Online registration processing system and method based on oncology department
By extracting keyword groups from patient medical information and automatically matching them with oncology department options, the system enables accurate online registration without the need for professional personnel, solving the problem of online registration errors and improving the accuracy and efficiency of registration.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ZHONGKEYINO (BEIJING) INT MEDICAL RES INST CO LTD
- Filing Date
- 2025-12-22
- Publication Date
- 2026-04-17
AI Technical Summary
In existing technologies, patients often make incorrect appointments online due to a lack of professional judgment, resulting in wasted time and resources.
By obtaining the patient's basic information and medical condition information, extracting target keyword groups, matching the oncology department option set with the oncology keyword database, and generating registration information, accurate registration can be achieved independently without the need for professional doctors or service personnel.
It has improved the accuracy and efficiency of online registration, reducing the waste of time and resources for both patients and hospitals.
Smart Images
Figure CN121885121A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of data processing technology, and in particular to an online registration system and method for oncology departments. Background Technology
[0002] To reduce patients' medical costs and shorten their registration time, many hospitals have launched online appointment registration systems. Patients register their account information, obtain expert information online, and complete the appointment. Then, within the specified time period, they go to the triage desk with their appointment number to collect their number and wait for their appointment.
[0003] However, since patients and registration staff are often not professional doctors, patients rely on subjective experience to determine which department to register in. If the wrong registration is made, it wastes the time and energy of both the patient and the hospital staff. If experienced doctors are responsible for registration, it wastes the hospital's human resources. Summary of the Invention
[0004] This application provides an online registration system and method based on oncology departments to improve the accuracy of online registration.
[0005] This invention provides an online registration method based on oncology departments, the method comprising:
[0006] Obtain patient information sent by the patient client, the patient information including basic patient information and patient condition information;
[0007] Target keyword groups are extracted from the patient's medical information, and a set of matching oncology department options is determined based on the extracted target keyword groups. The set of oncology department options includes at least one oncology department that can be booked.
[0008] The oncology department option set is sent to the patient client so that the patient client can display each oncology department that can be booked in the oncology department option set on the screen interface;
[0009] Receive the oncology department selected by the user on the screen interface of the patient client, and generate registration information corresponding to the patient's basic information based on the selected oncology department;
[0010] The registration information is sent to the patient's client, so that the patient's client displays the registration information.
[0011] In an optional embodiment of the present invention, the step of extracting target keyword groups from the patient's condition information includes:
[0012] The patient's condition information was segmented to obtain initial keywords;
[0013] Based on the context of the patient's condition information, the initial keywords are grouped into keyword groups, which include adjective keywords, degree keywords, and / or noun keywords;
[0014] The keyword group is matched with keyword groups in the tumor keyword database, and the successfully matched keyword group is determined as the target keyword group. The tumor keyword database stores multiple keyword groups related to tumor symptoms.
[0015] In an optional embodiment of the present invention, determining the set of matching oncology department options based on the extracted target keyword groups includes:
[0016] The extracted target keyword groups are matched with the corresponding keyword groups for each oncology department;
[0017] Calculate the matching value for each oncology department corresponding to the extracted target keyword group;
[0018] Oncology departments whose matching values exceed preset values are identified as oncology departments available for registration in the oncology department option set.
[0019] In an optional embodiment of the present invention, calculating the matching value corresponding to the extracted target keyword group for each oncology department includes:
[0020] The matching value for the extracted target keyword group for each oncology department is calculated using the following formula:
[0021]
[0022] Among them, A j For the j-th target keyword group, B i Let be the i-th keyword group in the p-th oncology department, n be the number of keyword groups in the p-th oncology department, m be the number of target keyword groups extracted, and α and β be the values based on A. j The corresponding adjective keywords and degree keywords determine the weight coefficient, K. p is the matching value of the extracted target keyword group for the p-th oncology department.
[0023] In an optional embodiment provided by the present invention, the method further includes:
[0024] Get A j B i These correspond to the levels of descriptive keywords and the levels of degree keywords, respectively.
