, realizes the multi-format data analysis and standardization processing of the initial scheme, which can effectively integrate multi-source data and solve the data conflict problem. This data processing method not only improves the accuracy and reliability of scheme generation, but also provides a solid foundation for subsequent dynamic parameter optimization. By introducing correction factors of geographical, solar term and environmental parameters, the dosage of medicinal materials can be dynamically adjusted according to the original producing area and the best harvesting solar term of the medicinal materials, which significantly reduces the fluctuation of effective component content caused by differences in producing area and harvesting time, and improves the scientificity and effectiveness of traditional Chinese medicine conditioning scheme. (2) In this invention, the dynamic parameter optimization module corrects the dosage of medicinal materials based on geographical, seasonal, and environmental factors, and optimizes the decoction parameters; by dynamically adjusting the decoction temperature and duration through a fuzzy PID control algorithm, this invention can design personalized decoction schemes based on the physical properties of medicinal materials and environmental conditions; the optimization process not only improves the extraction rate of effective components, but also reduces component loss caused by fixed decoction modes, significantly improving the efficacy and safety of traditional Chinese medicine conditioning schemes. The visualized correction basis chain output by the system provides clear decision support for clinicians, further enhancing the operability of the scheme and patient compliance; (3) In this invention, the scheme display module constructs a multi-dimensional evaluation index system to prioritize and display the revised scheme. Taking into account factors such as efficacy weight, safety risk and patient compliance, priority scores are generated by calculating the decision matrix and Euclidean distance, and the scheme is displayed using intuitive color markings (red, yellow, green) as the core elements and adjustable items. This hierarchical display method not only facilitates clinicians to quickly identify key treatment steps, but also provides patients with an easy-to-understand interpretation of the conditioning scheme, further enhancing the clinical application value of traditional Chinese medicine conditioning schemes. Attached Figure Description

[0015] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings; Figure 1 This is the overall system block diagram of the present invention. Detailed Implementation

[0016] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] It should be understood that the terms “comprising” and “including” used in this disclosure and claims indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0018] It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this disclosure. As used in this disclosure and claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this disclosure and claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations.

[0019] like Figure 1 As shown, a system for generating customized health conditioning plans using a traditional Chinese medicine four diagnostic instruments includes a plan analysis module, a dynamic parameter optimization module, and a plan display module. The scheme analysis module is used to analyze the initial scheme, extract and standardize key parameters from multi-format data, integrate multi-source data and resolve conflicts, and provide a foundation for subsequent processing. First, the initial plan is analyzed. The plan formats include: text data: prescription documents (PDF / Word), electronic medical records (EMR), free text descriptions; structured data: database records (SQL / NoSQL), JSON / XML formats; image data: scanned copies of handwritten prescriptions, photos of medicine packaging labels; For text-based data, OCR (Optical Character Recognition) + NLP (Natural Language Processing) are used to extract text information, supporting a TCM terminology database (containing 8,000+ alternative names of medicinal materials); for image-based data, a YOLOv5 model is used to train medicinal material identification detection (recognition accuracy >95%) to locate the names and dosage areas of medicinal materials in prescriptions; structured data is directly mapped to fields. Parameter extraction and standardization: Define key parameters, including: herbal name (mapped to the standard name in the Chinese Pharmacopoeia, such as "Astragalus membranaceus" → "Astragalus membranaceus"); dosage (unit uniformly in grams, supporting automatic conversion of traditional units such as "qian" and "liang", rule: 1 qian ≈ 3g); decoction method (decocting first, adding later, wrapping for decoction, etc., coded as standardized instructions, such as DECOCT_FIRST); use BiLSTM-CRF model to annotate the herbal name, dosage, and decoction method entities in the text; at the same time, dynamically link to the herbal safe dosage database to trigger anomaly warnings; To address the issues of multi-source data fusion and conflicts (conflict scenarios: inconsistent dosage of the same medicinal material in different data sources, such as "Astragalus membranaceus 9g" in text and "Astragalus membranaceus 12g" in images; contradictory decoction methods, such as "decoct first" in text and "add later" in database records), the following methods are used: Priority rules: structured data > image data > text data; and fuzzy matching algorithm: calculating descriptive similarity (e.g., "decoct for 30 minutes first" matches "DECOCT_FIRST" with a similarity of 0.92); and a manual review interface: highlighting conflicting items and providing historical prescription references (by calling a similar case database).

