WO2024000863A1 - 基于人工智能的在线购药方法及装置、存储介质 - Google Patents

基于人工智能的在线购药方法及装置、存储介质 Download PDF

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Publication number
WO2024000863A1
WO2024000863A1 PCT/CN2022/121565 CN2022121565W WO2024000863A1 WO 2024000863 A1 WO2024000863 A1 WO 2024000863A1 CN 2022121565 W CN2022121565 W CN 2022121565W WO 2024000863 A1 WO2024000863 A1 WO 2024000863A1
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consultation
questions
drug
purchased
asked
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PCT/CN2022/121565
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English (en)
French (fr)
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高歌
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康键信息技术（深圳）有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0613—Third-party assisted
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G06F16/332—Query formulation
    • G06F16/3329—Natural language query formulation or dialogue systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G06F16/3331—Query processing
    • G06F16/334—Query execution
    • G06F16/3344—Query execution using natural language analysis
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients

Definitions

  • This application relates to the fields of artificial intelligence and digital medical technology, and in particular to an artificial intelligence-based online drug purchasing method and device, storage media, and computer equipment.
  • the current method of online drug purchase and consultation is mainly through manual online consultation by doctors.
  • the user answers multiple questions in turn, including chief complaint, history of current illness, etc.
  • the doctor then issues a drug order based on the conversation content, and the user performs subsequent drug purchase operations.
  • This model requires users to answer relevant questions required for online drug purchase multiple times, which results in low drug purchase efficiency and high labor costs.
  • this application provides an artificial intelligence-based online drug purchasing method and device, storage medium, and computer equipment, which can solve the problems of low drug purchasing efficiency and high labor cost in online drug purchasing.
  • an artificial intelligence-based online drug purchasing method including:
  • an online drug purchasing device based on artificial intelligence includes:
  • the information acquisition module is used to obtain the pre-purchased drug information of drug purchasers
  • a form generation module is used to determine the questions to be asked corresponding to the pre-purchased drug information, and fill the questions to be asked into the preset consultation template to form a consultation form corresponding to the pre-purchased drug information;
  • An information receiving module configured to display the consultation form and receive the consultation answers input by the drug purchasing user on the consultation form
  • the information correction module is used to verify whether the drug purchasing user meets the purchase conditions for pre-purchased drugs based on the answers to the consultation.
  • a storage medium on which a computer program is stored.
  • the program is executed by a processor, the above-mentioned artificial intelligence-based online drug purchasing method is implemented.
  • a computer device including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor.
  • the processor executes the program, the above artificial intelligence-based The smart way to buy medicine online.
  • this application provides an artificial intelligence-based online drug purchasing method and device, storage medium, and computer equipment.
  • the user's pre-purchased drug information is obtained, and then the user's pre-purchased drug information is determined based on the relevant information of the pre-purchased drug.
  • the questions that need to be answered to purchase the above-mentioned medicines are then provided to the user in a consultation form, and the users answer them uniformly.
  • the answers submitted by the user it is verified whether the user is qualified to purchase the pre-purchased medicines.
  • the embodiments of this application can reduce labor costs and improve drug purchase efficiency.
  • Figure 1 shows a schematic flow chart of an artificial intelligence-based online drug purchasing method provided by an embodiment of the present application
  • Figure 2 shows a schematic structural diagram of an artificial intelligence-based online drug purchasing device provided by an embodiment of the present application
  • Figure 3 shows a schematic diagram of a consultation form provided by an embodiment of the present application.
  • an online drug purchasing method based on artificial intelligence is provided. As shown in Figure 1, the method includes:
  • Step 101 Obtain the pre-purchased drug information of the drug purchasing user.
  • the above-mentioned embodiments of the present application can be applied to user terminals, such as smart phones, tablet computers, desktop computers, etc.
  • user terminals such as smart phones, tablet computers, desktop computers, etc.
  • users can place online drug orders through smartphone terminals.
  • Specific ordering operations can be done through web links, WeChat public accounts, mobile applications and other ways that can be used to place orders.
  • the embodiment of this application takes a mobile application as an example for explanation.
  • the user opens the mobile application, clicks to select the medicine he wants to buy and places an order directly, or adds it to the shopping cart and places an order.
  • Drug qualifications are verified to determine whether the drug purchaser is qualified to purchase the pre-ordered drugs. If the drug purchaser is qualified to purchase the drug, the order will take effect after the user pays. Otherwise, the user will be refused to purchase the drug.
  • the corresponding pre-purchased drug information is obtained based on the pre-purchased drug ID placed by the user.
  • the pre-purchased drug information can specifically include the name of the drug, indications, usage and dosage, adverse reactions, contraindications and precautions for this product, etc. etc., for this purpose, all pre-purchased drug information of drug purchasers will be obtained.
  • Step 102 Determine the questions to be asked corresponding to the pre-purchased drug information, and fill the questions to be asked into the preset consultation template to form a consultation form corresponding to the pre-purchased drug information;
  • the corresponding questions to be asked are determined based on the pre-purchased drug information. Specifically, taking the determination of questions to be asked based on the "adaptation symptoms" in the drug information obtained in step 101 as an example, you can first extract the keywords in the aforementioned adaptation symptoms, and then structure the questions to be asked based on the keywords. If If the symptoms of the ordered medicine include "fever, headache, and cough", the final question to be asked can be: "Have you had symptoms of fever, headache, and cough recently?” etc. Similarly, the information obtained based on the above In the pre-purchase drug information, the contraindication symptoms of this product are structured into questions to be asked.
  • the platform obtains that the drug purchased by the user is Lianhua Qingwen Granules, it will obtain the following drug information based on the Lianhua Qingwen Granules drug instructions, including:
  • influenza which is caused by heat poison attacking the lungs.
  • Symptoms include: fever or high fever, chills, muscle aches, nasal congestion and runny nose, cough, headache, dry and sore throat, red tongue, yellow or yellow coating. Tired of waiting.
  • the determined questions to be diagnosed can be: "Have you ever had any symptoms of fever or high fever, cough, headache, dry throat and sore throat recently?"
  • step 102 the questions to be asked corresponding to the pre-purchased drug information are determined, including:
  • Step 102-1 identify whether the pre-purchased drug information contains prescription drug information, if not, generate a drug purchase order based on the pre-purchased drug;
  • Step 102-2 if included, obtain the health information of the drug purchaser, and determine the questions to be asked based on the prescription drug information and the health information.
  • the pre-purchased drugs contain prescription drug information. If not, there is no need to start the consultation process, and a drug purchase order is directly generated based on the user's pre-purchased drugs. Then, the user confirmation page is opened to wait for the user's confirmation and Payment. Among them, if the user clicks Confirm, the drug purchase process will be completed after payment. If the user clicks Cancel or times out, the drug purchase process will be closed.
  • the consultation process needs to be started.
  • the health information of the aforementioned drug purchasing user is first obtained.
  • the aforementioned health information may include the user's age, gender, current medical history, past history, contraindications, allergies, etc., and if the user is a female, it may also include pregnancy status, breastfeeding status, etc. All personal information related to drug purchase, and then determine the questions to be asked based on the health information and prescription drug information obtained above.