[0025] If A j B iThe corresponding descriptive keywords have different levels of intensity, and the degree keywords also have different levels of intensity; according to A j B i The weight coefficient α of the descriptive keyword is determined by the ratio of the rankings of the corresponding descriptive keywords; according to A... j B i The weight coefficient β of the degree keyword is determined by the ratio of the levels of the corresponding degree keywords; where the ratio of the levels of the adjective keywords to the levels of the degree keywords is A. j B i The lower-level ones are better than the higher-level ones;
[0026] If A j B i If the corresponding descriptive keywords have the same level and the degree keywords have the same level, then α and β are both 1.
[0027] In an optional embodiment of the present invention, determining the oncology departments whose matching values exceed a preset value as oncology departments available for registration in the oncology department option set includes:
[0028] Determine if there are any remaining numbers in oncology departments where the matching value exceeds the preset value;
[0029] If there are remaining appointment slots in oncology departments whose matching value exceeds the preset value, then the oncology departments with remaining appointment slots and matching values exceeding the preset value will be identified as oncology departments available for registration in the oncology department option set.
[0030] In an optional embodiment of the present invention, the registration information includes medical navigation information and basic information about the oncology department. The generation of registration information corresponding to the patient's basic information based on the selected oncology department includes:
[0031] Generate basic information about the oncology department corresponding to the patient's basic information based on the basic information of the selected oncology department;
[0032] Based on the location information of the selected oncology department, navigation information corresponding to the patient's basic information is generated.
[0033] In an optional embodiment of the present invention, generating medical navigation information corresponding to the patient's basic information based on the location information of the selected oncology department includes:
[0034] Obtain the current location information of the client, and generate medical navigation information corresponding to the patient's basic information based on the current location information and the location information of the selected oncology department.
[0035] In an optional embodiment of the present invention, determining the set of matching oncology department options based on the extracted target keyword groups includes:
[0036] Convert the extracted target keyword groups into target feature vectors;
[0037] Calculate the similarity between each target feature vector and each feature vector in each tumor vector database;
[0038] The oncology departments corresponding to tumor vectors with similarity exceeding the preset similarity are identified as the oncology departments available for registration in the oncology department option set.
[0039] This invention provides an online registration system for oncology departments, the system comprising:
[0040] The acquisition module is used to acquire patient information sent by the patient client, including basic patient information and patient condition information.
[0041] The determination module is used to extract target keyword groups from the patient's condition information, and determine a set of matching oncology department options based on the extracted target keyword groups, wherein the set of oncology department options includes at least one oncology department that can be booked.
[0042] The sending module is used to send the oncology department option set to the patient client, so that the patient client can display each oncology department that can be registered in the oncology department option set on the screen interface;
[0043] The generation module is used to receive the oncology department selected by the user on the screen interface of the patient client, and generate registration information corresponding to the patient's basic information based on the selected oncology department;
[0044] The sending module is also used to send the registration information to the patient client, so that the patient client displays the registration information.
[0045] This application provides an online appointment system and method based on oncology departments. First, it acquires patient information sent by the patient client, including basic patient information and patient condition information. Then, it extracts target keyword groups from the patient condition information and determines a set of matching oncology department options based on the extracted target keyword groups. The set of oncology department options includes at least one oncology department that can be booked. The set of oncology department options is sent to the patient client, so that the patient client can display each oncology department that can be booked in the set on the screen interface. The system also receives the oncology department selected by the corresponding user on the screen interface and generates appointment information corresponding to the patient's basic information based on the selected oncology department. Finally, the appointment information is sent to the patient client, so that the patient client can display the appointment information. Compared with existing technologies, this application automatically matches available oncology departments based on target keyword groups extracted from the patient's condition information, allowing users to complete appointments independently without the need for professional doctors or service personnel, thereby improving the accuracy of online appointments. Attached Figure Description
[0046] Figure 1 This application provides a flowchart of an online registration process based on an oncology department.
