Intervention task scheduling method and device and electronic equipment
By generating execution frequency constraint expressions and time roulettes, the problem of low accuracy and delay in target intervention tasks recommendation in digital therapy is solved, and more efficient task scheduling and execution is achieved.
Patent Information
- Application Number
- CN202311470296.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-11-06
- Publication Date
- 2025-05-06
AI Technical Summary
In digital therapy, due to the wide variety of target intervention tasks and the large amount of data, the system recommends target intervention tasks to patients with low accuracy and prone to delays.
By obtaining the intervention frequency and intervention time of the target intervention task, generating the execution frequency constraint expression, and generating a time roulette in combination with the execution start and end times, the target intervention task is scheduled to improve recommendation accuracy and avoid delays.
Improve the accuracy of recommending target intervention tasks to patients, avoid push delays, and ensure timely execution of tasks.
Smart Images
Figure CN119938242A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the field of data processing technology, and in particular to an intervention task scheduling method, device, and electronic device. Background Art
[0002] Digital therapy allows patients to obtain treatment plans and receive treatment at home online, solving the problems of difficulty in making appointments at traditional treatment hospitals, long journeys to the hospital, crowded queues, long waiting times, and poor patient experience.
[0003] Digital therapy can monitor patients' physical indicator data in real time through smart wearable devices, collect patients' lifestyle and personalized condition data through online assessments, and analyze these patient data to generate personalized treatment plans for patients based on artificial intelligence algorithms, thereby achieving the goal of tailored treatment for each individual.
[0004] In digital therapy, each patient's personalized treatment plan will include corresponding target intervention tasks to guide or monitor the patient's daily diet, sleep, exercise, psychology, etc. However, due to the wide variety of target intervention tasks and the large amount of data, the system is not accurate in recommending target intervention tasks to patients and is prone to delays. Summary of the invention
[0005] The present disclosure provides an intervention task scheduling method, device, and electronic device.
[0006] According to a first aspect of the present disclosure, there is provided an intervention task scheduling method, which includes:
[0007] Obtain the intervention frequency and intervention time of the target intervention task;
[0008] Based on the intervention frequency and intervention time, generating an execution frequency constraint expression for executing the target intervention task;
[0009] Obtaining the execution start time and execution end time of the target intervention task;
[0010] Based on the execution frequency constraint expression, the execution start time, and the execution end time, a time wheel for scheduling the target intervention task is generated;
[0011] Based on the time wheel, the target intervention task is scheduled for execution.
[0012] Optionally, generating an execution frequency constraint expression for executing the target intervention task based on the intervention frequency and intervention time includes:
[0013] The intervention frequency and intervention time are filled into the time domain to generate a string expression for executing the target intervention task, and the string expression is used as the execution frequency constraint expression.
[0014] Optionally, filling the intervention frequency and intervention time into a time domain sequence to generate a string expression for executing the target intervention task includes:
[0015] Parsing the time domain sequence to determine an intervention frequency setting domain and an intervention time setting domain in the time domain sequence;
[0016] The intervention frequency and intervention time are filled into the intervention frequency setting field and the intervention time setting field respectively to generate a character string expression for executing the target intervention task.
[0017] Optionally, the method further comprises:
[0018] Obtain the task record ID corresponding to the target intervention task and add it to the message queue;
[0019] Based on the time wheel, scheduling the target intervention task for execution includes: based on the time wheel, obtaining the task record ID from the message queue to execute the target intervention task corresponding to the task record ID.
[0020] Optionally, the method further comprises:
[0021] The task record ID is generated according to the target intervention task ID and the intervention content ID to be accessed when executing the target intervention task.
[0022] Optionally, scheduling the target intervention task for execution based on the time wheel includes:
[0023] Generate a scheduling task package based on the target intervention task ID;
[0024] Based on the time wheel, the corresponding target intervention task is searched in the task queue according to the scheduling task package, and the business is packaged and sent to the front end for execution.
[0025] Optionally, the method further comprises:
[0026] A response message for the execution of the target intervention task is generated, wherein the response message includes the target intervention task ID and a push target of the target intervention task.
[0027] Optionally, the method further includes: generating the target intervention task according to the trigger condition description of the target intervention task and the indicator code of the target patient.