[0020] Input initial scheme parameters: Set the medicinal material composition matrix, where each element represents (medicinal material code, initial dosage), medicinal material composition matrix. ,in Representative medicinal material code, This represents the initial dosage. It also sets the basic cooking parameters, including the total cooking time. And the curve of temperature changing over time Feature extraction: Obtaining geographic coordinates from patient information. (in These represent longitude and latitude respectively; GPS accuracy is ±5 meters) and the current timestamp t accurate to the solar term, such as "3 days after Grain in Ear"; environmental parameters, including temperature, are collected in real time. (Range from -10℃ to 45℃), air humidity (30-95%RH) and water hardness (0-500ppm).

[0021] Establish a set of correction factors: Geographic correction factors: Geographic correction factors The calculation formula is as follows: ,in Indicates the distance from the main producing area; This is a preset reference distance for the main producing areas; The specific determination process is as follows: Parameters such as altitude, slope, and aspect of the authentic producing area were obtained using GIS (accuracy ±1m); historical meteorological data (annual average temperature, precipitation, and sunshine duration) spanning ≥20 years were integrated; surface soil samples (0-30cm) were collected from the producing area to determine pH value, organic matter content, and 12 trace elements (such as selenium and zinc); DBSCAN clustering was performed on the quality of medicinal materials (content of effective ingredients) and geographical parameters to delineate the boundary of the core authentic producing area; the maximum radiation radius was calculated by expanding outward from the core area according to environmental similarity (Euclidean distance <0.5). : ,in The initial expansion radius is calculated through buffer analysis; The average effective ingredient content within the buffer zone; To determine the highest effective component content of medicinal herbs in the core producing area; to collect medicinal herb samples (≥100) in candidate producing areas (core area and surrounding 50km range) and test the effective component content; to establish a geographical distance-mass decay model: ,in The concentration of components in the core area; The attenuation coefficient (determined through regression analysis); defined For when The distance at which the active ingredient is retained (i.e., the maximum allowable distance at which 85% of the active ingredient is retained).

[0022] Solar Term Correction Factor: Solar Term Correction Factor It is calculated using the natural exponential function, through the formula: In the formula, For the current timestamp accurate to the solar term; The optimal harvesting season is the time when medicinal materials are at their best quality. This is a constant that plays a moderating role in calculating the solar term correction factor, affecting the magnitude of the correction factor's variation. The optimal harvesting solar term is... The determination process is as follows: Fixed sample plots were set up in the authentic producing areas, and medicinal material samples were collected every 15 days according to the solar terms (≥30 samples / time). The following indicators were tested: effective components (such as flavonoids and saponins), dry matter accumulation, and secondary metabolite content. Gaussian process regression (GPR) was used to model the change curve of component content over time. The first derivative (rate of change) of the curve was calculated, and the peak point (optimal harvest period) was identified when the derivative was zero. Formula derivation: ;in This is the optimal time for harvesting; To find the parameter values ​​that maximize the function within the time interval t; The first derivative of the effective component content C with respect to time t is zero; key parameters: accumulated temperature, calculated from germination to harvest (baseline temperature 5℃); photoperiod index: combined with the diurnal variation rate (calculated using astronomical algorithms); establish a multiple linear regression model: ;in This is the intercept term of the regression model; The regression coefficients represent the weights of the influence of accumulated temperature and photoperiod on harvesting time, respectively. The effective accumulated temperature is calculated as follows: ,in , and These are the highest and lowest temperatures of the day, respectively. The error term is used to train the model using historical data (R² must be ≥ 0.8) to predict the optimal harvesting window.

[0023] Environmental correction matrix: using the formula: ,in For environmental correction matrix; This is the real-time temperature, reflecting the current atmospheric temperature conditions. Air humidity is an indicator that measures the amount of water vapor in the air. Water hardness.

