Intelligent traditional Chinese medicine prescription processing and preparing system

Abstract

The invention provides an intelligent traditional Chinese medicine prescription processing and preparation system which integrates a prescription acquisition module, a medicinal material selection module, a dosage form analysis module, a dosage form decision module, an intelligent preparation module, an intelligent distribution module and the like. The system can receive traditional Chinese medicine prescriptions made by doctors in real time, intelligently recommend grades and production places of medicinal materials, analyze and display advantages and disadvantages of various suitable dosage forms, and allow patients to autonomously select dosage forms. And the intelligent preparation module adopts automatic equipment and an intelligent control technology, so that the accuracy and high efficiency of the preparation process are ensured. And the intelligent distribution module is responsible for safely and timely delivering the medicine to the patient. In addition, the system further has the functions of medicinal material producing area selection, intelligent medicine decocting, intelligent medicine sorting and the like, and the personalized and intelligent levels of traditional Chinese medicine prescriptions are further improved. Through comprehensive application of advanced technologies, full-chain intelligent management of traditional Chinese medicine prescriptions from issuing to preparation and distribution is realized, the efficiency and accuracy of traditional Chinese medicine preparation are improved, and individual requirements of patients are met.

Description

Technical Field

[0001] The present invention relates to the field of traditional Chinese medicine preparation and processing technology, specifically an intelligent system for processing and preparing traditional Chinese medicine prescriptions. This system integrates modern information technology, automated control technology, and specialized knowledge in traditional Chinese medicine to improve the processing efficiency and preparation accuracy of traditional Chinese medicine prescriptions, as well as the patient experience. Background Art

[0002] The traditional Chinese medicine (TCM) preparation process is plagued by numerous issues, including poor dissemination of prescription information, a lack of standardization in the selection of medicinal materials, outdated formulation processes, a lack of intelligent control during the preparation process, and inefficient distribution. These issues not only impact the quality and efficacy of TCM but also increase medication costs and inconvenience for patients.

[0003] The development of modern science and technology, particularly advancements in information technology, automation, and intelligent control, has provided new opportunities for improving the preparation process of Traditional Chinese Medicine (TCM). However, the market currently lacks a system that fully integrates these technologies to achieve intelligent management of the entire process of TCM prescriptions, from acquisition to preparation and distribution.

[0004] Therefore, this paper proposes an intelligent Chinese medicine prescription processing and preparation system. This system aims to address issues existing in the traditional Chinese medicine preparation process by integrating advanced technologies, improving the quality and efficacy of Chinese medicine, reducing patient medication costs, and enhancing the patient experience. The system enables accurate acquisition and verification of prescription information, intelligent selection and recommendation of medicinal materials, automated analysis and determination of dosage forms, precise control and recording of the preparation process, and efficient distribution and tracking of medicines, providing a new solution for the modern preparation and management of Chinese medicine. Summary of the Invention

[0005] An intelligent Chinese medicine prescription processing and preparation system, characterized by comprising:

[0006] Prescription acquisition module: Through a data interface connected to the medical information system or physician workstation, it receives the Chinese medicine prescription information written by the physician for the patient in real time or on a scheduled basis, including key data such as the patient's basic information, drug name, dosage, usage, and special preparation requirements. It also performs format verification and data integrity checks to ensure the accuracy and validity of the prescription information. If the prescription information is incomplete or contains errors, the system automatically sends a reminder to the physician, requesting a new prescription or correction.

[0007] The Herbal Material Selection Module integrates a highly user-friendly interactive interface. Based on the list of medicines in the prescription, it intelligently generates a detailed list of options, including herbal material grades (such as ordinary, premium, and selected) and their corresponding prices. It also provides a description of the herbal material grade, including key information such as source, production process, quality assurance, and active ingredient content. Furthermore, a built-in intelligent recommendation engine comprehensively considers the patient's historical choices, financial status, health status, and physician recommendations to recommend the most suitable herbal material grade for the patient.

[0008] Dosage Form Analysis Module: A comprehensive dosage form preparation knowledge base is built in, covering a variety of common and uncommon TCM dosage forms, including tablets, capsules, granules, and decoctions. Based on factors such as the drug ingredients in the prescription, patient needs, and preparation process requirements, it automatically analyzes all suitable dosage forms that can be provided by the prescription and lists the advantages and disadvantages of each dosage form, including key factors such as stability, bioavailability, taste, ease of administration, and price. The module uses charts, text descriptions, video animations, and interactive interfaces to intuitively display the information.

[0009] Dosage Form Decision Module: Through a carefully designed user interface, the advantages and disadvantages of each dosage form provided by the dosage form analysis module are clearly presented, allowing patients to freely select the most suitable dosage form based on their needs, personal preferences, and physician recommendations. A built-in intelligent prompt function immediately issues a warning and recommends an alternative dosage form when the selected dosage form is incompatible or potentially conflicting with the drug ingredients in the prescription. At the same time, the patient's dosage form selection history is recorded to provide data support for subsequent intelligent recommendations.

[0010] Intelligent Preparation Module: Based on the patient's selection in the dosage form determination module, the module automatically enters the preparation process for the corresponding dosage form. This includes steps such as raw material preparation and quality inspection, formulation and process design, dosage form preparation and process control, finished product quality inspection, packaging, and label printing. Advanced automation equipment and intelligent control technology are used to ensure the accuracy and efficiency of the preparation process. Key data and information during the preparation process are also recorded, and a traceability mechanism is established to ensure the traceability of the drug source and preparation process.

[0011] Intelligent delivery module: Prepares delivery matters according to patient needs, including packaging, boxing, and logistics arrangements, ensuring the safety and timeliness of drug transportation.

[0012] Furthermore, it is characterized in that the medicinal material selection module further includes a medicinal material origin selection function, allowing patients to directly select the origin of the medicinal material, or select according to factors such as grade classification, severity of disease, etc., so as to obtain medicinal materials that better meet personal needs;

[0013] The specific steps are as follows:

[0014] Step 1: Construction and integration of medicinal material origin database

[0015] Database contents:

[0016] Integrate data from major Chinese medicinal material production areas across the country, including authentic production areas (such as Ningxia wolfberry and Yunnan Panax notoginseng), non-authentic production areas, and their corresponding quality indicators (active ingredient content, pesticide residue test results), price ranges, and supply stability;

[0017] Correspondence between the grade of medicinal materials (common grade / high quality grade / selected grade) and the place of origin, for example:

[0018] Selected-grade Astragalus: Shanxi Hunyuan (astragaloside ≥ 0.04%) is preferred;

[0019] Ordinary grade Astragalus: You can choose the one produced in Longxi, Gansu (astragaloside IV ≥ 0.02%).

[0020] Dynamic update: By connecting to Chinese medicinal materials trading platforms (such as Yaotong.com), price fluctuations and supply information at the place of origin are updated in real time.

[0021] Step 2: Design of the Origin Selection Interactive Interface

[0022] Function entry: Added a new "Origin Filter" option in the interactive interface of the medicinal material selection module, supporting the following modes:

[0023] Direct selection mode: patients manually select a specific place of origin (e.g., “Yunnan Wenshan Panax notoginseng”);

[0024] Intelligent recommendation mode: The system automatically matches the origin according to the severity of the disease:

[0025] Emergency / severe illness: Priority is given to authentic production areas (high content of active ingredients);

[0026] Chronic diseases / mild illnesses: We recommend non-authentic production areas with better cost-effectiveness.

[0027] Visual display:

[0028] Use map annotation to show the distribution of medicinal material production areas (such as highlighting authentic production areas);

[0029] Provide origin comparison cards to show origin characteristics (such as climate, planting history), active ingredient data and price differences.

[0030] Step 3: Intelligent recommendation based on origin and grade

[0031] Recommended logic:

[0032] Economic priority: If the patient has a limited budget, the system will prioritize recommending lower-priced origins of the same grade (e.g., ordinary-grade astragalus should be produced in Gansu);

[0033] Prioritize efficacy: If the patient's disease is serious (such as adjuvant treatment for cancer), the system recommends high-end medicinal materials from authentic production areas (such as selected ginseng produced in Changbai Mountain, Jilin).

[0034] Conflict prompt: When the patient chooses high-end products but has insufficient budget, the system automatically prompts "origin downgrade suggestion" (such as switching from selected-grade Shanxi Astragalus to high-quality Inner Mongolia Astragalus).

[0035] Step 4: Dynamic screening of disease severity

[0036] Disease classification matching:

[0037] Emergency / severe cases: Mandatory use of medicinal materials from authentic production areas to ensure the highest active ingredient content (e.g., total saponins of Panax notoginseng ≥ 8%);

[0038] Chronic diseases: Open up non-authentic production area options to allow patients to adjust according to their budget.

[0039] Sample Application:

[0040] If the patient is diagnosed with acute angina pectoris (severe), the system will automatically select Panax notoginseng produced in Wenshan, Yunnan (total saponins ≥ 9%) and block other production areas;

[0041] The patient suffers from chronic insomnia (mild), and the system recommends Hubei Poria cocos (Poria cocos polysaccharide ≥ 25%) with high cost-effectiveness.