[0028] According to a second aspect of the present disclosure, there is provided an intervention task scheduling device, comprising:
[0029] A first data acquisition unit, used to acquire the intervention frequency and intervention time of the target intervention task;
[0030] An expression generation unit, used to generate an execution frequency constraint expression for executing the target intervention task based on the intervention frequency and intervention time;
[0031] A second data acquisition unit, used to acquire the execution start time and execution end time of the target intervention task;
[0032] A roulette generation unit, configured to generate a time roulette for scheduling the target intervention task based on the execution frequency constraint expression, the execution start time, and the execution end time;
[0033] A task scheduling unit is used to schedule the target intervention task for execution based on the time wheel.
[0034] According to a third aspect of the present disclosure, there is provided an electronic device, comprising:
[0035] at least one processor; and
[0036] a memory communicatively connected to the at least one processor; wherein,
[0037] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute any method described in the embodiments of the present application.
[0038] In the disclosed scheme, the intervention frequency and intervention time of the target intervention task are obtained; based on the intervention frequency and intervention time, an execution frequency constraint expression for executing the target intervention task is generated; the execution start time and execution end time of the target intervention task are obtained; based on the execution frequency constraint expression, the execution start time and the execution end time, a time wheel for scheduling the target intervention task is generated; based on the time wheel, the target intervention task is scheduled for execution, thereby ensuring the accuracy of recommending the target intervention task to the patient and avoiding push delays.
[0039] It should be understood that the contents described in the summary of the invention are not intended to limit the key or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS
[0040] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein:
[0041] Figure 1 A flowchart of an intervention task scheduling method according to an embodiment of the present disclosure is shown;
[0042] Figure 2 A block diagram of a target intervention task generating device according to an embodiment of the present disclosure is shown;
[0043] Figure 3 A block diagram of an exemplary electronic device capable of implementing embodiments of the present disclosure is shown. DETAILED DESCRIPTION
[0044] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.
[0045] In addition, the term "and / or" in this article is only a description of the association relationship between the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.
[0046] Figure 1 FIG. 1 is a flow chart of an intervention task scheduling method according to an embodiment of the present application. Figure 1 As shown, it includes:
[0047] S101, obtaining the intervention frequency and intervention time of the target intervention task;
[0048] In this embodiment, the interference content configuration data corresponding to the target intervention task may be parsed to obtain the intervention frequency and intervention time of the target intervention task.
[0049] In this embodiment, the intervention frequency defines the frequency of intervention content push, and the intervention time defines the time period range of intervention content push.
[0050] For example, in a specific application scenario, the intervention frequency of the intervention content is pushed once a day, and the intervention time is 11:21, which means that a specific task will be generated at 11:21 every day.
[0051] S102, generating an execution frequency constraint expression for executing the target intervention task based on the intervention frequency and intervention time;
[0052] In this embodiment, the form of the execution frequency constraint expression is not limited, for example, it can be in the form of a string or other forms.
[0053] S103, obtaining the execution start time and execution end time of the target intervention task;
[0054] In this embodiment, the interference content configuration data corresponding to the target intervention task may be parsed to obtain the execution start time and the execution end time of the target intervention task.
[0055] The execution start time and the execution end time respectively define when the target intervention task starts to be executed and when it ends.
[0056] S104, generating a time wheel for scheduling the target intervention task based on the execution frequency constraint expression, the execution start time, and the execution end time;
[0057] In this embodiment, the form of the time wheel is not limited.
[0058] In this embodiment, the time wheel is equivalent to defining the life cycle of the target intervention task, thereby facilitating subsequent scheduling.
[0059] S105: Based on the time wheel, schedule the target intervention task for execution.
[0060] Optionally, generating an execution frequency constraint expression for executing the target intervention task based on the intervention frequency and intervention time includes:
[0061] The intervention frequency and intervention time are filled into the time domain to generate a string expression for executing the target intervention task, and the string expression is used as the execution frequency constraint expression.
[0062] In this embodiment, for example, if the intervention frequency of the intervention content is pushed once a day, and the intervention time is 11:21, it means that a specific task will be generated at 11:21 every day. According to the frequency and time, the system will generate an execution frequency constraint expression: 0 21 11.