[0047] Figure 2 A flowchart for determining a set of oncology department options provided in this application;
[0048] Figure 3 This application provides a structural diagram of an online registration system based on an oncology department. Detailed Implementation
[0049] To better understand the above technical solutions, the technical solutions of the embodiments of this application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of this application and the specific features in the embodiments are detailed descriptions of the technical solutions of the embodiments of this application, rather than limitations on the technical solutions of this application. In the absence of conflict, the embodiments of this application and the technical features in the embodiments can be combined with each other.
[0050] Please see Figure 1 As shown in the figure, this invention provides an online registration method based on the oncology department. The execution flow of this method is as follows:
[0051] S101, Obtain patient information sent by the patient client.
[0052] The patient information includes basic patient information and patient condition information. Basic patient information may include name, age, ID number, weight, height, etc. Patient condition information is information entered by the client user to describe the symptoms, such as "headache accompanied by nausea, insomnia and excessive dreaming". The patient condition information can also be filled in based on the guidance information displayed on the client screen interface, such as by entering various items through the form interface displayed on the screen. For example, the pain location can be selected as head, chest, etc., and the pain level can be selected as mild pain, severe pain, etc. The user can also manually enter text information to supplement the description. The corresponding patient condition information can also be obtained by calling the corresponding medical records through the patient's basic information. This embodiment does not specifically limit the method of obtaining patient condition information.
[0053] S102, extract target keyword groups from patient condition information, and determine a set of matching oncology department options based on the extracted target keyword groups.
[0054] The oncology department option set includes at least one oncology department that can be booked. Different oncology departments can be identified by different identifiers, such as Oncology Department 1, Oncology Department 2, Oncology Department 3, etc. In this embodiment, the target keyword group includes multiple keywords, which are related in context. For example, the target keyword group is (head, pain, occasional), which includes three keywords extracted from the patient's condition information that are related in context. That is, "occasionally" is used to specify the tense of "pain," and the object of "pain" is "head."
[0055] Specifically, this embodiment extracts target keyword groups from patient condition information, including: segmenting the patient condition information into words to obtain initial keywords; forming keyword groups from the initial keywords based on the context of the patient condition information, wherein the keyword groups include adjective keywords, degree keywords, and / or noun keywords; matching the keyword groups with keyword groups in a tumor keyword database, and determining the successfully matched keyword groups as target keyword groups.
[0056] It should be noted that the tumor keyword database in this embodiment stores multiple keyword groups related to tumor symptoms, and each keyword group also includes multiple keywords. In this embodiment, keyword group matching can be precise matching or fuzzy matching. For example, the keyword groups extracted based on the patient's condition information include: (head, pain) and (eyes, blurred vision). These keyword groups are matched with keyword groups related to tumor symptoms in the tumor keyword database. If the tumor keyword database contains the keyword groups (head, pain) and (eyes, blurred vision), and if the match is fuzzy, then the keyword groups (head, pain) and (eyes, blurred vision) can be identified as the target keyword groups.
[0057] like Figure 2 As shown, in an optional embodiment provided in this application, determining the set of matching oncology department options based on the extracted target keyword groups includes:
[0058] S1021, Match the extracted target keyword groups with the corresponding keyword groups for each oncology department.
[0059] S1022, Calculate the matching value of each oncology department for the extracted target keyword group.
[0060] Specifically, the matching value for each oncology department corresponding to the extracted target keyword group is calculated using the following formula:
[0061]
[0062] Among them, A j For the j-th target keyword group, B i Let be the i-th keyword group in the p-th oncology department, n be the number of keyword groups in the p-th oncology department, m be the number of target keyword groups extracted, and α and β be the values based on A. j The corresponding adjective keywords and degree keywords determine the weight coefficient, K. p is the matching value of the p-th oncology department for the extracted target keyword group.
[0063] In one optional embodiment provided in this application, A can also be determined by the following formula. j B i Matching value:
[0064]
[0065] It should be noted that in this embodiment, the noun keywords are body part keywords, adjectives are used to describe the symptoms of the noun keywords, and degree keywords are used to describe the degree expressed by the adjective keywords. This embodiment does not impose specific limitations on these. For example, A j = (Head, pain, mild), Bi = (head, pain, particular), A can be determined using the above formula. j B i =0.7, meaning that the noun keywords and adjective keywords in the two keyword groups have the same meaning.