[0042] Step 5: User interaction and selection confirmation

[0043] Multi-condition screening: Patients can select "origin + grade + disease priority" at the same time through the interface, for example:

[0044] Select "Ningxia wolfberry (authentic production area) + high-quality grade + chronic disease", the system generates a matching result (polysaccharide content ≥3.5%, mid-range price); select "Xinjiang wolfberry (non-authentic) + ordinary grade + mild disease", the system displays comparative data of a 20% reduction in cost but a 15% reduction in effective ingredients.

[0045] Final confirmation: After the patient confirms, the system will bind the origin information with the grade of the medicinal materials and pass it to the dosage form analysis module for subsequent dosage form cost accounting (for example, authentic medicinal materials may increase the cost of granule preparation).

[0046] Step 6: Data Recording and Intelligent Learning

[0047] Historical records: Store the origin, grade and reasons for each patient's selection (such as "designated authentic production area" or "accepted system downgrade recommendation");

[0048] Machine learning optimization: Optimize recommendation algorithms based on historical data, for example:

[0049] It was found that patients in a certain region preferred local medicinal materials (for example, users in Guangdong often chose Huazhou Tangerine Peel), and the recommendation priority was adjusted.

[0050] Furthermore, the intelligent preparation module is characterized by including an intelligent decoction function that can automatically select appropriate decoction utensils, control the amount of water added, the heat and time, and handle decoction methods for special medicinal materials, such as decocting first, adding later, or wrapping and decocting, to ensure the accuracy and efficiency of the decoction process. At the same time, it provides decoction technique guidance and precautions to help users better master decoction methods.

[0051] Step 1: Construction of decoction knowledge base and rule base

[0052] Knowledge Base Contents:

[0053] Decoction Utensil Library: This stores characteristic data of various decoction utensils (such as ceramic pots, stainless steel pots, and smart decoction machines), including material thermal conductivity, capacity, applicable scenarios (such as home / hospital), and cleaning difficulty.

[0054] Water volume calculation rules: Based on the water absorption of the medicinal materials and the concentration requirements of the medicinal solution (e.g., antipyretics require less decoction, tonics require longer decoction), the water addition formula is automatically generated (e.g., medicinal material weight × water absorption coefficient + target medicinal solution volume);

[0055] Heat and time parameters: Associate the properties of medicinal materials (e.g., antipyretics require high heat and fast decoction, while minerals require low heat and long decoction), and preset the decoction time and temperature curve for different medicinal materials;

[0056] Special decoction rules: record the operating standards for special methods such as decocting first, adding later, wrapping and decocting, and melting (e.g., decocting aconite for 30 minutes first and adding mint for 5 minutes later);

[0057] Step 2: Prescription analysis and decoction parameter generation

[0058] Extracting medicinal material properties: Identify medicinal materials that require special treatment from the prescription (such as gypsum decocted first and Amomum villosum added later) and mark their priority;

[0059] Intelligent parameter matching:

[0060] Device selection: Automatically recommend devices based on drug volume (e.g., large-capacity smart decoction machine for >500g) and patient needs (e.g., portability);

[0061] Calculation of water addition: For example, if the prescription contains Poria cocos (water absorption coefficient 1.5), the system calculates the amount of water to be added as the weight of the medicinal material × 1.5 + the target liquid volume of 200ml;

[0062] Heat and time: For antipyretic herbs (e.g., ephedra), use high heat (100°C) and simmer quickly (10 minutes); for tonic herbs (e.g., Rehmannia glutinosa), use low heat (80°C) and simmer slowly (40 minutes);

[0063] Step 3: Decoction utensils and water addition control

[0064] Appliance linkage control: the system automatically starts the equipment and sets parameters (such as temperature and water volume);

[0065] Dynamic water replenishment: The water volume is monitored in real time during the decoction process. When it is lower than the threshold (such as 50ml remaining), the water volume is automatically replenished.

[0066] Step 4: Dynamically adjust the heat and time

[0067] Heat control:

[0068] High-heat stage (antipyretic drugs): quickly raise the temperature to 100°C and shorten the decoction time to retain volatile components;

[0069] Simmering stage (tonic medicine): maintain 80℃ and prolong the boiling time to improve the dissolution of active ingredients;

[0070] Countdown management: The interface displays the remaining decoction time and reminds the user to implement the process in special steps (such as 5 minutes before adding the last medicinal material). Step 5: Automated processing of special decoction methods

[0071] Decoction first / add herbs later:

[0072] The system automatically divides the decoction process, for example:

[0073] First, decoct the herbs (such as gypsum) separately for 30 minutes;

[0074] Add the remaining herbs in the last 5 minutes (later);

[0075] Use the compartment function of the smart medicine decoction machine to automatically dispense medicine in batches or prompt the user to dispense medicine in batches;

[0076] Wrapping and decoction operation: For sticky herbs (such as plantain seeds), gauze wrapping or filter netting is automatically used to avoid turbidity of the medicinal solution;

[0077] Step 6: Instructions on decoction techniques and precautions

[0078] Real-time interactive guidance:

[0079] Display the decoction step animation through the interface (such as "the first decoction of herbs has been decocted for 25 minutes, and 5 minutes remain");

[0080] Risk Warning:

[0081] When it is detected that the decoction time of toxic medicinal materials (such as aconite) is insufficient, the device will be forced to lock and issue a warning;

[0082] Advise patients to avoid using iron utensils to decoct acidic herbs (such as Schisandra chinensis);

[0083] Step 7: Data Recording and Machine Learning Optimization

[0084] Traceability of the decoction process: Recording decoction parameters (temperature curve, water volume changes, and time of drug administration) and linking them to patient efficacy feedback (e.g., efficacy scores);

[0085] Intelligent optimization: Analyze historical data through machine learning and automatically adjust decoction rules (for example, if it is found that patients in a certain area prefer to shorten the decoction time, the parameters will be optimized to suit their habits).

[0086] Furthermore, the system is characterized in that it also includes an intelligent drug sorting device, which realizes automatic sorting and accurate distribution of drugs through the coordinated operation of a loading unit, a placement unit, a drug taking unit and a unloading unit, further improving the automation and accuracy of the system; the intelligent drug sorting device (sorting medicinal materials) realizes automatic sorting and distribution through the following coordinated units, and the specific steps are as follows:

[0087] Step 1: Device architecture and unit function definition

[0088] The intelligent drug sorting equipment consists of the following core units, which are coordinated and operated by IoT technologies (such as PLC control and industrial bus):

[0089] Function: Receive the medicinal materials to be sorted from the medicinal material warehouse or preparation module, and transport them to the sorting area through a conveyor belt or vibrating feeder;

[0090] Technical support: Dynamic weighing sensors and visual recognition systems are used to detect the weight and integrity of medicinal materials in real time;

[0091] Place the cell:

[0092] Function: Dynamically allocate storage compartments based on medicinal material type, batch or order requirements, supporting multi-level classified storage;

[0093] Technical support: The medicine storage grid is equipped with RFID tags to record information such as the source and expiration date of the medicinal materials, and synchronize with the system database in real time;

[0094] Medication collection unit:

[0095] Function: Accurately grab the target medicinal materials through the robotic arm or AGV car;

[0096] Technical support: Combining force control sensors and visual positioning technology to ensure grasping accuracy ≤±0.1mm;

[0097] Unloading unit:

[0098] Function: Pack the sorted medicinal materials according to the order, automatically attach logistics labels and check the weight (the error exceeds ±5% and triggers an alarm);

[0099] Technical support: Dynamic weighing compensation technology is used to ensure that the packaging error is ≤0.5g;

[0100] Step 2: Automated control of sorting process

[0101] Identification and classification of medicinal materials:

[0102] The visual recognition system scans the morphology, color, and barcode of the medicinal material and matches it with the medicinal material characteristics in the database (such as the spindle shape of Panax notoginseng and the fibrous root of ginseng);

[0103] Combined with weight sorting technology, medicinal materials are classified according to preset rules (such as grading Gastrodia elata by gram weight);

[0104] Path planning and sorting execution:

[0105] After the system analyzes the order requirements, it dynamically plans the robot arm's motion trajectory and gives priority to expedited orders;

[0106] The status of medicinal materials is monitored in real time during the sorting process. If an abnormality is detected (such as insect-infested medicinal materials), the rejection mechanism is triggered and manual intervention is notified;

[0107] Step 3: Quality Control and Error Handling

[0108] Quality Inspection:

[0109] Embed multiple quality checks in the sorting process:

[0110] Component detection: Rapidly analyze the active ingredient content of medicinal materials (such as notoginseng saponins ≥ 8%) through near-infrared spectrometry;

[0111] Impurity removal: Use color sorters to automatically separate foreign matter or spoiled medicinal materials

[0112] Bug fixes:

[0113] If the sorting result does not match the order (such as weight deviation or mix-up of medicinal materials), the system automatically starts the re-sorting process and records the error type for machine learning optimization;

[0114] Step 4: Parallel processing of multiple orders and priority management

[0115] Parallel sorting strategy:

[0116] Partitioned storage grids are used to physically isolate regular orders from expedited orders to avoid cross contamination.

[0117] During peak hours, AGV cluster collaboration is enabled to increase throughput to 200 pieces per hour;

[0118] Intelligent scheduling:

[0119] Dynamically adjust the sorting order based on the characteristics of the medicinal materials (e.g., hygroscopic Poria cocos needs to be sorted first) and the urgency of the order;

[0120] Step 5: Data tracing and intelligent optimization

[0121] Full process traceability:

[0122] Record sorting operation logs (such as grabbing time, robot arm number, and medicinal material batch), associate them with traceability codes, and support reverse query of production sources. Machine learning optimization:

[0123] Analyze historical sorting data (such as common error types and efficiency bottlenecks) to optimize sorting algorithms and storage grid layout.