  • the platform recognizes that the drug pre-purchased by the user is Huoxiang Zhengqi Water and detects that the drug is an over-the-counter drug, it will not start the consultation process and directly generate the corresponding drug purchase order.
  • the aforementioned drug purchase order includes the name of the drug, the order quantity, the unit price of the drug, the total price of the drug and the purchase method.
  • the platform determines the final price based on the unit price and quantity of the pre-purchased drugs and displays it in the order. Then it opens the user confirmation page and prompts the user to confirm the relevant information in the drug purchase order and make payment.
  • the aforementioned purchase methods can be self-pickup at offline pharmacies or online mailing. Take online mailing as an example.
  • the platform After the user confirms the pre-purchased drug information, the platform prompts the user to fill in the mailing address, recipient name and recipient contact number. After all the information is filled in, the payment process will be entered. After the user completes the payment, the The drug purchase process is completed. If the platform detects that the user clicks to cancel the purchase or the payment time times out after prompting the user to confirm the drug purchase order, or while waiting for the user to pay, the platform will automatically close the drug purchase process.
  • the timeout time is preset and can be any length of time, such as 20 minutes, 30 minutes, or 1 hour, and is not limited here. When a payment timeout is detected, a timeout reminder is set to remind the user to pay as soon as possible to complete the order.
  • the platform recognizes that the drug pre-purchased by the user is nifedipine sustained-release tablets and detects that the drug is a prescription drug, the consultation process will be started.
  • the drug information of nifedipine sustained-release tablets is obtained according to the method of step 101, including: adapting symptoms to various types of hypertension and angina pectoris, and the precautions are: "1. When stopping taking calcium antagonists, the dosage should be gradually reduced , Do not stop taking the medicine without doctor's instruction. 2. Use with caution in patients with hypotension. 3. Use with caution in patients with severe aortic stenosis, liver and kidney dysfunction.”, Pregnant and lactating women are contraindicated and other information.
  • the identified questions to be asked can be: “Do you suffer from hypotension?" and “Do you suffer from severe aortic stenosis, liver and kidney dysfunction” and so on. If the health information submitted by the user is obtained and shows that the user is female, the questions to be asked also include: “Is she pregnant or lactating” and other questions.
  • the questions to be asked are filled into the preset consultation template to form a consultation form corresponding to the pre-purchased drug information, including:
  • Step 102-3 Obtain the preset basic consultation questions, and perform deduplication processing on the questions to be asked and the preset basic consultation questions to obtain the consultation form questions;
  • Step 102-4 Fill the questions in the consultation form into the preset consultation template to form the consultation form.
  • the preset basic consultation questions are first obtained.
  • the aforementioned basic consultation questions may include: "patient's name”, “patient's gender”, “patient's age”, “contraindications”, “allergies” “, “Lactation issues”, “Liver and kidney function”, “First diagnosis disease information” and “Prescription drug information”, etc., and then unify the preset basic consultation questions with the questions to be asked in step 102-2 Convert it into a recognizable data format and bring it to the data reorganization platform for data reintegration. Then remove duplicate question data through dynamic configuration, generate form data that does not contain duplicate question data, and convert the aforementioned form data into consultation form questions.
  • the questions of the consultation form are filled into the preset consultation template to form the consultation form, including:
  • corresponding answer options are determined according to the questions on the consultation form determined in step 102-3, and the aforementioned answer options include customized options and/or at least one optional option.
  • the aforementioned custom options are filled in by users themselves according to the consultation questions.
  • the aforementioned optional options can include: “Yes”, “No”, “None of the above”, “Others” and other basic options, as well as key options based on the pre-purchased drug information. Answer options determined by words.
  • the aforementioned custom options and the aforementioned optional options can be freely combined.
  • the optional options can support single selection or multiple selection. If multiple selection is possible, mark “Multiple selection" after the corresponding question to be asked. ”, as shown in Figure 3, is used to prompt the user.
  • the pre-purchased drugs of the drug purchaser are drugs used to treat stomach problems
  • the corresponding answer options can be composed of custom options and The optional options are: “duodenal ulcer”, “stress ulcer”, “gastric ulcer”, “reflux esophagitis”, “gastrinoma” and “other____________”, if the user When filling in the answers, if it is found that there is no matching content among the above available options, the user can fill in his or her own diagnosis results in the horizontal line after "Others" to verify the drug purchase conditions.
  • the corresponding answer options can only consist of optional options, such as “diabetes”, “renal insufficiency”, “uremia”, “second or third degree ovary syndrome” "Ventricular block”, “renal failure” and “none of the above”.
  • optional options such as “diabetes”, “renal insufficiency”, “uremia”, “second or third degree ovary syndrome” "Ventricular block”, “renal failure” and “none of the above”.
  • “multiple choices” are marked after the diagnostic questions, prompting the user to make multiple choices.
  • Step 103 display the consultation form, and receive the consultation answers input by the drug purchasing user on the consultation form;
  • the consultation form generated in step 102 is displayed to the user at once in the form of a page.
  • the background receives the answer information, thereby obtaining the questions filled in by the user.
  • the answer content facilitates later verification and diagnosis of whether the drug purchaser meets the purchase conditions.
  • Step 104 Verify whether the drug purchasing user meets the purchase conditions for pre-purchased drugs based on the answers to the consultation.
  • the platform After obtaining the answers to the questions selected by the user, the platform begins to verify whether the drug purchaser meets the purchase conditions for pre-purchased drugs to ensure that the user does not mistakenly purchase unsuitable drugs and thereby avoid risks.
  • the user's pre-purchased drug information is first obtained, and then the questions to be answered that the user needs to answer to purchase the above-mentioned drugs are determined based on the relevant information of the pre-purchased drugs, and then the questions to be asked are formed into questions.
  • the diagnosis form is provided to the user, who answers the questions uniformly, and finally verifies whether the user is qualified to purchase pre-purchased drugs based on the answers submitted by the user.
  • step 104 includes:
  • Step 104-1 Perform semantic analysis on the custom answers corresponding to the custom options in the consultation answers, and verify whether the semantic analysis results match the preset answers corresponding to the pre-purchased drug information; and/or verify the Whether the selection results of the optional options in the consultation answers match the preset options corresponding to the pre-purchased drug information;
  • Step 104-2 Determine whether the drug purchasing user meets the purchase conditions for pre-purchased drugs based on the verification results.
  • the platform obtains the customized answers filled in by the user.
  • the pre-purchased drugs of the drug purchaser are drugs used to treat gastric diseases.
  • the determined form question is "What is your first diagnosis at the offline hospital?"
  • the corresponding answer options are: “Duodenal ulcer”, “Stress ulcer”, “Gastric ulcer”, “Reflux esophagitis”, “Gastrinoma” and “Other____________”, the answer filled in by the user It is “other functional gastrointestinal diseases ", and the default answers for this drug are “stomach disease”, “gastric ulcer”, and “gastritis”.
  • the "gastrointestinal disease” filled in by the user is similar to “stomach disease”, so The answer options match the preset answers, so it is judged that the drug purchaser meets the purchase conditions for the drug.