[0063] Optionally, filling the intervention frequency and intervention time into a time domain sequence to generate a string expression for executing the target intervention task includes:
[0064] Parsing the time domain sequence to determine an intervention frequency setting domain and an intervention time setting domain in the time domain sequence;
[0065] The intervention frequency and intervention time are filled into the intervention frequency setting field and the intervention time setting field respectively to generate a character string expression for executing the target intervention task.
[0066] Specifically, the time domain sequence includes, for example, 7 domains divided by 6 spaces, each domain representing a time meaning. Usually, the part defining "year" can be omitted, and the time domain sequence is: {seconds}{minutes}{hours}{date}{month}(week}{year (can be empty)}
[0067] Among them, the following logical characters are used to generate string expressions:
[0068] * (wildcard): matches any value, for example *****? means the task is executed once per second.
[0069] ,(list): used to specify multiple values, for example, 0 0 6,12,18**? means that the task is executed at 6:00, 12:00 and 18:00 every day.
[0070] -(range): used to specify a value within a range. For example, 0 0 9-17**MON-FRI means that the task is executed every hour between 9:00 and 17:00 from Monday to Friday.
[0071] / (step): used to specify a step size. For example, 0* / 30***? means that the task is executed every 30 minutes.
[0072] ? (meaningless placeholder): used to specify that a field has no specific value and can only be used with other fields, for example, 0 0 12? *MON-FRI means that the task is executed at 12 noon from Monday to Friday.
[0073] #(calendar offset): used to specify the day of the week of a month, for example, 0 0 0? *3#1 means that the task is executed on the first Wednesday of every month.
[0074] L (Last): indicates the last day within a specified period of time. For example, 0 0L**? indicates that the task will be executed on the last day of each month.
[0075] W (Weekday): indicates the working day closest to the specified date. For example, 0 0 0 15W*? indicates that the task will be executed on the 15th working day of the month. If the 15th is a working day, the task will be executed; if the 15th is a weekend, the task will be executed on the nearest working day, the 14th.
[0076] C (Calendar): indicates the day closest to the specified date. For example, 0 0 0 1W*? indicates that the task will be executed on the first working day of the month. If the 1st is a working day, the task will be executed; if the 1st is a weekend, the task will be postponed to the nearest working day, that is, the 2nd.
[0077] The difference between W and C is that W can only be used in the day field, indicating the nearest working day to the specified date; while C can be used in the month, day, and week field, indicating the nearest day to the specified date. At the same time, C can also be used in combination with the week field, for example, 0 0 0? *2#2 means executing the task on the second Tuesday of every month.
[0078] Optionally, the method further comprises:
[0079] Obtain the task record ID corresponding to the target intervention task and add it to the message queue;
[0080] Based on the time wheel, scheduling the target intervention task for execution includes: based on the time wheel, obtaining the task record ID from the message queue to execute the target intervention task corresponding to the task record ID.
[0081] In this embodiment, the target intervention task is executed by means of a message queue, which improves the efficiency of task execution and avoids task conflicts.
[0082] Optionally, the method further comprises:
[0083] The task record ID is generated according to the target intervention task ID and the intervention content ID to be accessed when executing the target intervention task.
[0084] In this embodiment, different task record IDs are generated for target intervention tasks, thereby facilitating the management and scheduling of different target intervention tasks.
[0085] Optionally, scheduling the target intervention task for execution based on the time wheel includes:
[0086] Generate a scheduling task package based on the target intervention task ID;
[0087] Based on the time wheel, the corresponding target intervention task is searched in the task queue according to the scheduling task package, and the business is packaged and sent to the front end for execution.
[0088] In this embodiment, by generating a scheduling task package, the concurrent execution of multiple target intervention tasks can be achieved, thereby improving the efficiency of task scheduling.
[0089] Optionally, the method further comprises:
[0090] A response message for the execution of the target intervention task is generated, wherein the response message includes the target intervention task ID and a push target of the target intervention task.
[0091] In the above embodiment, the subject that executes each step may be, for example, a task scheduler, and the type of the task scheduler is not limited here.
[0092] In the above embodiment, when executing the target intervention task, the target patient ID is obtained by accessing the task record from the task record ID, and the intervention content corresponding to the target intervention task is pushed to the target patient.