[0124] Furthermore, it is characterized in that the specific implementation steps of the medicinal material selection module are as follows:

[0125] (a) The medicinal material selection module receives the Chinese medicine prescription information transmitted by the prescription acquisition module, which includes a list of medicines in the prescription and relevant information of the patient;

[0126] (b) Based on the list of drugs in the prescription, the herbal medicine selection module accesses the system's herbal medicine database, which stores detailed information on various herbal medicines, including different grades (such as ordinary grade, premium grade, and selected grade) and their corresponding prices, sources, production processes, quality assurance, and active ingredient content;

[0127] (c) The medicinal material selection module intelligently generates a list of options including the grades of the medicinal materials and their detailed information, and presents the list to the user in a user-friendly manner, allowing the user to view and compare the characteristics and prices of medicinal materials of different grades;

[0128] (d) The system's built-in intelligent recommendation engine recommends one or more most suitable medicinal material grades based on the patient's historical choices, financial status, health status, and physician's advice. This recommendation process may involve complex algorithms and data analysis to ensure the accuracy and personalization of the recommendations;

[0129] (e) Users can view the intelligently recommended medicinal material grades on the system interface and select them according to their needs and preferences. If the user wishes to select medicinal materials of a different grade, the system also allows the user to freely change the selection;

[0130] (f) Once the user makes a selection, the herbal material selection module will record this selection and pass it on to the subsequent preparation module for preparation of the preparation based on the selected herbal material. This selection will also be recorded in the historical database to provide data support for subsequent intelligent recommendations.

[0131] Furthermore, it is characterized in that the specific implementation steps of the dosage form analysis module are as follows:

[0132] (a) The dosage form analysis module receives the TCM prescription information transmitted by the prescription acquisition module. This information includes key data such as the patient's basic information, the list of prescribed drugs, the dosage, usage, special preparation requirements of each drug, and the patient's financial status or willingness to pay. This information together forms the basis for selecting the dosage form;

[0133] (b) Based on the list of drugs in the prescription, the dosage form analysis module accesses the system's built-in knowledge base of traditional Chinese medicine dosage forms. This knowledge base not only stores detailed information on various traditional Chinese medicine dosage forms, such as tablets, capsules, granules, decoctions, pills, powders, and other common and uncommon dosage forms, but also records in detail the preparation process, stability, bioavailability, taste, ease of administration, and other characteristics of each dosage form, as well as the cost structure and approximate price range of each dosage form;

[0134] (c) The dosage form analysis module comprehensively considers the drug ingredients in the prescription, patient needs (such as age, gender, disease type, medication habits, etc.), preparation process requirements, special preparation requirements, and the patient's financial status or willingness to pay, and automatically analyzes and screens all suitable dosage forms that can be provided for the prescription, while also evaluating the cost-effectiveness of each dosage form;

[0135] (d) For each selected suitable dosage form, the dosage form analysis module further analyzes its advantages and disadvantages, covering key factors such as stability, bioavailability, taste, ease of administration, and price. This information is presented to users intuitively and comprehensively through various forms such as charts, text descriptions, video animations, and interactive interfaces, ensuring that users can clearly understand the characteristics and pricing information of each dosage form;

[0136] (e) Users (e.g., patients or physicians) can view detailed information on the advantages, disadvantages, and pricing of various dosage forms through the system interface, allowing them to select the most appropriate dosage form based on their needs, personal preferences, physician recommendations, and financial affordability. The system allows users to freely switch between and view comparative analysis results of different dosage forms, enabling them to make more informed and cost-effective choices.

[0137] Furthermore, it is characterized in that the specific implementation steps of the dosage form determination module are as follows:

[0138] (a) The dosage form determination module receives prescription information and analysis data on the advantages and disadvantages of each dosage form from the dosage form analysis module. This data includes the drug ingredients in the prescription, patient needs, preparation process requirements, and key factors such as stability, bioavailability, taste, and ease of administration of each suitable dosage form;

[0139] (b) The dosage form decision module presents this information to patients in an intuitive and understandable manner through a carefully designed user interface. The interface clearly lists the advantages and disadvantages of each dosage form and may use various forms such as charts, text descriptions, video animations, and interactive elements to enable patients to fully understand and compare the characteristics of different dosage forms;

[0140] (c) Patients can freely select the most suitable dosage form on the interface based on their needs, personal preferences, and physician recommendations. The system allows patients to review and compare the advantages and disadvantages of different dosage forms to make more informed choices;

[0141] (d) When a patient selects a dosage form, the intelligent prompt function built into the dosage form decision module immediately checks whether the selected dosage form is incompatible or potentially conflicting with the drug ingredients in the prescription. If a conflict exists, the system immediately issues a warning and recommends an alternative dosage form to the patient, providing a detailed explanation and justification.

[0142] (e) If the patient accepts the alternative dosage form recommended by the system, the dosage form decision module updates the selection result; if the patient insists on the original choice, the system records the patient's decision and continues the subsequent process;

[0143] (f) The dosage form decision module records the patient's dosage form selection history, including the dosage form selected each time, the time of selection, and the reason for selection (if provided). This data provides important support for subsequent intelligent recommendations and personalized services;

[0144] (g) Finally, the dosage form decision module transmits the patient's dosage form selection result to the intelligent preparation module so that the corresponding preparation procedure can be entered according to the selected dosage form.

[0145] Furthermore, it is characterized in that the specific implementation steps of the intelligent preparation module are as follows:

[0146] (a) Receiving instructions: The intelligent preparation module receives instructions from the dosage form determination module, which contains key information such as the dosage form selected by the patient, the list of drugs in the prescription and their dosage;

[0147] (b) Raw material preparation and quality inspection: Based on the prescription information, the intelligent preparation module automatically retrieves the required medicinal materials from the storage system and performs quality inspection on the medicinal materials using built-in quality inspection equipment to ensure that the medicinal materials meet the preparation requirements;

[0148] (c) Preparation formula and process design: Based on the drug ingredients in the prescription, the dosage form selected by the patient, and the preparation process requirements, the intelligent preparation module automatically designs the preparation formula and preparation process, including parameters such as the ratio of each medicinal material, mixing sequence, preparation temperature, and time;

[0149] (d) Dosage Form Preparation and Process Control: Based on the designed formulation and process, the intelligent preparation module activates the corresponding preparation equipment, such as a grinder, mixer, tablet press, and capsule filler, to prepare the dosage form. During the preparation process, the module uses sensors to monitor the preparation environment (e.g., temperature, humidity) and preparation status (e.g., mixing uniformity, tablet hardness, etc.) in real time, and automatically adjusts the preparation parameters based on the monitoring results to ensure the stability and accuracy of the preparation process.

[0150] (e) Finished product quality inspection: After preparation, the intelligent preparation module conducts quality inspection on the finished product, including appearance inspection, weight difference, content determination, etc., to ensure that the finished product meets the quality standards;

[0151] (f) Packaging and label printing: Finished products that pass inspection will be sent to the packaging line for packaging. The intelligent preparation module will automatically print and paste labels containing key information such as patient information, drug name, usage and dosage;

[0152] (g) Recording and tracing: The intelligent preparation module records key data and information in the preparation process, such as the source of medicinal materials, preparation time, preparation personnel, quality inspection results, etc., and establishes a traceability mechanism so that the source and preparation process of the medicine can be traced when necessary.

[0153] Furthermore, it is characterized in that the specific implementation steps of the intelligent distribution module are as follows:

[0154] (a) Receiving delivery instructions: The intelligent delivery module first receives delivery instructions from other modules in the system (such as the intelligent preparation module). The instructions contain key data such as patient delivery information, drug information, and delivery requirements;

[0155] (b) Packaging and Boxing: Based on the delivery instructions received, the intelligent delivery module automatically activates the packaging equipment, packages the prepared drugs according to the specified packaging requirements, and places them in dedicated delivery boxes. During the packing and boxing process, the module uses built-in sensors and control systems to monitor key parameters such as the integrity of the packaging materials, the placement of the drugs, and the sealing of the delivery boxes in real time to ensure the safety and integrity of the drugs during transportation;

[0156] (c) Logistics Arrangement: After packaging and boxing are completed, the intelligent delivery module automatically selects the appropriate logistics company and generates a detailed logistics delivery plan based on factors such as the patient's delivery address, delivery time requirements, and the characteristics of the medication. The module communicates with the logistics company in real time through the built-in logistics management system to track logistics status and ensure that the medication is delivered to the patient on time and accurately.