  • determining the questions to be asked based on the prescription drug information and the health information includes: if the pre-purchased drugs include multiple prescription drugs, then according to All prescription drug information and the health information, determine the questions to be asked, and label the prescription drugs corresponding to each of the questions to be asked;
  • step 102-3 specifically includes: deduplicating the same questions among the questions to be asked and the preset basic consultation questions, and adding the annotation tags corresponding to the removed questions to be asked to the reserved Among the same questions to be asked, the questions on the consultation form are obtained.
  • the user can purchase a variety of medicines when placing an order, that is, he can order prescription medicines and over-the-counter medicines at the same time.
  • Prescription medicines can also include multiple types. This operation can facilitate the user to purchase all the medicines he needs at one time, which is simple and Convenient.
  • the platform identifies the pre-purchased drug information ordered by the user. If the search contains multiple prescription drugs, it will determine the questions to be asked based on all prescription drug information and health information, that is, the "drug name, applicable symptoms, usage and dosage, Adverse reactions, contraindications and precautions for this product, etc.”, as well as the user's age, gender, current history, past history, contraindications, allergies and other health information to determine multiple of the questions to be asked, and then in each of the questions to be asked Write the name of the corresponding prescription drug after the question.
  • prescription drug information and health information that is, the "drug name, applicable symptoms, usage and dosage, Adverse reactions, contraindications and precautions for this product, etc.”, as well as the user's age, gender, current history, past history, contraindications, allergies and other health information to determine multiple of the questions to be asked, and then in each of the questions to be asked Write the name of the corresponding prescription drug after the question.
  • the aforementioned basic consultation questions may include: "patient's name”, “patient's gender”, “patient's age”, “contraindications”, “allergies”, “lactation period” “Questions”, “Liver and Kidney Function”, “First Diagnosis Disease Information” and “Prescription Drug Information”, etc., and then uniformly convert the preset basic consultation questions and to-be-examined questions into identifiable data formats and bring them to the data reorganization platform Reintegrate the data, then remove duplicate question data through dynamic configuration, and add the annotation labels corresponding to the removed question data to the retained same question data to be diagnosed, forming a form with labels and non-duplicate questions. The data is then converted to generate consultation form questions.
  • step 104 optionally, after step 104, it also includes:
  • Step 105 If the drug purchasing user does not meet the purchase conditions for all pre-purchased drugs, obtain the verification failure answers that do not match the preset answers and/or the pre-purchased drugs in the consultation answers;
  • Step 106 Based on the label corresponding to the failed verification answer, determine the drugs to be deleted that the drug purchaser is not qualified to purchase;
  • Step 107 After deleting the drug to be deleted from the pre-purchased drugs, generate a drug purchase order based on the remaining drugs.
  • steps 104-1 and 104-2 are followed to verify whether the user meets the purchase conditions for pre-ordered drugs. If it is found that the user does not meet the purchase conditions for a certain drug, a mismatched failure answer will be obtained.
  • the above-mentioned drugs to be deleted are deleted from the drug list ordered by the user, and a drug purchase order is generated for user confirmation and payment.
  • a drug purchase order is generated for user confirmation and payment.
  • the embodiment of the present application provides a device for an online drug purchasing method based on artificial intelligence.
  • the device includes:
  • the information acquisition module is used to obtain the pre-purchased drug information of drug purchasers
  • a form generation module is used to determine the questions to be asked corresponding to the pre-purchased drug information, and fill the questions to be asked into the preset consultation template to form a consultation form corresponding to the pre-purchased drug information;
  • An information receiving module configured to display the consultation form and receive the consultation answers input by the drug purchasing user on the consultation form
  • the information correction module is used to verify whether the drug purchasing user meets the purchase conditions for pre-purchased drugs based on the answers to the consultation.
  • the form generation module is also used to:
  • the form generation module is also used to:
  • the form generation module is also used to:
  • the questions in the consultation form and their corresponding answer options are filled into the preset consultation template to form the consultation form.
  • the information correction module is also used to:
  • the form generation module is also used to:
  • the pre-purchased drugs include multiple prescription drugs, determine the questions to be asked based on all prescription drug information and the health information, and label the prescription drugs corresponding to each of the questions to be asked;
  • a question form which specifically includes:
  • the information correction module is also used to:
  • a drug purchase order is generated based on the remaining drugs.
  • the embodiment of the present application also provides a computer-readable storage medium.
  • the computer-readable storage medium may be non-volatile or volatile, and the computer-readable storage medium may be stored thereon.
  • the technical solution of this application can be embodied in the form of a software product.
  • the software product can be stored in a non-volatile storage medium (can be a CD-ROM, U disk, mobile hard disk, etc.), including several
  • the instructions are used to cause a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the method described in each implementation scenario of this application.
  • embodiments of the present application also provide a computer device, which can be a personal computer, a server, a network device, etc.
  • the computer device includes a storage medium and a processor; the storage medium is used to store a computer program; and the processor is used to execute the computer program to implement the above-mentioned artificial intelligence-based online drug purchasing method as shown in Figure 1.
  • the computer device may also include a user interface, a network interface, a camera, a radio frequency (Radio Frequency, RF) circuit, a sensor, an audio circuit, a WI-FI module, etc.
  • the user interface may include a display screen (Display), an input unit such as a keyboard (Keyboard), etc.
  • the optional user interface may also include a USB interface, a card reader interface, etc.
  • Optional network interfaces may include standard wired interfaces, wireless interfaces (such as Bluetooth interfaces, WI-FI interfaces), etc.
  • a computer device does not constitute a limitation on the computer device, and may include more or less components, or combine certain components, or arrange different components.
  • the storage medium may also include an operating system and a network communication module.
  • An operating system is a program that manages and saves the hardware and software resources of a computer device and supports the operation of information processing programs and other software and/or programs.
  • the network communication module is used to implement communication between components within the storage medium, as well as communication with other hardware and software in the physical device.
  • this application can use software and the necessary general hardware platform to achieve the acquisition of pre-purchased drug information of drug purchasers through hardware, and then determine the pre-purchase. Questions to be asked corresponding to the drug information, and the questions to be asked are filled into the preset consultation template to form a consultation form corresponding to the pre-purchased drug information, and then the consultation form is displayed, and the consultation form is received. The medicine purchaser enters the consultation answer on the consultation form, and finally, based on the consultation answer, it is verified whether the medicine purchaser meets the purchase conditions for the pre-purchased medicine.
  • This application solves the problems of low drug purchasing efficiency and high labor costs in online drug purchasing.
  • the accompanying drawing is only a schematic diagram of a preferred implementation scenario, and the modules or processes in the accompanying drawing are not necessarily necessary for implementing the present application.
  • the modules in the devices in the implementation scenario can be distributed in the devices in the implementation scenario according to the description of the implementation scenario, or can be correspondingly changed and located in one or more devices different from the implementation scenario.
  • the modules of the above implementation scenarios can be combined into one module or further split into multiple sub-modules.