[0066] In this embodiment, if there is no corresponding descriptive or degree keyword in the keyword group, the corresponding matching value can be obtained directly based on the existing keywords within the keyword group. For example, A j = (Head, pain), B i = (headache), then A j B i =1.
[0067] In an optional embodiment provided in this application, the matching value of the two keyword groups can also be calculated based on the levels of the descriptive keywords and degree keywords, that is, calculated using the weight coefficients determined by the specific descriptive keywords and degree keywords corresponding to α and β. The process for determining the weight coefficients of the descriptive keywords and degree keywords corresponding to α and β is as follows: Obtain A j B i These correspond to the levels of descriptive keywords and the levels of degree keywords, respectively; if A j B i The corresponding descriptive keywords have different levels of intensity, and the degree keywords also have different levels of intensity; according to A j B i The weight coefficient α of the descriptive keyword is determined by the ratio of the rankings of the corresponding descriptive keywords; according to A... j B i The weight coefficient β of the degree keyword is determined by the ratio of the levels of the corresponding degree keywords; where the ratio of the levels of the adjective keywords to the levels of the degree keywords is A. j B i The lower-level is higher than the higher-level; if A j B i If the corresponding descriptive keywords have the same level and the degree keywords have the same level, then α and β are both 1.
[0068] For example, severity keywords can be divided into three levels: mild pain, severe pain, and high pain. j B i The corresponding descriptive keywords have levels of 1 and 2, and the degree keywords have levels of 2 and 3; therefore, according to A... j B i The weight coefficient α = 1 / 2 is determined by the ratio of the ranking of the corresponding descriptive keywords. j B iThe weight coefficient β = 2 / 3 is determined by the ratio of the levels of the corresponding degree keywords.
[0069] S1023, Oncology departments whose matching values exceed preset values are identified as oncology departments in the oncology department option set that can be registered.
[0070] The preset values can be set according to actual needs, or multiple oncology departments with high matching values can be identified as oncology departments that can be registered in the candidate set of oncology departments. This embodiment does not make specific limitations in this regard.
[0071] In one optional embodiment provided in this application, determining the oncology departments whose matching values exceed a preset value as oncology departments available for registration in the oncology department option set includes: determining whether there are any remaining appointments among the oncology departments whose matching values exceed the preset value; if there are remaining appointments among the oncology departments whose matching values exceed the preset value, then determining the oncology departments with remaining appointments and matching values exceeding the preset value as oncology departments available for registration in the oncology department option set.
[0072] For example, oncology departments with matching values exceeding the preset values include: Oncology Department 1, Oncology Department 2, and Oncology Department 3. Oncology Department 2 has no remaining appointments, indicating that it is already fully booked. Therefore, Oncology Department 1 and Oncology Department 2 are identified as oncology departments available for appointment within the oncology department option set.
[0073] In this embodiment, the extracted target keyword groups are first matched with the corresponding keyword groups for each oncology department. Then, the matching value for each oncology department with respect to the extracted target keyword groups is calculated. Finally, oncology departments with matching values exceeding a preset value are identified as oncology departments available for registration in the oncology department option set. Since the target keyword groups in this embodiment are extracted from the patient's condition information, by calculating the matching value for each oncology department with respect to the extracted target keyword groups, the oncology department corresponding to the patient's condition can be identified. The entire process does not require the intervention of professional medical personnel; users can register independently through the client. Therefore, this embodiment can improve the accuracy and efficiency of oncology department registration.
[0074] S103, the oncology department option set is sent to the patient client so that the patient client can see each oncology department that can be registered in the oncology department option set displayed on the screen interface.
[0075] In this embodiment, after the oncology department option set is sent to the patient client, the client can display the oncology departments in the oncology department option set in descending order of matching value, so that the client user can select the corresponding oncology department for registration.