[0024] The dynamic parameter optimization module is used to adjust the dosage of medicinal materials based on geographical, seasonal, and environmental factors, optimize decoction parameters, and output a correction plan with visual evidence. Dosage Adjustment Algorithm: Basic Dosage Formula: ,in This is the new dosage after adjustments based on geography and solar terms; This is the initial dosage of the medicinal materials, and the starting value for adjusting the dosage; and These are geographical correction factors and seasonal correction factors, respectively.

[0025] Climate compensation factor: The climate compensation factor is calculated using the formula: ;in As a climate compensation factor; Real-time temperature; For air humidity; final correction formula: ,in This is the final revised dosage of medicinal materials; This is the new dosage after adjustments based on geography and solar terms; As a climate compensation factor; This is the initial dosage of the medicinal materials; The function is a numerical constraint function, used to... The calculation results are limited to Within the range; Optimization of cooking parameters: Establishment of a multi-objective optimization model: Mathematically expressed as: The constraints are and ℃; among which This refers to the actual ingredient content; The target component content; This refers to the actual total cooking time. The base total time is the initial cooking time standard set; The maximum permissible cooking temperature. Dynamic adjustment is achieved using a fuzzy PID control algorithm: via the formula: ;in, Set the temperature value; The average of the spatiotemporal fit scores for all medicinal materials; This is a spatiotemporal fit score (range 0-1) for a single medicinal herb, calculated based on the degree of matching between the medicinal herb and the user's spatiotemporal characteristics; then , which is the arithmetic mean of the scores of all medicinal materials in the scheme; N is the number of all medicinal materials; The duration of the phase is ,in The duration of a stage refers to the length of a certain stage in the simmering or boiling process; Based on total duration; For water hardness. Output correction scheme: Generate difference comparison charts, highlight parameters with correction magnitudes greater than 10%; provide a visual path from spatiotemporal parameters, through the calculation process, to the adjustment result as a correction basis chain.

[0026] The scheme display module is used to construct multi-dimensional evaluation indicators to calculate the priority total score, generate scores through decision matrix and calculated distance, and display the elements of the modified scheme in a hierarchical manner; Construction of multi-dimensional evaluation indicators: drug efficacy weighting Based on pharmacopoeia databases and clinical research data, the therapeutic efficacy levels of medicinal materials are defined (levels 1-5, with level 5 being the highest): ,in, The efficacy level of the i-th medicinal material; The dosage of medicinal materials (standardized to a range of 0-1); n represents the total quantity of all medicinal materials in the current health conditioning plan; safety risks. Calculate the risk value of toxic medicinal materials (refer to the toxicity classification in the Chinese Pharmacopoeia): ,in Toxicity level (1-3, with level 3 being highly toxic); This is the actual amount used. The maximum permissible dosage according to the pharmacopoeia; m represents the quantity of toxic medicinal materials in the current health conditioning program; Compliance score Calculated based on the compatibility between medication complexity (decoction steps, frequency) and patient's lifestyle: Then calculate the total priority score according to the formula: The logical basis is that the importance of drug efficacy > safety > patient compliance; Construct a decision matrix that includes all the elements of each option. Values; normalization processing, calculation of positive ideal solutions (highest efficacy, lowest risk, best compliance) and negative ideal solutions; calculation of the Euclidean distance between each element and the positive / negative ideal solutions, generating priority scores (0-1, 1 being the highest priority); hierarchical display: red highlight (priority ≥ 0.8): core treatment steps (such as the usage of principal drug, standard decoction of toxic medicinal materials); yellow mark (0.5 ≤ priority < 0.8): auxiliary conditioning measures (such as the compatibility of assistant drugs); green mark (priority < 0.5): adjustable items (such as fine adjustment of the dosage of adjuvant drugs).