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Abstract

一种基于人工智能的在线购药方法及装置、存储介质、计算机设备，涉及人工智能和数字医疗技术领域，方法包括：获取购药用户的预购药品信息(101)；确定预购药品信息对应的待问诊问题，并将待问诊问题填充至预设问诊模板中，形成预购药品信息对应的问诊表单(102)；显示问诊表单，并接收购药用户在问诊表单上输入的问诊答案(103)；根据问诊答案，验证购药用户是否符合对预购药品的购买条件(104)。基于人工智能的在线购药方法及装置、存储介质、计算机设备解决了在线购药中购药效率低，人力成本高的问题。

Description

基于人工智能的在线购药方法及装置、存储介质
本申请要求于2022年06月27日提交中国专利局、申请号为202210734083.1，发明名称为“基于人工智能的在线购药方法及装置、存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及人工智能和数字医疗技术领域，尤其是涉及到一种基于人工智能的在线购药方法及装置、存储介质、计算机设备。
背景技术
随着互联网医疗行业的蓬勃发展，互联网医疗的出现打破了传统的医疗就医方式，为用户提供了一种网络购药的渠道，用户采取网络购药的方式能够方便看病拿药，因此网络购药越来越得到人们的推崇。
当前网络购药问诊的方式主要是通过医生人工在线问诊，由用户依次回答包括主诉、现病史等多项问题，然后医生根据对话内容开具药单，再由用户进行后续的购药操作。发明人意识到，这种模式需要用户分多次对网络购药所需的相关问题进行回答，购药效率低，人力成本高。
发明内容
有鉴于此，本申请提供了一种基于人工智能的在线购药方法及装置、存储介质、计算机设备，能够解决在线购药中的购药效率低，人力成本高的问题。
根据本申请的一个方面，提供了一种基于人工智能的在线购药方法，包括：
获取购药用户的预购药品信息；
确定所述预购药品信息对应的待问诊问题，并将所述待问诊问填充至预设问诊模板中，形成所述预购药品信息对应的问诊表单；
显示所述问诊表单，并接收所述购药用户在所述问诊表单上输入的问诊答案；
根据所述问诊答案，验证所述购药用户是否符合对预购药品的购买条件。
根据本申请的另一方面，提供了一种基于人工智能的在线购药装置，所述装置包括：
信息获取模块，用于获取购药用户的预购药品信息；
表单生成模块，用于确定所述预购药品信息对应的待问诊问题，并将所述待问诊问题填充至预设问诊模板中，形成所述预购药品信息对应的问诊表单；
信息接收模块，用于显示所述问诊表单，并接收所述购药用户在所述问诊表单上输入的问诊答案；
信息校正模块，用于根据所述问诊答案，验证所述购药用户是否符合对预购药品的购买条件。
依据本申请又一个方面，提供了一种存储介质，其上存储有计算机程序，所述程序被处理器执行时实现上述基于人工智能的在线购药方法。
依据本申请再一个方面，提供了一种计算机设备，包括存储介质、处理器及存储在存储介质上并可在处理器上运行的计算机程序，所述处理器执行所述程序时实现上述基于人工智能的在线购药方法。
借由上述技术方案，本申请提供的一种基于人工智能的在线购药方法及装置、存储介质、计算机设备，首先获取购药用户的预购药品信息，然后根据预购药品的相关信息确定用户若要购买上述药品所需要回答的待问诊问题，接着将上述待问诊问题形成问诊表单提供给用户，由用户统一进行作答，最后根据用户提交的答案验证用户是否符合购买预购药品的资格。本申请实施例相比于现有技术中通过医生人工问诊来实现在线购药的方式，能够减少人力成本，提高购药效率。
上述说明仅是本申请技术方案的概述，为了能够更清楚了解本申请的技术手段，而可依照说明书的内容予以实施，并且为了让本申请的上述和其它目的、特征和优点能够更明显易懂，以下特举本申请的具体实施方式。
附图说明
此处所说明的附图用来提供对本申请的进一步理解，构成本申请的一部分，本申请的示意性实施例及其说明用于解释本申请，并不构成对本申请的不当限定。在附图中：
图1示出了本申请实施例提供的一种基于人工智能的在线购药方法的流程示意图；
图2示出了本申请实施例提供的一种基于人工智能的在线购药装置的结构示意图；
图3示出了本申请实施例提供的一种问诊表单示意图。
具体实施方式
下文中将参考附图并结合实施例来详细说明本申请。需要说明的是，在不冲突的情况下，本申请中的实施例及实施例中的特征可以相互组合。
在本实施例中提供了一种基于人工智能的在线购药方法，如图1所示，该方法包括：
步骤101，获取购药用户的预购药品信息。
本申请上述实施例可以应用于用户终端中，例如智能手机、平板电脑、台式电脑等。以智能手机为例，用户可以通过智能手机终端进行在线购药下单，具体的下单操作可以通过网页链接、微信公众号、手机应用程序等其他可以用于下单的方式。本申请实施例以手机应用程序为例进行解释说明，首先用户打开手机应用程序，点击选择想要购买的药品直接下单，或添加到购物车后下单，购药平台对购药用户的购药资格进行验证，以判断购药用户是否对下单的预购药品具有购买资格，若购药用户具有购买资格则在用户支付后订单生效，否则拒绝用户购买药品。在资格校验过程中，具体的，根据用户下单的预购药品ID获取对应的预购药品信息，预购药品信息具体可以包括药品名称、适应症状、用法用量、不良反应、本品禁忌和注意事项等等，为此将购药用户的预购药品信息全部获取。
步骤102，确定所述预购药品信息对应的待问诊问题，并将所述待问诊问题填充至预设问诊模板中，形成所述预购药品信息对应的问诊表单；
在上述实施例中，获取到预购药品信息之后，根据预购药品信息确定对应的待问诊问题。具体的，以根据步骤101中获取到的药品信息中“适应症状”确定待问诊问题为例，可以首先提取前述适应症状中的关键词，然后针对关键词进行待问诊问题的架构，若下单药品中适应症状中含有“发烧、头疼以及咳嗽”等字样，则最终确定待问诊问题可以为：“您最近是否有发烧、头疼以及咳嗽的症状”等，同样的，根据前述获取到的预购药品信息中本品禁忌症状进行架构待问诊问题，若下单药品中本品禁忌症状含有“高血压者禁用”和“肾脏功能不全患者禁用”等字样，可以得到的待问诊问题为：“是否有以下药物禁忌症”、“是否患有高血压”或者“是否患有肾脏功能不全的疾病”等问题，只要能够满足包含针对购买药品需要用户回答的问题即可，在此不做限定。
具体的，若平台获取到用户购买的药品为连花清瘟颗粒，则根据连花清瘟颗粒药品说明书获得如下药品信息，包括：
适应症状为用于治疗流行性感冒属热毒袭肺证，症见：发热或高热，恶寒，肌肉酸痛，鼻塞流涕，咳嗽，头痛，咽干咽痛，舌偏红，苔黄或黄腻等。根据前述确定待问诊问题的方法，确定的待确诊问题可以是：“请问您最近是否有发热或高热，咳嗽，头痛，咽干咽痛的症状”。
最后将上述待问诊问题填充至预设的问诊模板中，形成整体的问诊表单，如图3所示，然后提供给用户以便用户填选答案。这样，将用户在线购买药品需要回答的相关问题全部集中于一张表单之中，由用户一次性填写完毕后提交即可进行购药操作，提高了问诊效率，节约了人力成本。
在本申请实施例中，可选地，步骤102中确定所述预购药品信息对应的待问诊问题，包括：