[0093] Figure 2 Schematic diagram of the structure of an intervention task scheduling device according to an embodiment of the present application. Figure 2 As shown, it includes:
[0094] A first data acquisition unit, used to acquire the intervention frequency and intervention time of the target intervention task;
[0095] An expression generation unit, used to generate an execution frequency constraint expression for executing the target intervention task based on the intervention frequency and intervention time;
[0096] A second data acquisition unit, used to acquire the execution start time and execution end time of the target intervention task;
[0097] A roulette generation unit, configured to generate a time roulette for scheduling the target intervention task based on the execution frequency constraint expression, the execution start time, and the execution end time;
[0098] A task scheduling unit is used to schedule the target intervention task for execution based on the time wheel.
[0099] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described module can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.
[0100] Optionally, the method further includes: generating the target intervention task according to the trigger condition description of the target intervention task and the indicator code of the target patient.
[0101] Exemplarily, the generating of the target intervention task according to the trigger condition description of the target intervention task and the indicator code of the target patient includes the following steps:
[0102] S201, acquiring the collected target patient data;
[0103] In this embodiment, the patient data is collected based on a set data collection engine and uniquely corresponds to a target patient. The data collection engine is set on an electronic terminal used by the target patient.
[0104] Optionally, the method further comprises:
[0105] Get the configured questionnaire push trigger logic;
[0106] In response to the initial user data submitted by the target patient matching the questionnaire push trigger logic, a collection questionnaire is pushed to the target patient to collect the target patient data of the target patient through the collection questionnaire.
[0107] Here, it should be noted that the questionnaire push trigger logic includes, for example, a combination relationship of multiple set indicators and a set collection time. When the initial user data meets the combination relationship, the collection questionnaire is pushed to the user according to the set collection time.
[0108] In this embodiment, specific indicators are determined according to application scenarios, and the combination relationship can be configured by, for example, and or.
[0109] In this embodiment, the format of the initial user data is not limited.
[0110] In this embodiment, the collection questionnaire can be directly displayed on the electronic terminal, and the user only needs to fill in the relevant patient data.
[0111] In this embodiment, the type of the target patient data is not limited, for example, it may be physiological data, exercise data, sleep data, diet data, psychological data, medication data and behavioral data;
[0112] For example, the physiological data may be heart rate, blood pressure, blood sugar, respiratory rate, body temperature or respiratory oxygen content;
[0113] The exercise data may include number of steps, exercise distance, exercise duration, activity intensity (such as mild, moderate, and high), calorie consumption, and exercise type (such as walking, running, swimming, and yoga);
[0114] The sleep data may include sleep duration (such as the time interval between falling asleep and waking up), sleep quality (such as deep sleep, light sleep, rapid movement sleep, etc.), sleep cycle, number of awakenings, and sleep breathing conditions (such as sleep breathing frequency, snoring, etc.);
[0115] The dietary data may include food types (such as grains, vegetables, fruits, meat, fish, dairy products, beans, nuts, etc.), food intake nutrients (such as calories, protein, fat, carbohydrates, fiber, vitamins, minerals, etc.), eating frequency, and eating habits (such as whether to eat breakfast, whether to eat out often, whether to have dietary preferences, etc.);
[0116] The psychological data may be a psychological assessment scale (such as depression symptoms, anxiety level, stress level, etc.), an emotional record (such as happiness, sadness, anxiety, tension, etc.);
[0117] The medication data may include the name of the drug, dosage (such as the number of tablets taken, the volume of liquid medicine, the dosage of injection, etc.), frequency of medication (such as three times a day, once a week, etc.), time of medication (such as before meals in the morning, before bedtime, etc.), route of administration (such as oral, topical, injection, etc.), duration of medication, and adverse reactions (such as allergies, indigestion, skin itching, etc.);
[0118] The behavior data may be smoking or drinking.
[0119] Here, it should be noted that the initial user data can be of the same type as the target patient data. To this end, a collection name and a collection time can be set in the collection questionnaire; the collection name can be "your fertility status", "have you taken opioids recently", "have you drunk alcohol today", etc.
[0120] S202, parsing the target patient data to generate an indicator code for the target patient;
[0121] In this embodiment, the rule of the indicator coding is determined according to the application scenario, and no uniqueness is limited. For example, in one scenario, the collection name in the collection questionnaire is "Whether to drink alcohol today", and the corresponding indicator code can be "A1.342".