[0027] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A system for generating customized health conditioning plans using a traditional Chinese medicine four diagnostic instruments, characterized in that, include; The scheme analysis module is used to analyze the initial scheme, extract and standardize key parameters from multi-format data, fuse multi-source data and resolve conflicts, providing a foundation for subsequent processing; the execution steps are as follows: First, the initial plan is analyzed; Input initial scheme parameters: Set the medicinal material composition matrix, where each element includes the medicinal material code, initial dosage, and medicinal material composition matrix. ,in Representative medicinal material code, This represents the initial dosage; it also sets the basic cooking parameters, including the total cooking time. And the curve of temperature change over time ; feature Extraction: Obtaining geographic coordinates from patient information and the current timestamp t accurate to the solar term; where These represent longitude and latitude, respectively. Real-time collection of environmental parameters, including temperature air humidity and water hardness ; Establish a set of correction factors: Geographical correction factor: Geographical correction factor The calculation formula is as follows: ,in Indicates the distance from the main producing area; This is a preset reference distance for the main producing areas; Solar Term Correction Factor: Solar Term Correction Factor It is calculated using the natural exponential function, through the formula: In the formula, For the current timestamp accurate to the solar term; Optimal harvesting season It is a constant; The dynamic parameter optimization module is used to adjust the dosage of medicinal materials based on geographical, seasonal, and environmental factors, optimize decoction parameters, and output a correction plan with visual evidence. The solution display module is used to construct multi-dimensional evaluation indicators to calculate the priority total score, generate scores through decision matrix and calculated distance, and display the elements of the modified solution in a hierarchical manner.

2. The system for generating customized health conditioning plans using a traditional Chinese medicine four-diagnosis instrument according to claim 1, characterized in that, The specific steps of the scheme parsing module in parsing the initial scheme are as follows: First, the initial plan is analyzed. The plan formats include: text data: prescription documents, electronic medical records, free text descriptions; structured data: database records, JSON / XML format; image data: scanned copies of handwritten prescriptions, photos of medicine packaging labels; For text-based data, optical character recognition and natural language processing are used to extract text information, supporting a TCM terminology database; for image-based data, a YOLOv5 model is used to train medicinal herb identification and locate the names and dosage areas of medicinal herbs in prescriptions; structured data is directly mapped to fields. Parameter extraction and standardization: Define key parameters, including: herbal name, dosage, and decoction method; The BiLSTM-CRF model is used to annotate the entities of medicinal materials, dosage, and decoction methods in the text; at the same time, it is dynamically linked to the database of safe dosage of medicinal materials to trigger anomaly warnings. To address the fusion and conflicts of multi-source data, the following methods are used: Priority rules: structured data > image data > text data; fuzzy matching algorithm: calculates descriptive similarity; manual review interface: highlights conflicting items and provides historical prescription references.

3. The system for generating customized health conditioning plans using a traditional Chinese medicine four-diagnosis instrument according to claim 2, characterized in that, Reference distance of the traditional producing areas and the best harvest season The determination process is as follows: The elevation, slope, and aspect parameters of the authentic producing areas were obtained through GIS; historical data from meteorological stations, including average annual temperature, precipitation, and sunshine duration, were integrated, with a time span of ≥20 years; and surface soil samples from the producing areas were collected to determine pH value, organic matter content, and 12 trace elements. DBSCAN clustering was performed on the quality of medicinal materials (i.e., the content of effective components) and geographical parameters to delineate the boundaries of the core authentic region; with the core region as the center, the maximum radiation radius was calculated by expanding outward according to environmental similarity. : ,in The initial expansion radius is calculated through buffer analysis; The average effective ingredient content within the buffer zone; The highest content of effective ingredients in medicinal materials from the core authentic producing areas; Medicinal herb samples were collected from candidate production areas to test the content of active ingredients; a geographical distance-mass decay model was established. ,in The concentration of components in the core region; The attenuation coefficient is defined as follows: For when Distance at time; Optimal harvesting season The determination process is as follows: Fixed sample plots were set up in the traditional producing areas, and medicinal material samples were collected according to the solar terms; the detection indicators were: effective components, dry matter accumulation, and secondary metabolite content. The component content variation curve over time is modeled using Gaussian process regression; the first derivative of the curve is calculated, and the peak point, i.e., the optimal harvest period, is found when the derivative is zero; formula derivation: ;in This is the optimal time for harvesting; To find the parameter values ​​that maximize the function within the time interval t; The first derivative of the effective ingredient content C with respect to time t is zero; Key parameters: accumulated temperature, calculating the effective accumulated temperature from germination to harvest; photoperiod index: combined with the diurnal variation rate; establishing a multiple linear regression model: ;in This is the intercept term of the regression model; , where are regression coefficients, representing the weights of the influence of accumulated temperature and photoperiod on harvesting time, respectively; This is the error term; The effective accumulated temperature is calculated as follows: ,in , and These are the highest and lowest temperatures of the day, respectively. The model is trained using historical data to predict the optimal harvesting window.