步骤102-1，识别所述预购药品信息中是否包含处方药品信息，若不包含，则依据所述预购药品，生成购药订单；
步骤102-2，若包含，则获取所述购药用户的健康信息，根据所述处方药品信息及所述健康信息，确定待问诊问题。
在上述实施例中，识别所述预购药品中是否包含处方药品信息，如果不包含，则无需开启问诊流程，直接根据用户的预购药品生成购药订单，接着，打开用户 确认页等待用户确认并付款。其中，若用户点击确认，付款后即完成购药流程，若用户点击取消或超时，则关闭购药流程。
如果用户的预购药品中包含处方药，则需要开启问诊流程。具体的，首先获取前述购药用户的健康信息，前述健康信息可以包括用户年龄、性别、现病史、既往史、禁忌症、过敏症等等，若用户为女性还包括妊娠情况、哺乳情况等等一切与购药相关的个人信息，然后根据前述获取的健康信息以及处方药信息确定待问诊问题。
具体的，若平台识别到用户预购的药品为藿香正气水，同时检测出该药品属于非处方药，则不开启问诊流程，直接生成对应的购药订单。其中，前述购药订单包括药品名称、订购数量、药品单价、药品总价和购买方式。首先平台根据预购药品的单价及数量确定最终价格显示于订单内，然后打开用户确认页，提示用户确认购药订单中的相关信息并付款。前述购买方式可以为线下药房自提或者网络邮寄等方式。以网络邮寄为例，在用户确认预购药品信息之后，平台提示用户填写邮寄地址、收件人名称和收件人联系电话，待全部信息填写完毕后则进入付款环节，待用户完成付款后即此购药流程完毕。如果平台在提示用户确认购药订单后，或者等待用户付款的过程中，检测到用户点击取消购买或者付款时间超时，则自动关闭购药流程。其中，超时的时间为预设的，可以为20分钟、30分钟或者1个小时等任意时长，在此不作限定。在检测到付款超时的同时设置超时提醒，用于提醒用户尽快付款完成订单。
具体的，若平台识别到用户预购的药品为硝苯地平缓释片，同时检测出该药品属于处方药，则开启问诊流程。具体的，根据步骤101的方法获取硝苯地平缓释片的药品信息，具体包括：适应症状为各种类型的高血压及心绞痛，注意事项为“1、中止服用钙拮抗剂时应逐渐减量，没有医生指示，不要中止服药。2、低血压患者慎用。3、严重主动脉瓣狭窄、肝肾功能不全患者慎用。”，孕妇及哺乳期妇女禁用等等信息。为此，确定的待问诊问题可以为：“是否患有低血压”和“是否患有重主动脉瓣狭窄、肝肾功能不全疾病”等等。若获取到用户提交的健康信息显示为女性，则待问诊问题还包括：“是否正处于孕期或者哺乳期”等等问题。
在本申请实施例中，可选地，步骤102中所述将所述待问诊问题填充至预设问诊模板中，形成所述预购药品信息对应的问诊表单，包括：
步骤102-3，获取预设基本问诊问题，并对所述待问诊问题及所述预设基本问诊问题进行去重处理，得到问诊表单问题；
步骤102-4，将所述问诊表单问题填充至预设问诊模板中，形成所述问诊表单。
在上述实施例中，首先获取预设的基本问诊问题，前述基本问诊问题可以包括：“就诊人姓名”、“就诊人性别”、“就诊人年龄”、“禁忌症”、“过敏症”、“哺乳期问题”、“肝肾功能”、“初诊疾病信息”和“处方药品信息”等等，然后将预设的基本问诊问题与步骤102-2中确定的待问诊问题统一转换为可识别的数据格式带入数据重组平台中进行数据重新整合，然后通过动态配置去掉重复的问题数据，生成不包含重复问题数据的表单数据，并将前述表单数据转换生成问诊表单问题。
最后将上述表单问题配置于预设的问诊模板中，从而形成问诊表单，如图3所示。
在本申请实施例中，可选地，步骤步骤102-4中所述将所述问诊表单问题填充至预设问诊模板中，形成所述问诊表单，包括：
102-4-1，获取每个所述问诊表单问题各自对应的答案选项，其中，任一所述问诊表单问题对应的答案选项包括自定义选项和/或至少一个可选选项；
102-4-2，将所述问诊表单问题及其对应的答案选项填充至预设问诊模板中，形成所述问诊表单。
在上述实施例中，根据步骤102-3中确定的问诊表单问题确定对应的答案选项，前述答案选项包括自定义选项和/或至少一个可选选项。其中，前述自定义选项为用户根据问诊问题自行输入文字填写，前述可选选项可以包括：“是”、“否、“以上均无”、“其他”等基本选项，以及根据预购药品信息关键词确定的答案选项。前述自定义选项和前述可选选项可以自由进行组合，同时可选选项可以支持单选或者多选，如果可以进行多选则在对应的待问诊问题后标注“多选”，如图3所示，用于提示用户。
具体的，以购药用户的预购药品为用于治疗胃病的药品为例，若确定的表单问题为“请问您在线下医院就诊初诊诊断是什么”，则对应的答案选项可以由自定义选项和可选选项组成，为：“十二肠溃疡”、“应激性溃疡”、“胃溃疡”、“反流性食管炎”、“胃泌素瘤”以及“其他____________”,如果用户在填选答案时发现以上可选选项中没有符合的内容，则用户可以在“其他”后的横线中自行填写自己的诊断结果，用于验证购药条件。若确定的表单问题为“是否有以下药物禁忌症”，对应的答案选项可以仅由可选选项组成，为“糖尿病”、“肾功能不全”、“尿毒症”、“二度或三度房室传导阻滞”、“肾功能衰竭”和“以上均无”，同时在问诊问题后标注“多选”，提示用户可以进行多项选择。
步骤103，显示所述问诊表单，并接收所述购药用户在所述问诊表单上输入的问诊答案；
在上述实施例中，将步骤102中生成的问诊表单通过页面的形式一次性展示给用户，由用户填选各问诊问题对应的答案之后，后台接收答案信息，从而获取用户填选的问题答案内容，便于后期校验和诊断购药用户是否符合购买条件。
步骤104，根据所述问诊答案，验证所述购药用户是否符合对预购药品的购买条件。
在上述实施例中，平台获取用户填选的问诊答案后，开始验证购药用户是否符合对预购药品的购买条件，以保证用户不会误购不适合的药物，从而规避危险。
通过应用本实施例的技术方案，首先获取购药用户的预购药品信息，然后根据预购药品的相关信息确定用户若要购买上述药品所需要回答的待问诊问题，接着上述待问诊问题形成问诊表单提供给用户，由用户统一进行作答，最后根据用户提交的答案验证用户是否符合购买预购药品的资格。本申请实施例相比于现有技术中通过医生人工问诊来实现在线购药的方式，能够减少人力成本，提高购药效率。
在本申请实施例中，可选地，步骤104包括：
步骤104-1，对所述问诊答案中自定义选项对应的自定义答案进行语义分析，并验证语义分析结果是否与所述预购药品信息对应的预设答案匹配；和/或，验证所述问诊答案中可选选项的选择结果是否与所述预购药品信息对应的预设选项匹配；
步骤104-2，根据验证结果判断所述购药用户是否符合对预购药品的购买条件。
在上述实施例中，平台获取用户填写的自定义答案，以购药用户的预购药品为用于治疗胃病的药品为例，确定的表单问题为“请问您在线下医院就诊初诊诊断是什么”，对应的答案选项为：“十二肠溃疡”、“应激性溃疡”、“胃溃疡”、“反流性食管炎”、“胃泌素瘤”以及“其他____________”,用户填写的答案为“其他 功能性胃肠病”，该药品的预设答案为“胃病”、“胃溃疡”、“胃炎”,通过语义分析，用户所填的“胃肠病”与“胃病”类似，故此答案选项与预设答案相匹配,所以判断购药用户符合对该药品的购买条件。