[0122] S203, obtaining a configured intervention rule, wherein the intervention rule is configured with an association relationship between a target intervention task trigger condition ID and an intervention content ID;
[0123] In this embodiment, the target intervention task trigger condition includes a combination relationship of multiple indicators, such as and, or. Since there may be multiple target intervention task trigger conditions, in this application, different target intervention task trigger conditions are distinguished by the target intervention task trigger condition ID.
[0124] Similarly, intervention content refers to intervention measures for target patients, such as drug intervention, food intervention, video intervention, audio intervention, questionnaire intervention, popular science knowledge intervention, etc. In order to distinguish different intervention contents, an intervention content ID is set for each intervention content.
[0125] In this embodiment, the intervention rules may be directly stored in a relational database, for example, for easy access.
[0126] S204, based on the target intervention task trigger condition ID, obtaining a target intervention task trigger condition description, wherein the target intervention task trigger condition description is used to describe a logical rule of an indicator code that satisfies task triggering;
[0127] In this embodiment, the target intervention task triggering condition is described so that the target intervention task triggering condition can be recognized by a machine, so as to realize the automatic execution of subsequent steps without human intervention.
[0128] Specifically, the form of the target intervention task trigger condition description is not limited to uniqueness, for example, it can be implemented based on JS or Groove.
[0129] S205. In response to the indicator code matching the target intervention task trigger description, generate a target intervention task based on the intervention content ID to push the intervention content corresponding to the intervention content ID to the electronic terminal by executing the target intervention task.
[0130] Optionally, before step S204, the method may further include:
[0131] According to the target intervention task trigger condition ID, obtain the target intervention task trigger condition;
[0132] Based on the set description template, the target intervention task trigger condition is converted into a target intervention task trigger condition description.
[0133] Optionally, the description template defines an indicator name field, an indicator code field, and a logical relationship field;
[0134] Correspondingly, the target intervention task trigger condition is converted into a target intervention task trigger condition description based on the set description template, including:
[0135] Parsing the triggering conditions of the target intervention task to obtain the indicator name, indicator code, and logical relationship therefrom;
[0136] The indicator name, indicator code, and logical relationship are respectively filled into the indicator name field, indicator code field, and logical relationship field in the description template to obtain the trigger condition description of the target intervention task.
[0137] In this embodiment, in the set description template, if there are multiple target intervention task description conditions, the description template can be set to a nested structure, so that flexible combination relationship configuration can be performed between different target intervention task trigger condition descriptions, so as to dynamically realize dynamic adjustment and flexible configuration of intervention rules.
[0138] In addition to the indicator name field, indicator code field, logical relationship field, etc., the set description template can also include the type field of target patient data, etc. To this end, the structured processing of the intervention rules is achieved, which is convenient for machine recognition and reading for execution.
[0139] Optionally, the step of filling the indicator name, indicator code, and logical relationship into the indicator name field, indicator code field, and logical relationship field in the description template, respectively, to obtain the target intervention task trigger condition description includes:
[0140] The target intervention task trigger condition ID is used as the key in the key-value pair, and the indicator name, indicator code, and logical relationship are respectively filled into the indicator name field, indicator code field, and logical relationship field in the description template as the values in the key-value pair, and the target intervention task trigger condition description is expressed by the key-value pair.
[0141] For example, when the trigger condition description of the target intervention task is expressed in a key-value pair, it may be in the following structure:
[0142] {"rules":[{"rules":[{"values":[],"resType":"text","operator":"notNull","indicatorsCode":"*****","indicatorsName":"*****","indicatorsGroupType":1}],"combinator":"and"}],"combinator":"and"}
[0143] Where rules represents intervention rules, resType represents the type field of target patient data, operator represents the logical relationship field, indicatorsCode represents the indicator code field, indicatorsName represents the indicator name field, and [] represents a nesting symbol.
[0144] In this embodiment, based on the above structure, a structured description of the triggering conditions of the target intervention task is implemented, and at the same time, the complexity of the description is reduced, with strong recognizability and readability.
[0145] In this embodiment, in a specific implementation, the key-value pair may be saved in the form of a JSON string.