[0157] (d) Delivery tracking and feedback: During the delivery process, the intelligent delivery module monitors the logistics status in real time through the built-in tracking system, including information such as delivery location and estimated arrival time, and provides delivery progress inquiry services to patients through the system interface or through SMS and email. At the same time, the module also receives delivery feedback from the logistics company, including information such as delivery success, delivery failure, or the need for secondary delivery, and takes appropriate measures based on the feedback results;

[0158] (e) Recording and Traceability: The intelligent delivery module records key data and information during the delivery process, such as delivery instructions, packaging time, packing information, logistics company selection, and logistics status tracking records, and establishes a traceability mechanism. When necessary, these records can be used to trace the delivery process and status of drugs, ensuring traceability and transparency of the delivery process. DETAILED DESCRIPTION

[0159] A specific implementation example of an intelligent Chinese medicine prescription processing and preparation system

[0160] Background: With the continuous advancement of modern medical technology, patients are increasingly demanding personalized and intelligent medical services. The traditional Chinese medicine prescription and preparation process is cumbersome and difficult to meet the individual needs of different patients. To address this, this paper proposes an intelligent Chinese medicine prescription processing and preparation system designed to simplify the prescription process, improve preparation efficiency, and ensure drug quality and patient safety.

[0161] Patient Information: Patient Name: Ms. Li Age: 45 Diagnosis: Chronic Gastritis

[0162] Clinical use process:

[0163] Prescription Obtaining:

[0164] Ms. Li went to the hospital for treatment, and the doctor prescribed her a Chinese medicine prescription for chronic gastritis;

[0165] Prescription information is transmitted to the system of the present invention in real time through the medical information system. After receiving the prescription, the system automatically performs format verification and data integrity check to ensure the accuracy of the prescription information.

[0166] Herbal medicine selection:

[0167] Based on the list of medicines in the prescription, the system intelligently generates a detailed list of options including the grade of the medicine and its corresponding price;

[0168] Taking into account Ms. Li's financial situation and health status, the system recommends high-quality medicinal materials and provides a description of the grade of the medicinal materials, including key information such as source, production process, quality assurance, and active ingredient content;

[0169] Ms. Li viewed the recommended medicinal materials through the system interface and confirmed her selection.

[0170] Dosage form analysis:

[0171] The system automatically analyzes the appropriate dosage form, such as granules, based on the drug ingredients in the prescription, Ms. Li's needs, and the preparation process requirements. The system lists the advantages and disadvantages of granules, including good stability, moderate taste, and easy administration, and displays them intuitively through charts, text descriptions, and interactive interfaces.

[0172] Dosage form determination:

[0173] After learning about the advantages and disadvantages of each dosage form through the system interface, Ms. Li chose granules as the final dosage form.

[0174] The system intelligently indicates that the selected dosage form is compatible with the drug ingredients in the prescription, with no potential conflicts. It also records Ms. Li's dosage form selection history, providing data support for subsequent intelligent recommendations.

[0175] Smart preparation:

[0176] Based on Ms. Li’s selection, the system automatically enters the granule preparation procedure.

[0177] The preparation process includes steps such as raw material preparation and quality inspection, formulation and process design, dosage form preparation and process control, finished product quality inspection, packaging and label printing.

[0178] The system uses advanced automation equipment and intelligent control technology to ensure the accuracy and efficiency of the preparation process. At the same time, it records key data and information during the preparation process and establishes a traceability mechanism.

[0179] Smart delivery:

[0180] Ms. Li selected the express delivery method on the system interface and filled in the delivery address.

[0181] The system prepares delivery matters according to Ms. Li's needs, including packaging, boxing, and logistics arrangements.

[0182] The medicine remained safe during transportation and was delivered to Ms. Li promptly. The system provides logistics tracking, allowing Ms. Li to check the delivery status of the medicine at any time.

[0183] Clinical Results: After receiving the medication, Ms. Li took it according to her physician's instructions and the drug package insert. After a period of treatment, Ms. Li's chronic gastritis symptoms were alleviated and her physical condition improved. She expressed high satisfaction with the intelligent service provided by the system and the quality of the medication.

[0184] Clinical example of the implementation process of the origin selection function

[0185] Background Overview

[0186] A TCM hospital's intelligent prescription processing and preparation system integrates a medicinal material origin selection function. This feature allows patients to directly select the origin of the medicinal material or receive intelligent recommendations based on their needs, budget, and medical condition. The following is a specific clinical example demonstrating the operational process and effectiveness of this feature in practice.

[0187] Patient Information

[0188] Patient's name: Mr. Zhang

[0189] Age: 50

[0190] Disease diagnosis: Chronic atrophic gastritis (mild)

[0191] Prescription requirements: Long-term Chinese medicine conditioning is required to relieve stomach discomfort and promote gastric mucosal repair.

[0192] Origin selection process

[0193] First look at the origin selection function:

[0194] When Mr. Zhang first used the system, he noticed the newly added "origin screening" option through the interactive interface of the herbal medicine selection module. He was curious about this feature and decided to try it out.

[0195] Learn about the origin of medicinal materials:

[0196] On the origin screening screen, Mr. Zhang saw a map showing the distribution of medicinal material origins, along with cards comparing the characteristics of each origin. He was particularly interested in Poria cocos, as it is a medicinal ingredient that requires long-term use in prescriptions.

[0197] The system shows that the polysaccharide content of Poria cocos from the authentic production area of Hubei is ≥25%, and the price is moderate; while Poria cocos from non-authentic production areas such as Henan, although slightly cheaper, has a slightly lower polysaccharide content and poor supply stability.

[0198] Intelligent recommendation and selection:

[0199] Considering his mild condition requiring long-term treatment, Mr. Zhang opted for the "Smart Recommendation Mode." Based on the severity of his condition and his budget, the system recommended Hubei Poria (premium grade), a highly cost-effective product.

[0200] The system also suggested downgrading the origin of the product. Choosing a lower-grade Poria cocos (such as ordinary grade) would further reduce costs, but the active ingredients would be reduced. After careful consideration, Mr. Zhang decided to stick with the premium grade to ensure efficacy.

[0201] Dynamic screening of disease severity and urgency:

[0202] Because Mr. Zhang's condition was mild, the system allowed him to adjust his choice of origin based on his budget. He tried different combinations of origin and grade, ultimately settling on high-quality Poria cocos from Hubei as his long-term medication.

[0203] User interaction and selection confirmation:

[0204] Mr. Zhang selected the combination of "Hubei Poria (premium grade) + chronic diseases" on the interface and checked the matching results generated by the system. He expressed satisfaction with the results and confirmed his selection.

[0205] The system then binds the origin information with the grade of the medicinal material and passes it to the dosage form analysis module for subsequent dosage form cost accounting and preparation.

[0206] Data recording and intelligent learning:

[0207] The system records Mr. Zhang's selection process, the origin and grade he chose, and the reasons for his choice. This data will be used for subsequent machine learning optimization to more accurately meet the patient's needs.

[0208] For example, the system may find that patients with chronic atrophic gastritis like Mr. Zhang generally prefer to choose high-quality Poria cocos produced in Hubei, thereby increasing the priority of this option in future recommendations.

[0209] Specific implementation case of intelligent decoction function in intelligent Chinese medicine prescription processing and preparation system

[0210] 1. Case Background

[0211] Patient Wang, female, 45 years old, went to a traditional Chinese medicine hospital for treatment due to long-term chronic gastritis. The doctor prescribed a prescription containing a variety of Chinese medicinal materials based on her condition, including special medicinal materials such as aconite that needs to be decocted first, amomum villosum that needs to be added later, and plantain seeds that need to be decocted. In order to ensure the accuracy and efficiency of the decoction process, the doctor recommended that the patient use the intelligent decoction function in the intelligent Chinese medicine prescription processing and preparation system to decoct the medicine; II. Implementation steps of the intelligent decoction function

[0212] Prescription analysis and decoction parameter generation:

[0213] After receiving the prescription information, the system automatically analyzes the properties of the medicinal materials, identifies that aconite root is the first medicinal material to be decocted, amomum villosum is the last medicinal material to be added, and plantain seed is the medicinal material to be decocted, and marks their priority;

[0214] Based on the weight of the medicinal materials and the target liquid volume, the system calculates the amount of water to be added as the total weight of the medicinal materials multiplied by the water absorption coefficient (taking into account the water absorption of different medicinal materials) plus the target liquid volume;

[0215] The system has preset heat and time parameters. Aconite is quickly simmered over high heat (for a short period of high temperature to remove toxins) before switching to low heat for slow simmering. Amomum villosum is added at the end and then switched to low heat to maintain the temperature. Plantain seed requires a steady heat throughout the simmering process.

[0216] Decoction utensils and water addition control:

[0217] The system automatically recommends a large-capacity intelligent decoction machine based on the dosage and sets parameters such as temperature and water volume;

[0218] After the decoction machine is started, the system automatically adds the calculated amount of water and monitors the changes in water volume in real time;

[0219] Dynamic adjustment of temperature and time:

[0220] In the high-fire stage, the system heats up quickly to the set temperature, and the aconite is briefly boiled at high temperature to remove the toxins.

[0221] Then, turn to the simmering stage, maintain a stable temperature to slowly fry the aconite, while keeping the temperature of the area where the Amomum villosum is located, ready to be added later;

[0222] The countdown management interface displays the remaining decoction time and reminds the user 5 minutes before adding the last medicinal material;

[0223] Special decoction method automation

[0224] The system automatically divides the decoction process, first decocting the aconite root for the specified time;

[0225] In the last 5 minutes of decoction of the remaining herbs, the system automatically adds Amomum villosum (added last);

[0226] For Plantago seeds, the system automatically uses gauze bags or filters to wrap and decoct them to avoid turbidity of the liquid.