在本申请实施例中，可选地，步骤102-2中根据所述处方药品信息及所述健康信息，确定待问诊问题，包括：若所述预购药品中包含多个处方药品，则根据全部处方药品信息以及所述健康信息，确定所述待问诊问题，并对每个所述待问诊问题对应的处方药品进行标注；
相应地，步骤102-3，具体包括：对所述待问诊问题以及所述预设基本问诊问题中相同的问题进行去重，并将去掉的待问诊问题对应的标注标签添加到保留的相同待问诊问题中，得到所述问诊表单问题。
在上述实施例中，用户下单时可以购买多种药品，即可以同时下单处方药和非处方药，其中，处方药也可以包含多种，这样操作可以方便用户一次性购买所需的全部药品，简单而且便捷。
首先，平台识别用户下单的预购药品信息，若检索出包含多个处方药品，则根据所有处方药品信息以及健康信息确定待问诊问题，即全部处方药的“药品名称、适应症状、用法用量、不良反应、本品禁忌和注意事项等”，以及用户年龄、性别、现病史、既往史、禁忌症、过敏症等等健康信息确定多个所述待问诊问题，然后在每个待问诊问题后标注对应的处方药品名称。
然后，获取预设的基本问诊问题，前述基本问诊问题可以包括：“就诊人姓名”、“就诊人性别”、“就诊人年龄”、“禁忌症”、“过敏症”、“哺乳期问题”、“肝肾功能”、“初诊疾病信息”和“处方药品信息”等等，然后将预设的基本问诊问题与待问诊问题统一转换为可识别的数据格式带入数据重组平台中进行数据重新整合，然后通过动态配置去掉重复的问题数据，并将去掉的问题数据所对应的标注标签添加到保留的相同待问诊问题数据中，形成带有标签且含有不重复问题的表单数据，进而转换生成问诊表单问题。
在本申请实施例中，可选地，步骤104之后，还包括：
步骤105，若所述购药用户不符合全部预购药品的购买条件，则获取所述问诊答案中与所述预设答案和/或所述预购药品不匹配的验证失败答案；
步骤106，依据所述验证失败答案对应的标注标签，确定所述购药用户不具备购买资格的待删除药品；
步骤107，将所述待删除药品从所述预购药品中删除后，依据剩余药品，生成购药订单。
在上述实施例中，按照步骤步骤104-1、104-2验证用户是否符合预购药品的购买条件，若发现不符合其中某种药品的购药条件，将获取不匹配的失败答案。
然后获取前述失败答案对应的待问诊问题，确定此待问诊问题对应的标签，通过标签确定对应的处方药，进而确定用户不符合哪种药品的购买条件，然后将此种药品列为待删除药品。
最后将上述待删除药品从用户下单的药品单列中删除，生成购药订单，用于用户确认并付款。这样，即使用户不符合下单的预购药品中的某个药品的购买条件，用户还可以继续购买其他药品而无需重新下单，提高了购药效率。
进一步的，作为图1方法的具体实现，本申请实施例提供了一种基于人工智能的在线购药方法的装置，如图2所示，该装置包括：
信息获取模块，用于获取购药用户的预购药品信息；
表单生成模块，用于确定所述预购药品信息对应的待问诊问题，并将所述待问诊问题填充至预设问诊模板中，形成所述预购药品信息对应的问诊表单；
信息接收模块，用于显示所述问诊表单，并接收所述购药用户在所述问诊表单上输入的问诊答案；
信息校正模块，用于根据所述问诊答案，验证所述购药用户是否符合对预购药品的购买条件。
可选地，所述表单生成模块，还用于：
识别所述预购药品信息中是否包含处方药品信息，若不包含，则依据所述预购药品，生成购药订单；
若包含，则获取所述购药用户的健康信息，根据所述处方药品信息及所述健康信息，确定待问诊问题。
可选地，所述表单生成模块，还用于：
获取预设基本问诊问题，并对所述待问诊问题及所述预设基本问诊问题进行去重处理，得到问诊表单问题；
将所述问诊表单问题填充至预设问诊模板中，形成所述问诊表单。
可选地，所述表单生成模块，还用于：
获取每个所述问诊表单问题各自对应的答案选项，其中，任一所述问诊表单问题对应的答案选项包括自定义选项和/或至少一个可选选项；
将所述问诊表单问题及其对应的答案选项填充至预设问诊模板中，形成所述问诊表单。
可选地，所述信息校正模块，还用于：
对所述问诊答案中自定义选项对应的自定义答案进行语义分析，并验证语义分析结果是否与所述预购药品信息对应的预设答案匹配；和/或，
验证所述问诊答案中可选选项的选择结果是否与所述预购药品信息对应的预设选项匹配；
根据验证结果判断所述购药用户是否符合对预购药品的购买条件。
可选地，所述表单生成模块，还用于：
若所述预购药品中包含多个处方药品，则根据全部处方药品信息以及所述健康信息，确定所述待问诊问题，并对每个所述待问诊问题对应的处方药品进行标注；
相应地，所述对所述待问诊问题及所述预设基本问诊问题进行去重处理，得到问诊表单问题，具体包括：
对所述待问诊问题以及所述预设基本问诊问题中相同的问题进行去重，并将去掉的待问诊问题对应的标注标签添加到保留的相同待问诊问题中，得到所述问诊表单问题。
可选地，所述信息校正模块，还用于：
若所述购药用户不符合全部预购药品的购买条件，则获取所述问诊答案中与所述预设答案和/或所述预购药品不匹配的验证失败答案；
依据所述验证失败答案对应的标注标签，确定所述购药用户不具备购买资格的待删除药品；
将所述待删除药品从所述预购药品中删除后，依据剩余药品，生成购药订单。
需要说明的是，本申请实施例提供的一种基于人工智能的在线购药方法的装置所涉及各功能单元的其他相应描述，可以参考图1方法中的对应描述，在此不再赘述。
基于上述如图1所示方法，相应的，本申请实施例还提供了一种计算机可读存储介质，所述计算机可读存储介质可以是非易失性，也可以是易失性，其上存储有计算机程序，该计算机程序被处理器执行时实现上述如图1所示的基于人工智能的在线购药方法。
基于这样的理解，本申请的技术方案可以以软件产品的形式体现出来，该软件产品可以存储在一个非易失性存储介质(可以是CD-ROM，U盘，移动硬盘等)中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请各个实施场景所述的方法。
基于上述如图1所示的方法，以及图2所示的虚拟装置实施例，为了实现上述目的，本申请实施例还提供了一种计算机设备，具体可以为个人计算机、服务器、网络设备等，该计算机设备包括存储介质和处理器；存储介质，用于存储计 算机程序；处理器，用于执行计算机程序以实现上述如图1所示的基于人工智能的在线购药方法。
可选地，该计算机设备还可以包括用户接口、网络接口、摄像头、射频(Radio Frequency，RF)电路，传感器、音频电路、WI-FI模块等等。用户接口可以包括显示屏(Display)、输入单元比如键盘(Keyboard)等，可选用户接口还可以包括USB接口、读卡器接口等。网络接口可选的可以包括标准的有线接口、无线接口(如蓝牙接口、WI-FI接口)等。
本领域技术人员可以理解，本实施例提供的一种计算机设备结构并不构成对该计算机设备的限定，可以包括更多或更少的部件，或者组合某些部件，或者不同的部件布置。