[0076] It should be noted that if the client user in this embodiment is a follow-up visit user, the department they previously booked can also be displayed on the screen interface, allowing them to choose whether to continue booking for a follow-up visit, thereby improving the user experience.
[0077] S104, Receive the oncology department selected by the user on the screen interface of the patient client, and generate registration information corresponding to the patient's basic information based on the selected oncology department.
[0078] The registration information includes the appointment time, location, doctor, and precautions, but this embodiment does not specify these details.
[0079] In an optional embodiment provided in this example, the registration information includes medical navigation information and basic information of the oncology department. The process of generating registration information corresponding to the patient's basic information based on the selected oncology department includes: generating basic information of the oncology department corresponding to the patient's basic information based on the basic information of the selected oncology department; and generating medical navigation information corresponding to the patient's basic information based on the location information of the selected oncology department.
[0080] More specifically, generating the medical navigation information corresponding to the patient's basic information based on the location information of the selected oncology department includes: obtaining the current location information of the client, and generating the medical navigation information corresponding to the patient's basic information based on the current location information and the location information of the selected oncology department.
[0081] It should be noted that the medical navigation information in this embodiment can not only plan the driving route, but also plan the corresponding examination sequence. If a user has performed multiple physical examinations, this embodiment can first obtain the status information of each physical examination task. This status information can include the number of people queuing for physical examinations, the duration of the physical examination, etc. Then, based on the status information, the order of each physical examination task is planned, and after determining the order of the physical examination tasks, a corresponding navigation path is formulated so that the client user can travel to the corresponding department for physical examination based on the navigation path.
[0082] S105, the registration information is sent to the patient's client, so that the patient's client displays the registration information.
[0083] This invention provides an online appointment booking method based on oncology departments. First, patient information, including basic patient information and medical condition information, is obtained from the patient's client. Then, target keyword groups are extracted from the patient's medical condition information. Based on the extracted target keyword groups, a set of matching oncology department options is determined, with at least one oncology department available for appointment booking. The oncology department option set is sent to the patient's client, allowing the client to display each available oncology department on their screen. The method also receives the oncology department selected by the user on the screen and generates appointment information corresponding to the patient's basic information based on the selected department. Finally, the appointment information is sent to the patient's client, allowing the client to display the appointment information. Compared to existing technologies, this application automatically matches available oncology departments based on target keyword groups extracted from the patient's medical condition information, enabling self-registration without the need for professional doctors or service personnel, thus improving the accuracy of online appointment booking.
[0084] In one embodiment, an online appointment system based on oncology departments is provided, which corresponds one-to-one with the aforementioned online appointment method based on oncology departments. For example... Figure 3 As shown, the device includes:
[0085] The acquisition module 31 is used to acquire patient information sent by the patient client, the patient information including basic patient information and patient condition information;
[0086] The determination module 32 is used to extract target keyword groups from the patient's condition information, and determine a set of matching oncology department options based on the extracted target keyword groups, wherein the set of oncology department options includes at least one oncology department that can be registered for.
[0087] The sending module 33 is used to send the oncology department option set to the patient client, so that the patient client can display each oncology department that can be registered in the oncology department option set on the screen interface;
[0088] The generation module 34 is used to receive the oncology department selected by the user corresponding to the patient client on the screen interface, and generate registration information corresponding to the patient's basic information based on the selected oncology department;
[0089] The sending module 33 is also used to send the registration information to the patient client, so that the patient client displays the registration information.
[0090] In an optional embodiment of the present invention, the determining module 32 is specifically used for:
[0091] The patient's condition information was segmented to obtain initial keywords;
[0092] Based on the context of the patient's condition information, the initial keywords are grouped into keyword groups, which include adjective keywords, degree keywords, and / or noun keywords;
[0093] The keyword group is matched with keyword groups in the tumor keyword database, and the successfully matched keyword group is determined as the target keyword group. The tumor keyword database stores multiple keyword groups related to tumor symptoms.