[0146] In this embodiment, since the target patient data has different types, such as text and numerical types, the target intervention task triggering conditions will also have corresponding different logical relationships. Therefore, a logical relationship dictionary mapping is set, in which the mapping relationship between different types of target patient data and logical relationships is defined. The types include ext, number, datetime, date, time, etc. The logical relationship is represented by operator. The mapping relationship between the target patient data and the logical relationship is as follows:
[0147] datetime:eq,neq,lt,lte,gt,gte,between,notNull,nothing
[0148] date:eq,neq,lt,lte,gt,gte,between,notNull,nothing
[0149] time:eq,neq,lt,lte,gt,gte,between,notNull,nothing
[0150] number:eq,neq,lt,lte,gt,gte,between,notNull,nothing
[0151] text:eq,neq,contains,doesNotContain,notNull,nothing
[0152] eq means "equal to"
[0153] neq means "not equal to"
[0154] lt means "less than"
[0155] lte means "less than or equal to"
[0156] gt means "greater than"
[0157] gte means "greater than or equal to"
[0158] Between means "between two values"
[0159] notNull means it cannot be empty
[0160] Nothing means empty.
[0161] In this embodiment, when generating the target intervention task trigger condition description, the mapping dictionary is queried to quickly and accurately find the matching relationship between different types of target patient data and logical relationships, thereby improving the efficiency and accuracy of generating the target intervention task trigger condition description.
[0162] Optionally, parsing the target patient data to generate an indicator code for the target patient includes:
[0163] Get the set executable code;
[0164] The executable code is executed based on a script executor to parse the target patient data to generate an indicator code for the target patient.
[0165] In this embodiment, the automatic execution of the analysis is achieved based on the executable code, without the need for human intervention.
[0166] Optionally, the method further comprises:
[0167] Converting the target intervention task trigger condition description into executable code;
[0168] The executable code is executed based on the script executor to compare the executable code with the value of the indicator code of the target patient to determine whether the indicator code matches the target intervention task trigger description.
[0169] Exemplarily, the executable code converted from the trigger condition description of the target intervention task of the above structure is as follows:
[0170]
[0171]
[0172] For example, if there is a target intervention task trigger condition:
[0173] {"rules":[{"rules":[{"values":[],"resType":"text","operator":"notNull","indicatorsCode":"A1.342","indicatorsName":"Did you drink alcohol today","indicatorsGroupType":1}],"combinator":"and"}],"combinator":"and"}
[0174] The converted executable code is as follows:
[0175]
[0176] A1.342 represents the code of the indicator "Did you drink alcohol today?". The meaning of this code is: if the value of the indicator "Did you drink alcohol today?" is "yes", return true; if the value is "no", return false (this depends on what the user fills in the questionnaire).
[0177] In this embodiment, converting the target intervention task trigger condition description into executable code includes: extracting target patient data and indicator code from the target intervention task trigger condition description based on a set conversion function, and adding an executable function to generate executable code.
[0178] Optionally, the method further comprises:
[0179] For the target patients, a task queue is established;
[0180] The target intervention task is stored in the task queue.
[0181] In the above embodiment, the intervention content may be, for example:
[0182] For example, the drug target intervention task includes drug name (e.g., doglitin tablets), route of administration (e.g., oral), drug dosage (e.g., tablets), dosage (e.g., 1 tablet each time), frequency of use (e.g., 3 times a day), and time of use (e.g., 10:35, 10:45, 10:55);
[0183] The food target intervention task includes the food name (such as herbal dietary fiber powder), consumption method (such as preparation), food dosage (such as 10 grams each time), and consumption time (such as 9:00);
[0184] The video target intervention task includes file name (such as Li Xian HIIT fat burning challenge), file type (such as video), intervention frequency (such as 3 times a day), and intervention time (such as 11:00, 15:00, 18:00);
[0185] The audio target intervention task includes a file name (such as a 35-minute non-jumping 5,000-step weight loss and fat burning walking training), a file type (such as audio), an intervention frequency (such as once a day), and an intervention time (such as 06:00).
[0186] Figure 3A schematic block diagram of an electronic device 300 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.
[0187] The electronic device 300 includes a computing unit 301, which can perform various appropriate actions and processes according to a computer program stored in a ROM 302 or a computer program loaded from a storage unit 308 into a RAM 303. In the RAM 303, various programs and data required for the operation of the electronic device 300 can also be stored. The computing unit 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An I / O interface 305 is also connected to the bus 304.