[0227] Tips for decoction techniques and precautions:

[0228] The system displays the decoction step animation through the interface and updates the decoction progress in real time;

[0229] Voice prompts for key operations, such as "Please add the final herbal ingredient Amomum villosum";

[0230] When the system detects that the decoction time of aconite is insufficient, it will forcibly lock the decoction machine and issue a warning to ensure that the toxic herbs are fully decocted;

[0231] Advise patients to avoid using iron utensils to decoct acidic herbs (although this is not included in the prescription, it is a general precaution for decoction);

[0232] Data logging and machine learning optimization:

[0233] The system records key data such as temperature curve, water volume change, and medicinal material dosing time during the decoction process;

[0234] During subsequent patient visits, correlate the patient's efficacy feedback (e.g., efficacy scores) for machine learning analysis;

[0235] Through machine learning, the system can automatically adjust the decoction rules to suit the preferences and habits of patients in different regions, such as shortening or extending the decoction time.

[0236] Case background

[0237] Patient: Mr. Wang, 58 years old

[0238] Diagnosis: Chronic gastritis with indigestion

[0239] Prescription requirements: The Chinese medicine prescriptions issued by doctors include medicinal materials such as Atractylodes macrocephala, Poria cocos, and dried tangerine peel. The grade of medicinal materials must be selected and the preparation must be completed according to the patient's personalized needs.

[0240] Integration of implementation process and clinical practice

[0241] 1. Receiving and verifying prescription information:

[0242] Physicians transmit prescriptions to the system through the medical information system. The system automatically verifies the completeness of the prescription (such as the name of the medicinal material, dosage, and special preparation requirements) and links it with the patient's basic information (age, medical history, and financial status). If any prescription information is missing, the system triggers a reminder mechanism to require the physician to correct it.

[0243] 2. Retrieving the medicinal material database and generating options

[0244] Based on the list of herbs in the prescription (Atractylodes macrocephala, Poria cocos, and dried tangerine peel), the system accesses the herbal medicine database to retrieve detailed information on herbs of different grades:

[0245] Ordinary grade: Commonly grown in the origin, with active ingredient content ≥80%, and lower price;

[0246] Premium grade: authentic medicinal materials, hand-selected, active ingredients ≥ 90%, moderately priced;

[0247] Selected grade: GAP certified planting base, strict processing technology, active ingredients ≥ 95%, higher price.

[0248] The database also contains data such as the source of medicinal materials (such as Atractylodes macrocephala is produced in Zhejiang) and production processes (such as the nine-steaming and nine-drying process of Poria cocos), which are presented in an interactive list for patients to compare.

[0249] 3. Personalized decision-making of intelligent recommendation engine:

[0250] The system generates recommendations based on the following factors:

[0251] Patient's economic status: Mr. Wang is a working class person, so the system prioritizes recommending high-quality medicinal materials;

[0252] Health status: Chronic gastritis requires long-term conditioning, and the system recommends selected grade Atractylodes macrocephala to improve the efficacy;

[0253] Physician's advice: Physicians mark "avoid irritating ingredients" and the system filters out products that may contain impurities in ordinary tangerine peel

[0254] The recommendation algorithm is based on historical case data (such as efficacy data of similar patients choosing high-quality medicinal materials) and deep learning models to ensure accurate matching.

[0255] User interaction and selection optimization

[0256] Mr. Wang checks the recommended solution on the system interface:

[0257] Atractylodes macrocephala (selected grade), Poria cocos (premium grade), Tangerine peel (premium grade);

[0258] The system provides a comparison chart showing that the active ingredient content of selected-grade Atractylodes macrocephala (95%) is significantly higher than that of ordinary-grade Atractylodes macrocephala (80%), and is supported by clinical research data.

[0259] The patient adjusts his choice according to his budget and changes the Atractylodes macrocephala to the premium grade. The system updates the price and efficacy evaluation in real time, and prompts that "the premium grade Atractylodes macrocephala can meet the treatment needs and has a better cost-effectiveness."

[0260] Data recording and preparation connection

[0261] After the user completes their selection, the system transmits the herbal grade information (Atractylodes macrocephala - premium grade, Poria cocos - premium grade, Tangerine peel - premium grade) to the preparation module and records it in the patient's history database. During subsequent follow-up visits, the system can optimize recommendations based on historical selections (e.g., automatically excluding herbs that have previously caused mild discomfort).

[0262] Clinical implementation cases of dosage form analysis module

[0263] Case background

[0264] Patient Information

[0265] Name: Mr. Zhang, 60 years old

[0266] Diagnosis: Chronic heart failure (Qi deficiency and blood stasis syndrome)

[0267] Prescription requirements: When a doctor prescribes a Chinese medicine prescription containing herbs such as ginseng, astragalus, salvia miltiorrhiza, and safflower, the doctor needs to choose an appropriate dosage form based on the patient's medication habits (difficulty swallowing), financial situation (limited pension), and efficacy requirements.

[0268] Implementation steps of dosage form analysis module and clinical integration

[0269] Step (a) receiving prescription information

[0270] The dosage form analysis module receives prescription information from the prescription acquisition module, including:

[0271] List of medicines: Ginseng, Astragalus, Salvia miltiorrhiza, Safflower;

[0272] Patient needs: dysphagia (prefer liquid or granules), financial budget (≤30 yuan / course);

[0273] Special requirements: long-term medication is required, and high stability is required (stored at room temperature).

[0274] Step (b) Access the dosage form knowledge base

[0275] The system accesses the built-in knowledge base and retrieves relevant dosage form data:

[0276] Granules: low preparation cost (about 20 yuan / course), fast dissolution (90% in 30 minutes), high stability at room temperature;

[0277] Decoction: a traditional dosage form, but it takes time to boil and is inconvenient to carry (cost 15 yuan per course);

[0278] Capsules: Mask the bitter taste, but the enteric-coated process is expensive (about 35 yuan per course of treatment), which exceeds the patient's budget.

[0279] Step (c) Screening of suitable dosage forms and cost-effectiveness evaluation

[0280] The module automatically excludes capsules (cost exceeds the standard) and selects granules and decoctions.

[0281] Cost-Benefit Analysis:

[0282] Granules: 20 yuan / course, high stability, suitable for long-term use;

[0283] Decoction: 15 yuan / course of treatment, but needs to be decocted daily (high time cost), and the effective ingredients of Salvia miltiorrhiza are easily oxidized.

[0284] Step (d) Visual display of dosage form advantages and disadvantages

[0285] The system displays comparison information through an interactive interface:

[0286] Granules:

[0287] Advantages: portable, high stability, active ingredient content ≥90%;

[0288] Disadvantages: Need to be taken with hot water (twice a day);

[0289] Price: 20 yuan / course (including preparation cost).

[0290] Decoction:

[0291] Advantages: low cost, traditional dosage form;

[0292] Disadvantages: decoction is time-consuming (1 hour per day), and Danshen ingredients are easily degraded (shelf life ≤ 3 days).

[0293] Chart comparison: dissolution curve of granules and degradation trend chart of decoction ingredients.

[0294] Step (e) User Interaction and Selection

[0295] Patients view comparative data through the interface, and the system intelligently recommends granules (which are in line with the budget and highly stable).

[0296] Mr. Zhang chose granules, and the system prompted him to take precautions for brewing (water temperature ≥ 80℃ for full dissolution).

[0297] Clinical implementation cases of the dosage form decision module

[0298] Case background

[0299] Patient Information

[0300] Name: Ms. Li, 45 years old

[0301] Diagnosis: Chronic gastritis (Spleen and stomach deficiency syndrome)

[0302] Prescription requirements: The Chinese medicine prescriptions issued by doctors include medicinal materials such as Codonopsis pilosula, Atractylodes macrocephala, Poria cocos, and Licorice. The appropriate dosage form should be selected based on the patient's medication habits (prefer portable dosage forms), economic status (medium budget) and efficacy requirements.

[0303] Implementation steps of dosage form decision module and clinical integration

[0304] Step (a) receiving prescription and dosage form data

[0305] The dosage form determination module receives prescription information and analysis data from the dosage form analysis module, including:

[0306] Drug ingredients: Codonopsis pilosula, Atractylodes macrocephala, Poria cocos, Licorice root;

[0307] Suitable dosage forms: granules (cost 25 yuan / course), capsules (cost 30 yuan / course), traditional decoctions (cost 20 yuan / course);

[0308] Characteristics of each dosage form: granules are highly portable, capsules mask the bitter taste, and decoctions are low-cost but time-consuming to prepare.

[0309] Step (b) User interaction interface presentation

[0310] The system displays dosage form comparisons through a multimodal interactive interface (charts + animations):

[0311] Granules: fast dissolution (90% in 30 minutes), portable (suitable for office workers);

[0312] Capsules: Enteric coating process ensures gastric protection, but the cost is higher;

[0313] Decoction: It needs to be decocted for 1 hour every day, as the components of Salvia miltiorrhiza are easily oxidized.

[0314] The interface uses three-dimensional dynamic charts to intuitively display the dosage form dissolution curve and cost comparison.

[0315] Step (c) Patient selection and intelligent recommendation

[0316] Patients choose granules based on their own needs (portability), and the system simultaneously reminds them of the precautions: "Granules need to be taken with hot water above 80°C."

[0317] The intelligent recommendation engine combines the patient's historical data (who previously refused capsules due to difficulty in swallowing) to recommend granules first.