[0094] In an optional embodiment of the present invention, the determining module 32 is specifically used for:
[0095] The extracted target keyword groups are matched with the corresponding keyword groups for each oncology department;
[0096] Calculate the matching value for each oncology department corresponding to the extracted target keyword group;
[0097] Oncology departments whose matching values exceed preset values are identified as oncology departments available for registration in the oncology department option set.
[0098] In an optional embodiment of the present invention, the determining module 32 is specifically used for:
[0099] The matching value for the extracted target keyword group for each oncology department is calculated using the following formula:
[0100]
[0101] Among them, A j For the j-th target keyword group, B i Let be the i-th keyword group in the p-th oncology department, n be the number of keyword groups in the p-th oncology department, m be the number of target keyword groups extracted, and α and β be the values based on A. j The corresponding adjective keywords and degree keywords determine the weight coefficient, K. p is the matching value of the extracted target keyword group for the p-th oncology department.
[0102] In an optional embodiment of the present invention, the determining module 32 is specifically used for:
[0103] Get A j B i These correspond to the levels of descriptive keywords and the levels of degree keywords, respectively.
[0104] If A j B iThe corresponding descriptive keywords have different levels of intensity, and the degree keywords also have different levels of intensity; according to A j B i The weight coefficient α of the descriptive keyword is determined by the ratio of the rankings of the corresponding descriptive keywords; according to A... j B i The weight coefficient β of the degree keyword is determined by the ratio of the levels of the corresponding degree keywords; where the ratio of the levels of the adjective keywords to the levels of the degree keywords is A. j B i The lower-level ones are better than the higher-level ones;
[0105] If A j B i If the corresponding descriptive keywords have the same level and the degree keywords have the same level, then α and β are both 1.
[0106] In an optional embodiment of the present invention, the determining module 32 is specifically used for:
[0107] Determine if there are any remaining numbers in oncology departments where the matching value exceeds the preset value;
[0108] If there are remaining appointment slots in oncology departments whose matching value exceeds the preset value, then the oncology departments with remaining appointment slots and matching values exceeding the preset value will be identified as oncology departments available for registration in the oncology department option set.
[0109] In an optional embodiment of the present invention, the determining module 32 is specifically used for:
[0110] Generate basic information about the oncology department corresponding to the patient's basic information based on the basic information of the selected oncology department;
[0111] Based on the location information of the selected oncology department, navigation information corresponding to the patient's basic information is generated.
[0112] In an optional embodiment of the present invention, the determining module 32 is specifically used for:
[0113] Obtain the current location information of the client, and generate medical navigation information corresponding to the patient's basic information based on the current location information and the location information of the selected oncology department.
[0114] In an optional embodiment of the present invention, the determining module 32 is specifically used for:
[0115] Convert the extracted target keyword groups into target feature vectors;
[0116] Calculate the similarity between each target feature vector and each feature vector in each tumor vector database;
[0117] The oncology departments corresponding to tumor vectors with similarity exceeding the preset similarity are identified as the oncology departments available for registration in the oncology department option set.
[0118] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.
Claims
1. A method for online registration processing based on oncology departments, characterized in that, The method includes: Obtain patient information sent by the patient client, the patient information including basic patient information and patient condition information; Target keyword groups are extracted from the patient's medical information, and a set of matching oncology department options is determined based on the extracted target keyword groups. The set of oncology department options includes at least one oncology department that can be booked. The oncology department option set is sent to the patient client so that the patient client can display each oncology department that can be booked in the oncology department option set on the screen interface; Receive the oncology department selected by the user on the screen interface of the patient client, and generate registration information corresponding to the patient's basic information based on the selected oncology department; The registration information is sent to the patient's client, so that the patient's client displays the registration information.
2. The method according to claim 1, characterized in that, The extraction of target keyword groups from the patient's medical information includes: The patient's condition information was segmented to obtain initial keywords; Based on the context of the patient's condition information, the initial keywords are grouped into keyword groups, which include adjective keywords, degree keywords, and / or noun keywords; The keyword group is matched with keyword groups in the tumor keyword database, and the successfully matched keyword group is determined as the target keyword group. The tumor keyword database stores multiple keyword groups related to tumor symptoms.