存储介质中还可以包括操作系统、网络通信模块。操作系统是管理和保存计算机设备硬件和软件资源的程序，支持信息处理程序以及其它软件和/或程序的运行。网络通信模块用于实现存储介质内部各组件之间的通信，以及与该实体设备中其它硬件和软件之间通信。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到本申请可以借助软件加必要的通用硬件平台的方式来实现通过硬件实现获取购药用户的预购药品信息，然后确定所述预购药品信息对应的待问诊问题，并将所述待问诊问填充至预设问诊模板中，形成所述预购药品信息对应的问诊表单，接着显示所述问诊表单，并接收所述购药用户在所述问诊表单上输入的问诊答案，最后根据所述问诊答案，验证所述购药用户是否符合对预购药品的购买条件。本申请解决了在线购药中购药效率低，人力成本高的问题。
本领域技术人员可以理解附图只是一个优选实施场景的示意图，附图中的模块或流程并不一定是实施本申请所必须的。本领域技术人员可以理解实施场景中的装置中的模块可以按照实施场景描述进行分布于实施场景的装置中，也可以进行相应变化位于不同于本实施场景的一个或多个装置中。上述实施场景的模块可以合并为一个模块，也可以进一步拆分成多个子模块。
上述本申请序号仅仅为了描述，不代表实施场景的优劣。以上公开的仅为本申请的几个具体实施场景，但是，本申请并非局限于此，任何本领域的技术人员能思之的变化都应落入本申请的保护范围。

Claims (20)

  1. 一种基于人工智能的在线购药方法，其中，所述方法包括：
    获取购药用户的预购药品信息；
    确定所述预购药品信息对应的待问诊问题，并将所述待问诊问填充至预设问诊模板中，形成所述预购药品信息对应的问诊表单；
    显示所述问诊表单，并接收所述购药用户在所述问诊表单上输入的问诊答案；
    根据所述问诊答案，验证所述购药用户是否符合对预购药品的购买条件。
  2. 根据权利要求1所述的方法，其中，所述确定所述预购药品信息对应的待问诊问题，包括：
    识别所述预购药品信息中是否包含处方药品信息，若不包含，则依据所述预购药品，生成购药订单；
    若包含，则获取所述购药用户的健康信息，根据所述处方药品信息及所述健康信息，确定待问诊问题。
  3. 根据权利要求2所述的方法，其中，所述将所述待问诊问题填充至预设问诊模板中，形成所述预购药品信息对应的问诊表单，包括：
    获取预设基本问诊问题，并对所述待问诊问题及所述预设基本问诊问题进行去重处理，得到问诊表单问题；
    将所述问诊表单问题填充至预设问诊模板中，形成所述问诊表单。
  4. 根据权利要求3所述的方法，其中，所述将所述问诊表单问题填充至预设问诊模板中，形成所述问诊表单，包括：
    获取每个所述问诊表单问题各自对应的答案选项，其中，任一所述问诊表单问题对应的答案选项包括自定义选项和/或至少一个可选选项；
    将所述问诊表单问题及其对应的答案选项填充至预设问诊模板中，形成所述问诊表单。
  5. 根据权利要求4所述的方法，其中，所述根据所述问诊答案，验证所述购药用户是否符合对预购药品的购买条件，包括：
    对所述问诊答案中自定义选项对应的自定义答案进行语义分析，并验证语义分析结果是否与所述预购药品信息对应的预设答案匹配；和/或，
    验证所述问诊答案中可选选项的选择结果是否与所述预购药品信息对应的预设选项匹配；
    根据验证结果判断所述购药用户是否符合对预购药品的购买条件。
  6. 根据权利要求5所述的方法，其中，所述根据所述处方药品信息及所述健康信息，确定待问诊问题，具体包括：
    若所述预购药品中包含多个处方药品，则根据全部处方药品信息以及所述健康信息，确定所述待问诊问题，并对每个所述待问诊问题对应的处方药品进行标注；
    相应地，所述对所述待问诊问题及所述预设基本问诊问题进行去重处理，得到问诊表单问题，具体包括：
    对所述待问诊问题以及所述预设基本问诊问题中相同的问题进行去重，并将去掉的待问诊问题对应的标注标签添加到保留的相同待问诊问题中，得到所述问诊表单问题。
  7. 根据权利要求6所述的方法，其中，所述根据所述问诊答案，验证所述购药用户是否符合对预购药品的购买条件之后，包括：
    若所述购药用户不符合全部预购药品的购买条件，则获取所述问诊答案中与所述预设答案和/或所述预购药品不匹配的验证失败答案；
    依据所述验证失败答案对应的标注标签，确定所述购药用户不具备购买资格的待删除药品；
    将所述待删除药品从所述预购药品中删除后，依据剩余药品，生成购药订单。
  8. 一种基于人工智能的在线购药装置，其中，所述装置包括：
    信息获取模块，用于获取购药用户的预购药品信息；
    表单生成模块，用于确定所述预购药品信息对应的待问诊问题，并将所述待问诊问题填充至预设问诊模板中，形成所述预购药品信息对应的问诊表单；
    信息接收模块，用于显示所述问诊表单，并接收所述购药用户在所述问诊表单上输入的问诊答案；
    信息校正模块，用于根据所述问诊答案，验证所述购药用户是否符合对预购药品的购买条件。
  9. 一种计算机可读存储介质，其上存储有计算机程序，其中，所述计算机程序被处理器执行时实现以下步骤：
    获取购药用户的预购药品信息；
    确定所述预购药品信息对应的待问诊问题，并将所述待问诊问填充至预设问诊模板中，形成所述预购药品信息对应的问诊表单；
    显示所述问诊表单，并接收所述购药用户在所述问诊表单上输入的问诊答案；
    根据所述问诊答案，验证所述购药用户是否符合对预购药品的购买条件。
  10. 根据权利要求9所述的计算机可读存储介质，其中，所述确定所述预购药品信息对应的待问诊问题，包括：
    识别所述预购药品信息中是否包含处方药品信息，若不包含，则依据所述预购药品，生成购药订单；
    若包含，则获取所述购药用户的健康信息，根据所述处方药品信息及所述健康信息，确定待问诊问题。
  11. 根据权利要求10所述的计算机可读存储介质，其中，所述将所述待问诊问题填充至预设问诊模板中，形成所述预购药品信息对应的问诊表单，包括：
    获取预设基本问诊问题，并对所述待问诊问题及所述预设基本问诊问题进行去重处理，得到问诊表单问题；
    将所述问诊表单问题填充至预设问诊模板中，形成所述问诊表单。
  12. 根据权利要求11所述的计算机可读存储介质，其中，所述将所述问诊表单问题填充至预设问诊模板中，形成所述问诊表单，包括：
    获取每个所述问诊表单问题各自对应的答案选项，其中，任一所述问诊表单问题对应的答案选项包括自定义选项和/或至少一个可选选项；
    将所述问诊表单问题及其对应的答案选项填充至预设问诊模板中，形成所述问诊表单。
  13. 根据权利要求12所述的计算机可读存储介质，其中，所述根据所述问诊答案，验证所述购药用户是否符合对预购药品的购买条件，包括：
    对所述问诊答案中自定义选项对应的自定义答案进行语义分析，并验证语义分析结果是否与所述预购药品信息对应的预设答案匹配；和/或，
    验证所述问诊答案中可选选项的选择结果是否与所述预购药品信息对应的预设选项匹配；
    根据验证结果判断所述购药用户是否符合对预购药品的购买条件。
  14. 根据权利要求13所述的计算机可读存储介质，其中，所述根据所述处方药品信息及所述健康信息，确定待问诊问题，具体包括：