[0318] Step (d) Conflict Detection and Alternative Suggestion

[0319] The system detected that Atractylodes macrocephala requires high-temperature drying during the preparation of granules, which may affect the stability of the active ingredient, triggering a warning and recommending an alternative dosage form (capsule).

[0320] The patient insisted on choosing the granules, and the system recorded the decision and prompted to "brew in batches to reduce ingredient loss."

[0321] Step (e) Select Update and Record

[0322] The patient finally confirms the granules, and the system updates the selection results and passes them to the intelligent preparation module.

[0323] Step (f) Data Recording and Traceability

[0324] Record dosage form selection history: granules, selection time (2025-04-17), and reasons (portability is preferred).

[0325] Step (g) Preparation process connection

[0326] The intelligent preparation module starts the automated process according to the granule parameters, including raw material weighing (accuracy ±0.1g), granulation process (temperature control ±2℃) and packaging.

[0327] Clinical implementation cases of the intelligent preparation module

[0328] Case background

[0329] Patient Information

[0330] Name: Mr. Wang, 58 years old

[0331] Diagnosis: Type 2 diabetes (Qi and Yin deficiency syndrome)

[0332] Prescription requirements: The Chinese medicine prescriptions issued by doctors contain medicinal materials such as astragalus, yam, kudzu root, and ophiopogon, which need to be prepared into granules for the convenience of long-term use by patients.

[0333] Implementation steps of intelligent preparation module and clinical integration

[0334] Step (a) receiving instructions

[0335] The intelligent preparation module receives instructions from the dosage form determination module, including:

[0336] Dosage form selection: granules;

[0337] Prescription information: Astragalus (15g), Chinese Yam (10g), Pueraria (12g), Ophiopogon (9g);

[0338] Special requirements: Avoid high temperature from destroying the activity of Pueraria lobata flavonoids.

[0339] Step (b) Raw material preparation and quality inspection

[0340] The system automatically retrieves medicinal materials from the medicinal material warehouse and inspects them using quality inspection equipment:

[0341] Astragalus: HPLC detection of astragaloside IV content ≥ 0.04% (in line with the standards of the Chinese Pharmacopoeia);

[0342] Pueraria root: The flavonoids content in Pueraria root detected by ultraviolet spectrophotometry is ≥12%.

[0343] Unqualified medicinal materials will be automatically returned, and qualified medicinal materials will enter the preparation process.

[0344] Step (c) Preparation formula and process design

[0345] The module generates preparation process parameters based on the characteristics of the granules:

[0346] Proportion: The medicinal material extract is concentrated to a density of 1.2g / ml;

[0347] Mixing: Add 15% of auxiliary material (dextrin);

[0348] Granulation: Fluidized bed granulation temperature ≤ 60°C (to protect kudzu flavonoids).

[0349] Step (d) Dosage Form Preparation and Process Control

[0350] The preparation equipment (crusher, extraction tank, fluidized bed granulator) is started, and sensors monitor key parameters in real time:

[0351] Extraction temperature: 80±2°C (to avoid degradation of kudzu flavonoids);

[0352] Particle moisture content: controlled ≤5% (monitored by infrared moisture meter).

[0353] The system dynamically adjusts the pellet mill inlet air temperature to ensure a pellet forming rate of ≥95%.

[0354] Step (e) Finished product quality inspection

[0355] Finished product testing items include:

[0356] Dissolution: Pueraria lobata flavonoids dissolved ≥85% in 30 minutes;

[0357] Content determination: Astragaloside IV content ≥ 0.03 mg / g;

[0358] Weight difference: within ±5% (in line with pharmacopoeia standards).

[0359] Step (f) Packaging and label printing

[0360] The fully automatic packaging machine completes the packaging (10g per bag), and the label printing content is:

[0361] Patient information: Mr. Wang, ID: 202405001;

[0362] Dosage: 2 times a day, 1 bag each time, take with warm water;

[0363] Batch number and traceability code: 20240417-001 (scan the code to view preparation details).

[0364] Step (g) Recording and tracing

[0365] The system records key data: medicinal material batch (astragalus: 2024-03-15), preparation time (2024-04-17 14:30), and quality inspection results (pass rate 100%).

[0366] Through the traceability code, you can query: Pueraria lobata flavonoids detection value 12.5%, granulation temperature curve, quality inspector information, etc.

Claims

1. An intelligent Chinese medicine prescription processing and preparation system, characterized in that: include: Prescription acquisition module: Through a data interface connected to the medical information system or physician workstation, it receives the Chinese medicine prescription information written by the physician for the patient in real time or on a scheduled basis, including key data such as the patient's basic information, drug name, dosage, usage, and special preparation requirements. It also performs format verification and data integrity checks to ensure the accuracy and validity of the prescription information. If the prescription information is incomplete or contains errors, the system automatically sends a reminder to the physician, requesting a new prescription or correction. The Herbal Material Selection Module integrates a highly user-friendly interactive interface. Based on the list of medicines in the prescription, it intelligently generates a detailed list of options, including herbal material grades (such as ordinary, premium, and selected) and their corresponding prices. It also provides a description of the herbal material grade, including key information such as source, production process, quality assurance, and active ingredient content. Furthermore, a built-in intelligent recommendation engine comprehensively considers the patient's historical choices, financial status, health status, and physician recommendations to recommend the most suitable herbal material grade for the patient. Dosage form analysis module: It has a built-in comprehensive knowledge base for dosage form preparation, covering a variety of common and uncommon Chinese medicine dosage forms such as tablets, capsules, granules, and decoctions. Based on factors such as the drug ingredients in the prescription, patient needs, and preparation process requirements, it automatically analyzes all suitable dosage forms that can be provided for the prescription and lists the advantages and disadvantages of each dosage form, including key factors such as stability, bioavailability, taste, ease of administration, and price. It uses multiple forms such as charts, text descriptions, video animations, and interactive interfaces to intuitively display them. Dosage Form Decision Module: Through a carefully designed user interface, the advantages and disadvantages of each dosage form provided by the dosage form analysis module are clearly presented, allowing patients to freely select the most suitable dosage form based on their needs, personal preferences, and physician recommendations. A built-in intelligent prompt function immediately issues a warning and recommends an alternative dosage form when the selected dosage form is incompatible or potentially conflicting with the drug ingredients in the prescription. At the same time, the patient's dosage form selection history is recorded to provide data support for subsequent intelligent recommendations. Intelligent Preparation Module: Based on the patient's selection in the dosage form determination module, the module automatically enters the preparation process for the corresponding dosage form. This includes steps such as raw material preparation and quality inspection, formulation and process design, dosage form preparation and process control, finished product quality inspection, packaging, and label printing. Advanced automation equipment and intelligent control technology are used to ensure the accuracy and efficiency of the preparation process. Key data and information during the preparation process are also recorded, and a traceability mechanism is established to ensure the traceability of the drug source and preparation process. Intelligent delivery module: Prepares delivery matters according to patient needs, including packaging, boxing, and logistics arrangements, ensuring the safety and timeliness of drug transportation.

2. The intelligent Chinese medicine prescription processing and preparation system according to claim 1, characterized in that: The medicinal material selection module further includes a medicinal material origin selection function, allowing patients to directly select the origin of the medicinal material, or select according to factors such as grade classification, severity of disease, etc., to obtain medicinal materials that better meet personal needs; The specific steps are as follows: Step 1: Construction and integration of medicinal material origin database Database contents: Integrate data from major Chinese medicinal material production areas across the country, including authentic production areas (such as Ningxia wolfberry and Yunnan Panax notoginseng), non-authentic production areas, and their corresponding quality indicators (active ingredient content, pesticide residue test results), price ranges, and supply stability; Correspondence between the grade of medicinal materials (common grade / high quality grade / selected grade) and the place of origin, for example: Selected-grade Astragalus: Shanxi Hunyuan (astragaloside ≥ 0.04%) is preferred; Ordinary grade Astragalus: You can choose the one produced in Longxi, Gansu (astragaloside IV ≥ 0.02%). Dynamic update: By connecting to Chinese medicinal materials trading platforms (such as Yaotong.com), price fluctuations and supply information at the place of origin are updated in real time. Step 2: Design of the Origin Selection Interactive Interface Function entry: Added the "Origin Filter" option in the interactive interface of the medicinal material selection module, supporting the following modes: Direct selection mode: Patients manually select a specific place of origin (e.g., "Yunnan Wenshan Panax notoginseng"); Intelligent recommendation mode: The system automatically matches the origin according to the severity of the disease: Emergency / severe illness: Priority is given to authentic production areas (high content of active ingredients); Chronic diseases / mild illnesses: We recommend non-authentic production areas with better cost-effectiveness. Visual display: Use map annotation to show the distribution of medicinal material production areas (such as highlighting authentic production areas); Provide origin comparison cards to show origin characteristics (such as climate, planting history), active ingredient data and price differences. Step 3: Intelligent recommendation based on origin and grade Recommended logic: Economic priority: If the patient has a limited budget, the system will prioritize recommending lower-priced origins of the same grade (e.g., ordinary-grade astragalus should be produced in Gansu); Prioritize efficacy: If the patient's disease is serious (such as adjuvant treatment for cancer), the system recommends high-end medicinal materials from authentic production areas (such as selected ginseng produced in Changbai Mountain, Jilin). Conflict prompt: When the patient chooses high-end products but has insufficient budget, the system automatically prompts "origin downgrade suggestion" (such as switching from selected-grade Shanxi Astragalus to high-quality Inner Mongolia Astragalus). Step 4: Dynamic screening of disease severity Disease classification matching: Emergency / severe cases: Mandatory use of medicinal materials from authentic production areas to ensure the highest active ingredient content (e.g., total saponins of Panax notoginseng ≥ 8%); Chronic diseases: Open up non-authentic production area options to allow patients to adjust according to their budget. Sample Application: If the patient is diagnosed with acute angina pectoris (severe), the system will automatically select Panax notoginseng produced in Wenshan, Yunnan (total saponins ≥ 9%) and block other production areas; The patient suffers from chronic insomnia (mild), and the system recommends Hubei Poria cocos (Poria cocos polysaccharide ≥ 25%) with high cost-effectiveness. Step 5: User interaction and selection confirmation Multi-condition screening: Patients can select "origin + grade + disease priority" at the same time through the interface, for example: Select "Ningxia wolfberry (authentic production area) + premium grade + chronic disease" and the system will generate matching results (polysaccharide content ≥ 3.5%, mid-range price); Select "Xinjiang wolfberry (non-authentic) + ordinary grade + mild symptoms", and the system will display comparative data showing a 20% reduction in cost but a 15% reduction in active ingredients. Final confirmation: After the patient confirms, the system will bind the origin information with the grade of the medicinal materials and pass it to the dosage form analysis module for subsequent dosage form cost accounting (for example, authentic medicinal materials may increase the cost of granule preparation). Step 6: Data Recording and Intelligent Learning Historical records: Stores the origin, grade, and reasons for each patient's selection (such as "designated authentic production area" or "accepted system downgrade recommendation"); Machine learning optimization: Optimizes the recommendation algorithm based on historical data, for example: It was found that patients in a certain region preferred local medicinal materials (for example, users in Guangdong often chose Huazhou Tangerine Peel), and the recommendation priority was adjusted.