[0188] A number of components in the electronic device 300 are connected to the I / O interface 305, including: an input unit 306, such as a keyboard, a mouse, etc.; an output unit 307, such as various types of displays, speakers, etc.; a storage unit 308, such as a disk, an optical disk, etc.; and a communication unit 309, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 309 allows the electronic device 300 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.
[0189] The computing unit 301 may be a variety of general and / or special processing engines with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 301 performs the various methods and processes described above, such as the intervention task scheduling method. For example, in some embodiments, the intervention task scheduling method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 308. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 300 via ROM 302 and / or a communication unit 309. When the computer program is loaded into RAM 303 and executed by the computing unit 301, one or more steps of the intervention task scheduling method described above may be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to perform the intervention task scheduling method in any other appropriate manner (e.g., by means of firmware).
[0190] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.
[0191] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.
[0192] In the context of the present disclosure, a readable storage medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A readable storage medium may be a machine-readable signal medium or a machine-readable storage medium. A readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. More specific examples of readable storage media may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
[0193] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).
[0194] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communications network). Examples of communications networks include: a local area network (LAN), a wide area network (WAN), and the Internet.
[0195] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.
[0196] It should be understood that the above-mentioned various forms of processes can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of this disclosure can be achieved, and this document is not limited here.
[0197] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.
Claims
1. A method for scheduling intervention tasks, characterized in that: include: Obtain the intervention frequency and intervention time of the target intervention task; Based on the intervention frequency and intervention time, generating an execution frequency constraint expression for executing the target intervention task; Obtaining the execution start time and execution end time of the target intervention task; Based on the execution frequency constraint expression, the execution start time, and the execution end time, a time wheel for scheduling the target intervention task is generated; Based on the time wheel, the target intervention task is scheduled for execution.
2. The method according to claim 1, characterized in that The step of generating an execution frequency constraint expression for executing the target intervention task based on the intervention frequency and intervention time includes: The intervention frequency and intervention time are filled into the time domain to generate a string expression for executing the target intervention task, and the string expression is used as the execution frequency constraint expression.
3. The method according to claim 2, characterized in that The step of filling the intervention frequency and intervention time into the time domain sequence to generate a character string expression for executing the target intervention task includes: Parsing the time domain sequence to determine an intervention frequency setting domain and an intervention time setting domain in the time domain sequence; The intervention frequency and intervention time are filled into the intervention frequency setting field and the intervention time setting field respectively to generate a character string expression for executing the target intervention task.
4. The method according to any one of claims 1 to 3, characterized in that: The method further comprises: Obtain the task record ID corresponding to the target intervention task and add it to the message queue; Based on the time wheel, scheduling the target intervention task for execution includes: based on the time wheel, obtaining the task record ID from the message queue to execute the target intervention task corresponding to the task record ID.
5. The method according to claim 4, characterized in that The method further comprises: The task record ID is generated according to the target intervention task ID and the intervention content ID to be accessed when executing the target intervention task.
6. The method according to claim 1, characterized in that The step of scheduling the target intervention task for execution based on the time wheel includes: Generate a scheduling task package based on the target intervention task ID; Based on the time wheel, the corresponding target intervention task is searched in the task queue according to the scheduling task package, and the business is packaged and sent to the front end for execution.
7. The method according to claim 6, characterized in that The method further comprises: A response message for the execution of the target intervention task is generated, wherein the response message includes the target intervention task ID and a push target of the target intervention task.
8. The method according to claim 1, characterized in that The method further includes: generating the target intervention task according to the trigger condition description of the target intervention task and the indicator code of the target patient.
9. An intervention task scheduling device, characterized in that: include: A first data acquisition unit, used to acquire the intervention frequency and intervention time of the target intervention task; An expression generation unit, used to generate an execution frequency constraint expression for executing the target intervention task based on the intervention frequency and intervention time; A second data acquisition unit, used to acquire the execution start time and execution end time of the target intervention task; A roulette generation unit, configured to generate a time roulette for scheduling the target intervention task based on the execution frequency constraint expression, the execution start time, and the execution end time; A task scheduling unit is used to schedule the target intervention task for execution based on the time wheel.
10. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 8.