4. The system for generating customized health conditioning plans using a traditional Chinese medicine four-diagnosis instrument according to claim 1, characterized in that, The execution steps of the dynamic parameter optimization module are as follows: The dosage correction algorithm is as follows: Basic dosage formula: ,in This is the new dosage after adjustments based on geography and solar terms; This is the initial dosage of the medicinal materials, and the starting value for adjusting the dosage; and These are geographical correction factors and solar term correction factors, respectively. Climate compensation factor: The climate compensation factor is calculated using the formula: ;in As a climate compensation factor; Real-time temperature; Air humidity; Final revised formula: ,in This is the final revised dosage of medicinal materials; This is the new dosage after adjustments based on geography and solar terms; As a climate compensation factor; This is the initial dosage of the medicinal materials; The function is a numerical constraint function, used to... The calculation results are limited to Within the range; Optimization of cooking parameters: Establishment of a multi-objective optimization model: Mathematically expressed as: The constraints are and ℃; among which This refers to the actual ingredient content; The target component content; This refers to the actual total cooking time. The base total time is the initial cooking time standard set; The maximum permissible cooking temperature; Dynamic adjustment is achieved using a fuzzy PID control algorithm: via the formula: ;in, Set the temperature value; The average of the spatiotemporal fit scores for all medicinal materials; This is a spatiotemporal suitability score for a single medicinal herb, calculated based on the degree of matching between the herb and the user's spatiotemporal characteristics; then... , which is the arithmetic mean of the scores of all medicinal materials in the scheme; N is the number of all medicinal materials; The duration of the phase is ,in The duration of a stage refers to the duration of a certain stage in the simmering or boiling process; Based on total duration; Water hardness; Output correction scheme: Generate difference comparison map, highlight the parameter items with correction magnitude greater than 10%; provide a visual path from spatiotemporal parameters, through the calculation process, to the adjustment result as the correction basis chain.

5. The system for generating customized health conditioning plans using a traditional Chinese medicine four diagnostic instruments according to claim 1, characterized in that, The specific operation steps of the solution display module are as follows: Construction of multi-dimensional evaluation indicators: drug efficacy weighting Based on pharmacopoeia databases and clinical research data, the therapeutic efficacy levels of medicinal materials are defined as follows: ,in, The efficacy level of the i-th medicinal material; The dosage of medicinal materials is standardized to a range of 0-1; n represents the total quantity of all medicinal materials in the current health conditioning plan. Security risks Calculate the risk value of toxic medicinal materials: ,in Toxicity level; This is the actual amount used. The maximum permissible dosage according to the pharmacopoeia; m represents the quantity of toxic medicinal materials in the current health conditioning program; Compliance score The calculation is based on the complexity of medication use, including the degree of matching between the decoction process, frequency, and the patient's lifestyle. ; Then calculate the total priority score according to the formula: ; Construct a decision matrix that includes all the elements of each option. Value; normalization processing; calculation of positive and negative ideal solutions; calculation of the Euclidean distance between each element and the positive and negative ideal solutions; generation of priority scores, ranging from 0 to 1. Tiered display: Red highlights indicate priority ≥ 0.8, including core treatment steps; yellow marks indicate priority ≤ 0.5, including auxiliary conditioning measures; green marks indicate priority < 0.5, including adjustable items.

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