3. The intelligent Chinese medicine prescription processing and preparation system according to claim 1, characterized in that: The intelligent preparation module further includes an intelligent decoction function that can automatically select the appropriate decoction utensils, control the amount of water added, the heat and time, and handle the decoction methods of special medicinal materials, such as decocting first, adding later, and wrapping decoction, etc., to ensure the accuracy and efficiency of the decoction process. At the same time, it provides decoction skill guidance and precautions to help users better master the decoction method. Step 1: Construction of decoction knowledge base and rule base Knowledge Base Contents: Decoction Utensil Library: This stores characteristic data of various decoction utensils (such as ceramic pots, stainless steel pots, and smart decoction machines), including material thermal conductivity, capacity, applicable scenarios (such as home / hospital), and cleaning difficulty. Water volume calculation rules: Based on the water absorption of the medicinal materials and the concentration requirements of the medicinal solution (e.g., antipyretics require less decoction, tonics require longer decoction), the water addition formula is automatically generated (e.g., medicinal material weight × water absorption coefficient + target medicinal solution volume); Heat and time parameters: Associate the properties of medicinal materials (e.g., antipyretics require high heat and fast decoction, while minerals require low heat and long decoction), and preset the decoction time and temperature curve for different medicinal materials; Special decoction rules: record the operating standards for special methods such as decocting first, adding later, wrapping and decocting, and melting (e.g., decocting aconite for 30 minutes first and adding mint for 5 minutes later); Step 2: Prescription analysis and decoction parameter generation Extracting medicinal material properties: Identify medicinal materials that require special treatment from the prescription (such as gypsum decocted first and Amomum villosum added later) and mark their priority; Intelligent parameter matching: Device selection: Automatically recommend devices based on drug volume (e.g., large-capacity smart decoction machine for >500g) and patient needs (e.g., portability); Calculation of water addition: For example, if the prescription contains Poria cocos (water absorption coefficient 1.5), the system calculates the amount of water to be added as the weight of the medicinal material × 1.5 + the target liquid volume of 200ml; Heat and time: For antipyretic herbs (e.g., ephedra), use high heat (100°C) and simmer quickly (10 minutes); for tonic herbs (e.g., Rehmannia glutinosa), use low heat (80°C) and simmer slowly (40 minutes); Step 3: Decoction utensils and water addition control Appliance linkage control: the system automatically starts the equipment and sets parameters (such as temperature and water volume); Dynamic water replenishment: The water volume is monitored in real time during the decoction process. When it is lower than the threshold (such as 50ml remaining), the water volume is automatically replenished. Step 4: Dynamically adjust the heat and time Heat control: High-heat stage (antipyretic drugs): quickly raise the temperature to 100°C and shorten the decoction time to retain volatile components; Simmering stage (tonic medicine): maintain 80℃ and prolong the boiling time to improve the dissolution of active ingredients; Countdown management: The interface displays the remaining decoction time and reminds the user to implement the process at special steps (such as 5 minutes before adding the last medicinal material). Step 5: Automated processing of special decoction methods Decoction first / add herbs later: The system automatically divides the decoction process, for example: First, decoct the herbs (such as gypsum) separately for 30 minutes; Add the remaining herbs in the last 5 minutes (later); Use the compartment function of the smart medicine decoction machine to automatically dispense medicine in batches or prompt the user to dispense medicine in batches; Wrapping and decoction operation: For sticky herbs (such as plantain seeds), gauze wrapping or filter netting is automatically used to avoid turbidity of the medicinal solution; Step 6: Instructions on decoction techniques and precautions Real-time interactive guidance: Display the decoction step animation through the interface (such as "the first decoction of herbs has been decocted for 25 minutes, and 5 minutes remain"); Risk Warning: When it is detected that the decoction time of toxic medicinal materials (such as aconite) is insufficient, the device will be forced to lock and issue a warning; Advise patients to avoid using iron utensils to decoct acidic herbs (such as Schisandra chinensis); Step 7: Data Recording and Machine Learning Optimization Traceability of the decoction process: Recording decoction parameters (temperature curve, water volume changes, and time of drug administration) and correlating them with patient efficacy feedback (such as efficacy scores); Intelligent optimization: Analyzing historical data through machine learning and automatically adjusting decoction rules (for example, if it is found that patients in a certain region prefer to shorten the decoction time, the parameters will be optimized to suit their habits).

4. The intelligent Chinese medicine prescription processing and preparation system according to claim 1, characterized in that: The system also includes intelligent medicine sorting equipment, which realizes automatic sorting and accurate distribution of medicines through the coordinated operation of the loading unit, placement unit, medicine taking unit and unloading unit, further improving the automation and accuracy of the system; The intelligent medicine sorting equipment (sorting medicinal materials) realizes automated sorting and distribution through the following collaborative units. The specific steps are as follows: Step 1: Device architecture and unit function definition The intelligent drug sorting equipment consists of the following core units, which are coordinated and operated by IoT technologies (such as PLC control and industrial bus): Function: Receive the medicinal materials to be sorted from the medicinal material warehouse or preparation module, and transport them to the sorting area through a conveyor belt or vibrating feeder; Technical support: Dynamic weighing sensors and visual recognition systems are used to detect the weight and integrity of medicinal materials in real time; Place the cell: Function: Dynamically allocate medicine storage grids according to medicinal material type, batch or order requirements, and support multi-level classified storage; Technical support: The medicine storage grid is equipped with RFID tags to record information such as the source and expiration date of the medicinal materials, and synchronize with the system database in real time; Medication collection unit: Function: Accurately grab the target medicinal materials through the robotic arm or AGV car; Technical support: Combining force control sensors and visual positioning technology to ensure grasping accuracy ≤±0.1mm; Unloading unit: Function: Pack the sorted medicinal materials according to the order, automatically attach logistics labels and check the weight (the error exceeds ±5% and triggers an alarm); Technical support: Dynamic weighing compensation technology is used to ensure that the packaging error is ≤0.5g; Step 2: Automated control of sorting process Identification and classification of medicinal materials: The visual recognition system scans the morphology, color, and barcode of the medicinal material and matches it with the medicinal material characteristics in the database (such as the spindle shape of Panax notoginseng and the fibrous root of ginseng); Combined with weight sorting technology, medicinal materials are classified according to preset rules (such as grading Gastrodia elata by gram weight); Path planning and sorting execution: After the system analyzes the order requirements, it dynamically plans the robot arm's motion trajectory and gives priority to expedited orders; The status of medicinal materials is monitored in real time during the sorting process. If an abnormality is detected (such as insect-infested medicinal materials), the rejection mechanism is triggered and manual intervention is notified; Step 3: Quality Control and Error Handling Quality Inspection: Embed multiple quality checks in the sorting process: Component detection: Rapidly analyze the active ingredient content of medicinal materials (such as notoginseng saponins ≥ 8%) through near-infrared spectrometry; Impurity removal: Use color sorters to automatically separate foreign matter or spoiled medicinal materials Bug fixes: If the sorting result does not match the order (such as weight deviation or mix-up of medicinal materials), the system automatically starts the re-sorting process and records the error type for machine learning optimization; Step 4: Parallel processing of multiple orders and priority management Parallel sorting strategy: Partitioned storage grids are used to physically isolate regular orders from expedited orders to avoid cross contamination. During peak hours, AGV cluster collaboration is enabled to increase throughput to 200 pieces per hour; Intelligent scheduling: Dynamically adjust the sorting order based on the characteristics of the medicinal materials (e.g., hygroscopic Poria cocos needs to be sorted first) and the urgency of the order; Step 5: Data tracing and intelligent optimization Full process traceability: Record sorting operation logs (such as grabbing time, robot arm number, and medicinal material batch), associate them with traceability codes, and support reverse query of production sources. Machine learning optimization: Analyze historical sorting data (such as common error types and efficiency bottlenecks) to optimize sorting algorithms and storage grid layout.