    若所述预购药品中包含多个处方药品，则根据全部处方药品信息以及所述健康信息，确定所述待问诊问题，并对每个所述待问诊问题对应的处方药品进行标注；
    相应地，所述对所述待问诊问题及所述预设基本问诊问题进行去重处理，得到问诊表单问题，具体包括：
    对所述待问诊问题以及所述预设基本问诊问题中相同的问题进行去重，并将去掉的待问诊问题对应的标注标签添加到保留的相同待问诊问题中，得到所述问诊表单问题。
  15. 根据权利要求14所述的计算机可读存储介质，其中，所述根据所述问诊答案，验证所述购药用户是否符合对预购药品的购买条件之后，包括：
    若所述购药用户不符合全部预购药品的购买条件，则获取所述问诊答案中与所述预设答案和/或所述预购药品不匹配的验证失败答案；
    依据所述验证失败答案对应的标注标签，确定所述购药用户不具备购买资格的待删除药品；
    将所述待删除药品从所述预购药品中删除后，依据剩余药品，生成购药订单。
  16. 一种计算机设备，包括存储介质、处理器及存储在存储介质上并可在处理器上运行的计算机程序，其中，所述处理器执行所述计算机程序时实现以下步骤：
    获取购药用户的预购药品信息；
    确定所述预购药品信息对应的待问诊问题，并将所述待问诊问填充至预设问诊模板中，形成所述预购药品信息对应的问诊表单；
    显示所述问诊表单，并接收所述购药用户在所述问诊表单上输入的问诊答案；
    根据所述问诊答案，验证所述购药用户是否符合对预购药品的购买条件。
  17. 根据权利要求16所述的计算机设备，其中，所述确定所述预购药品信息对应的待问诊问题，包括：
    识别所述预购药品信息中是否包含处方药品信息，若不包含，则依据所述预购药品，生成购药订单；
    若包含，则获取所述购药用户的健康信息，根据所述处方药品信息及所述健康信息，确定待问诊问题。
  18. 根据权利要求17所述的计算机设备，其中，所述将所述待问诊问题填充至预设问诊模板中，形成所述预购药品信息对应的问诊表单，包括：
    获取预设基本问诊问题，并对所述待问诊问题及所述预设基本问诊问题进行去重处理，得到问诊表单问题；
    将所述问诊表单问题填充至预设问诊模板中，形成所述问诊表单。
  19. 根据权利要求18所述的计算机设备，其中，所述将所述问诊表单问题填充至预设问诊模板中，形成所述问诊表单，包括：
    获取每个所述问诊表单问题各自对应的答案选项，其中，任一所述问诊表单问题对应的答案选项包括自定义选项和/或至少一个可选选项；
    将所述问诊表单问题及其对应的答案选项填充至预设问诊模板中，形成所述问诊表单。
  20. 根据权利要求12所述的计算机设备，其中，所述根据所述问诊答案，验证所述购药用户是否符合对预购药品的购买条件，包括：
    对所述问诊答案中自定义选项对应的自定义答案进行语义分析，并验证语义分析结果是否与所述预购药品信息对应的预设答案匹配；和/或，
    验证所述问诊答案中可选选项的选择结果是否与所述预购药品信息对应的预设选项匹配；
    根据验证结果判断所述购药用户是否符合对预购药品的购买条件。
PCT/CN2022/121565 2022-06-27 2022-09-27 基于人工智能的在线购药方法及装置、存储介质 WO2024000863A1 (zh)

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Publication number Priority date Publication date Assignee Title
CN115099895A (zh) * 2022-06-27 2022-09-23 康键信息技术（深圳）有限公司 基于人工智能的在线购药方法及装置、存储介质
CN115936804A (zh) * 2022-11-29 2023-04-07 昭阳健康(广州)科技有限公司 基于人工智能的在线购药方法、系统、设备及存储介质

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003114932A (ja) * 2001-10-09 2003-04-18 Issei Denki Sekkei Jimusho:Kk 医薬品商品の販売方法およびそのシステム
CN107330266A (zh) * 2017-06-28 2017-11-07 江苏叶雨智能科技有限公司 远程诊疗通信方法
CN112185505A (zh) * 2020-10-29 2021-01-05 济南市第三人民医院 一种药房远程服务系统
CN113706243A (zh) * 2021-08-26 2021-11-26 贵阳朗玛信息技术股份有限公司 一种线上购药的系统
CN113744836A (zh) * 2021-09-08 2021-12-03 平安科技（深圳）有限公司 基于自然语言处理的处方生成方法、装置、设备及介质
CN114119163A (zh) * 2021-11-30 2022-03-01 北京三快在线科技有限公司 一种执行药品购买业务的方法及装置
CN114283919A (zh) * 2021-12-27 2022-04-05 朗森特科技有限公司 一种基于电子处方的自动售药柜及其系统
CN115099895A (zh) * 2022-06-27 2022-09-23 康键信息技术（深圳）有限公司 基于人工智能的在线购药方法及装置、存储介质

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003114932A (ja) * 2001-10-09 2003-04-18 Issei Denki Sekkei Jimusho:Kk 医薬品商品の販売方法およびそのシステム
CN107330266A (zh) * 2017-06-28 2017-11-07 江苏叶雨智能科技有限公司 远程诊疗通信方法
CN112185505A (zh) * 2020-10-29 2021-01-05 济南市第三人民医院 一种药房远程服务系统
CN113706243A (zh) * 2021-08-26 2021-11-26 贵阳朗玛信息技术股份有限公司 一种线上购药的系统
CN113744836A (zh) * 2021-09-08 2021-12-03 平安科技（深圳）有限公司 基于自然语言处理的处方生成方法、装置、设备及介质
CN114119163A (zh) * 2021-11-30 2022-03-01 北京三快在线科技有限公司 一种执行药品购买业务的方法及装置
CN114283919A (zh) * 2021-12-27 2022-04-05 朗森特科技有限公司 一种基于电子处方的自动售药柜及其系统
CN115099895A (zh) * 2022-06-27 2022-09-23 康键信息技术（深圳）有限公司 基于人工智能的在线购药方法及装置、存储介质

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