3. The method according to claim 2, characterized in that, The set of matching oncology department options determined based on the extracted target keyword groups includes: The extracted target keyword groups are matched with the corresponding keyword groups for each oncology department; Calculate the matching value for each oncology department corresponding to the extracted target keyword group; Oncology departments whose matching values exceed preset values are identified as oncology departments available for registration in the oncology department option set.
4. The method according to claim 3, characterized in that, The calculation of the matching value for each oncology department corresponding to the extracted target keyword group includes: The matching value for the extracted target keyword group for each oncology department is calculated using the following formula: Wherein, A j is the jth target keyword group, B i is the ith keyword group in the pth oncology department, n is the number of keyword groups in the pth oncology department, m is the number of extracted target keyword groups, and α, β are weight coefficients corresponding to the determined adjectival keywords and degree keywords. j K p is the matching value of the pth oncology department to the extracted target keyword group.
5. The method according to claim 4, characterized in that, The process of determining α and β is as follows: Get A j B i These correspond to the levels of descriptive keywords and the levels of degree keywords, respectively. If A j B i The corresponding descriptive keywords have different levels of intensity, and the degree keywords also have different levels of intensity; according to A j B i The weight coefficient α of the descriptive keyword is determined by the ratio of the rankings of the corresponding descriptive keywords; according to A... j B i The weight coefficient β of the degree keyword is determined by the ratio of the levels of the corresponding degree keywords; where the ratio of the levels of the adjective keywords to the levels of the degree keywords is A. j B i The lower-level ones are better than the higher-level ones; If A j B i If the corresponding descriptive keywords have the same level and the degree keywords have the same level, then α and β are both 1.
6. The method according to claim 3, characterized in that, The step of identifying oncology departments whose matching values exceed a preset value as eligible oncology departments in the oncology department option set includes: Determine if there are any remaining numbers in oncology departments where the matching value exceeds the preset value; If there are remaining appointment slots in oncology departments whose matching value exceeds the preset value, then the oncology departments with remaining appointment slots and matching values exceeding the preset value will be identified as oncology departments available for registration in the oncology department option set.
7. The method according to claim 1, characterized in that, The registration information includes patient navigation information and basic information about the oncology department. The registration information generated based on the selected oncology department and corresponding to the patient's basic information includes: Generate basic information about the oncology department corresponding to the patient's basic information based on the basic information of the selected oncology department; Based on the location information of the selected oncology department, navigation information corresponding to the patient's basic information is generated.
8. The method according to claim 7, characterized in that, The process of generating medical navigation information corresponding to the patient's basic information based on the location information of the selected oncology department includes: Obtain the current location information of the client, and generate medical navigation information corresponding to the patient's basic information based on the current location information and the location information of the selected oncology department.
9. The method according to claim 2, characterized in that, The set of matching oncology department options determined based on the extracted target keyword groups includes: Convert the extracted target keyword groups into target feature vectors; Calculate the similarity between each target feature vector and each feature vector in each tumor vector database; The oncology departments corresponding to tumor vectors with similarity exceeding the preset similarity are identified as the oncology departments available for registration in the oncology department option set.
10. An online registration system for oncology departments based on the method described in any one of claims 1-9, characterized in that, The system includes: The acquisition module is used to acquire patient information sent by the patient client, including basic patient information and patient condition information. The determination module is used to extract target keyword groups from the patient's condition information, and determine a set of matching oncology department options based on the extracted target keyword groups, wherein the set of oncology department options includes at least one oncology department that can be booked. The sending module is used to send the oncology department option set to the patient client, so that the patient client can display each oncology department that can be registered in the oncology department option set on the screen interface; The generation module is used to receive the oncology department selected by the user on the screen interface of the patient client, and generate registration information corresponding to the patient's basic information based on the selected oncology department; The sending module is also used to send the registration information to the patient client, so that the patient client displays the registration information.