5. According to claim 1, it is characterized in that The specific implementation steps of the medicinal material selection module are as follows: (a) The medicinal material selection module receives the Chinese medicine prescription information transmitted by the prescription acquisition module, which includes a list of medicines in the prescription and relevant information of the patient; (b) Based on the list of drugs in the prescription, the herbal medicine selection module accesses the system's herbal medicine database, which stores detailed information on various herbal medicines, including different grades (such as ordinary grade, premium grade, and selected grade) and their corresponding prices, sources, production processes, quality assurance, and active ingredient content; (c) The medicinal material selection module intelligently generates a list of options including the grades of the medicinal materials and their detailed information, and presents the list to the user in a user-friendly manner, allowing the user to view and compare the characteristics and prices of medicinal materials of different grades; (d) The system's built-in intelligent recommendation engine recommends one or more most suitable medicinal material grades based on the patient's historical choices, financial status, health status, and physician's advice. This recommendation process may involve complex algorithms and data analysis to ensure the accuracy and personalization of the recommendations; (e) Users can view the intelligently recommended medicinal material grades on the system interface and select them according to their needs and preferences. If the user wishes to select medicinal materials of a different grade, the system also allows the user to freely change the selection; (f) Once the user makes a selection, the herbal material selection module will record this selection and pass it on to the subsequent preparation module for preparation of the preparation based on the selected herbal material. This selection will also be recorded in the historical database to provide data support for subsequent intelligent recommendations.

6. According to claim 1, it is characterized in that The specific implementation steps of the dosage form analysis module are as follows: (a) The dosage form analysis module receives the TCM prescription information transmitted by the prescription acquisition module. This information includes key data such as the patient's basic information, the list of prescribed drugs, the dosage, usage, special preparation requirements of each drug, and the patient's financial status or willingness to pay. This information together forms the basis for selecting the dosage form; (b) Based on the list of drugs in the prescription, the dosage form analysis module accesses the system's built-in knowledge base of traditional Chinese medicine dosage forms. This knowledge base not only stores detailed information on various traditional Chinese medicine dosage forms, such as tablets, capsules, granules, decoctions, pills, powders, and other common and uncommon dosage forms, but also records in detail the preparation process, stability, bioavailability, taste, ease of administration, and other characteristics of each dosage form, as well as the cost structure and approximate price range of each dosage form; (c) The dosage form analysis module comprehensively considers the drug ingredients in the prescription, patient needs (such as age, gender, disease type, medication habits, etc.), preparation process requirements, special preparation requirements, and the patient's financial status or willingness to pay, and automatically analyzes and screens all suitable dosage forms that can be provided for the prescription, while also evaluating the cost-effectiveness of each dosage form; (d) For each selected suitable dosage form, the dosage form analysis module further analyzes its advantages and disadvantages, covering key factors such as stability, bioavailability, taste, ease of administration, and price. This information is presented to users intuitively and comprehensively through various forms such as charts, text descriptions, video animations, and interactive interfaces, ensuring that users can clearly understand the characteristics and pricing information of each dosage form; (e) Users (e.g., patients or physicians) can view detailed information on the advantages, disadvantages, and pricing of various dosage forms through the system interface, allowing them to select the most appropriate dosage form based on their needs, personal preferences, physician recommendations, and financial affordability. The system allows users to freely switch between and view comparative analysis results of different dosage forms, enabling them to make more informed and cost-effective choices.

7. According to claim 1, it is characterized in that The specific implementation steps of the dosage form determination module are as follows: (a) The dosage form determination module receives prescription information and analysis data on the advantages and disadvantages of each dosage form from the dosage form analysis module. This data includes the drug ingredients in the prescription, patient needs, preparation process requirements, and key factors such as stability, bioavailability, taste, and ease of administration of each suitable dosage form; (b) The dosage form decision module presents this information to patients in an intuitive and understandable manner through a carefully designed user interface. The interface clearly lists the advantages and disadvantages of each dosage form and may use various forms such as charts, text descriptions, video animations, and interactive elements to enable patients to fully understand and compare the characteristics of different dosage forms; (c) Patients can freely select the most suitable dosage form on the interface based on their needs, personal preferences, and physician recommendations. The system allows patients to review and compare the advantages and disadvantages of different dosage forms to make more informed choices; (d) When a patient selects a dosage form, the intelligent prompt function built into the dosage form decision module immediately checks whether the selected dosage form is incompatible or potentially conflicting with the drug ingredients in the prescription. If a conflict exists, the system immediately issues a warning and recommends an alternative dosage form to the patient, providing a detailed explanation and justification. (e) If the patient accepts the alternative dosage form recommended by the system, the dosage form decision module updates the selection result; if the patient insists on the original choice, the system records the patient's decision and continues the subsequent process; (f) The dosage form decision module records the patient's dosage form selection history, including the dosage form selected each time, the time of selection, and the reason for selection (if provided). This data provides important support for subsequent intelligent recommendations and personalized services; (g) Finally, the dosage form decision module transmits the patient's dosage form selection result to the intelligent preparation module so that the corresponding preparation procedure can be entered according to the selected dosage form.

8. According to claim 1, it is characterized in that The specific implementation steps of the intelligent preparation module are as follows: (a) Receiving instructions: The intelligent preparation module receives instructions from the dosage form determination module, which contains key information such as the dosage form selected by the patient, the list of drugs in the prescription and their dosage; (b) Raw material preparation and quality inspection: Based on the prescription information, the intelligent preparation module automatically retrieves the required medicinal materials from the storage system and performs quality inspection on the medicinal materials using built-in quality inspection equipment to ensure that the medicinal materials meet the preparation requirements; (c) Preparation formula and process design: Based on the drug ingredients in the prescription, the dosage form selected by the patient, and the preparation process requirements, the intelligent preparation module automatically designs the preparation formula and preparation process, including parameters such as the ratio of each medicinal material, mixing sequence, preparation temperature, and time; (d) Dosage Form Preparation and Process Control: Based on the designed formulation and process, the intelligent preparation module activates the corresponding preparation equipment, such as a grinder, mixer, tablet press, and capsule filler, to prepare the dosage form. During the preparation process, the module uses sensors to monitor the preparation environment (e.g., temperature, humidity) and preparation status (e.g., mixing uniformity, tablet hardness, etc.) in real time, and automatically adjusts the preparation parameters based on the monitoring results to ensure the stability and accuracy of the preparation process. (e) Finished product quality inspection: After preparation, the intelligent preparation module conducts quality inspection on the finished product, including appearance inspection, weight difference, content determination, etc., to ensure that the finished product meets the quality standards; (f) Packaging and label printing: Finished products that pass inspection will be sent to the packaging line for packaging. The intelligent preparation module will automatically print and paste labels containing key information such as patient information, drug name, usage and dosage; (g) Recording and tracing: The intelligent preparation module records key data and information in the preparation process, such as the source of medicinal materials, preparation time, preparation personnel, quality inspection results, etc., and establishes a traceability mechanism so that the source and preparation process of the medicine can be traced when necessary.

9. According to claim 1, it is characterized in that The specific implementation steps of the intelligent distribution module are as follows: (a) Receiving delivery instructions: The intelligent delivery module first receives delivery instructions from other modules in the system (such as the intelligent preparation module). The instructions contain key data such as patient delivery information, drug information, and delivery requirements; (b) Packaging and boxing: Based on the delivery instructions received, the intelligent delivery module automatically starts the packaging equipment, packs the prepared medicines according to the specified packaging requirements, and places them in a dedicated delivery box. During the packaging and boxing process, the module uses built-in sensors and control systems to monitor key parameters such as the integrity of packaging materials, the placement of drugs, and the sealing of delivery boxes in real time to ensure the safety and integrity of drugs during transportation; (c) Logistics Arrangement: After packaging and boxing are completed, the intelligent delivery module automatically selects the appropriate logistics company and generates a detailed logistics delivery plan based on factors such as the patient's delivery address, delivery time requirements, and the characteristics of the medication. The module communicates with the logistics company in real time through the built-in logistics management system to track logistics status and ensure that the medication is delivered to the patient on time and accurately. (d) Delivery tracking and feedback: During the delivery process, the intelligent delivery module monitors the logistics status in real time through the built-in tracking system, including information such as delivery location and estimated arrival time, and provides delivery progress inquiry services to patients through the system interface or through SMS and email. At the same time, the module also receives delivery feedback from the logistics company, including information such as delivery success, delivery failure, or the need for secondary delivery, and takes appropriate measures based on the feedback results; (e) Recording and Traceability: The intelligent delivery module records key data and information during the delivery process, such as delivery instructions, packaging time, packing information, logistics company selection, and logistics status tracking records, and establishes a traceability mechanism. When necessary, these records can be used to trace the delivery process and status of drugs, ensuring traceability and transparency of the delivery process.