A coordination system and method for intelligent appointment treatment of day chemotherapy

Abstract

The present invention discloses a coordination system and method for intelligent appointment treatment of day chemotherapy, which relates to the field of medical information technology, including: an information processing unit, which is used to obtain the medical information of the target patient, construct a comprehensive diagnosis and treatment information model including the patient's diagnosis and treatment parameters, and generate an initial diagnosis and treatment node sequence based on the comprehensive diagnosis and treatment information model; an optimization unit, which is used to receive the initial diagnosis and treatment node sequence from the information processing unit, adjust the priority of each node in the initial diagnosis and treatment node sequence according to a first influencing factor, and generate a diagnosis and treatment path after reordering; a management unit, which generates a day chemotherapy appointment strategy and follow-up plan for the target patient based on the diagnosis and treatment path sent by the optimization unit, and sends reminder content containing key appointment information through the patient terminal. The present invention optimizes the resource utilization and diagnosis and treatment path of day chemotherapy through a multi-dimensional priority comprehensive evaluation and dynamic adjustment mechanism, realizes intelligent appointment and real-time response, and improves treatment efficiency and patient experience.

Description

Technical Field

[0001] The present invention relates to the field of medical information technology, and in particular to a coordination system and method for intelligent appointment treatment of daytime chemotherapy. Background Art

[0002] In recent years, with the increasing incidence of tumors year by year, the day chemotherapy model has been widely used in medical institutions and has become an effective way to improve the utilization of medical resources and improve the patient's treatment experience. Day chemotherapy not only provides patients with a convenient and efficient treatment approach, avoids the high cost of hospitalization, but also optimizes the allocation of medical resources. However, the current day chemotherapy appointment system is mostly based on fixed cycles and simple manual rules, which makes it difficult to adapt to the complex differences in individual patients' conditions and dynamic changes during the treatment process. This traditional method lacks the ability to respond quickly when dealing with sudden changes in the condition or urgent treatment needs, which may not only reduce treatment efficiency, but also affect the patient's treatment effect and safety. In addition, existing technologies usually only consider the order of appointments and basic resource allocation, and fail to combine multi-dimensional factors such as patients' clinical indicators, treatment compliance, and resource utilization for comprehensive evaluation, resulting in a lack of scientificity and personalization in the diagnosis and treatment path.

[0003] To improve the above shortcomings, some studies have attempted to introduce intelligent systems to optimize the appointment management of day chemotherapy, including priority setting and resource scheduling optimization, but there are still significant limitations in practical applications. The current system mostly adopts a single-dimensional or simple hierarchical priority setting, fails to dynamically monitor the patient's condition and adjust the diagnosis and treatment priority accordingly, and is difficult to meet the needs of complex conditions. In addition, the existing intelligent solutions are mostly limited to basic rule matching and static sorting, lacking a comprehensive and dynamic evaluation mechanism, especially when resources are tight, and are prone to problems such as uneven resource utilization, long waiting time or appointment conflicts, affecting patient experience and treatment effects. Therefore, it has become a key direction for current technological development to realize comprehensive priority evaluation based on multidimensional factors in the day chemotherapy appointment system, and dynamically adjust the diagnosis and treatment path in combination with the patient's real-time status. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the present invention provides a coordination system and method for intelligent appointment treatment of day chemotherapy, which can solve the problems mentioned in the background technology.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: a coordination system for intelligent appointment treatment of day chemotherapy, comprising: an information processing unit, used to obtain the medical information of the target patient, construct a comprehensive diagnosis and treatment information model including the patient's diagnosis and treatment parameters, and generate an initial diagnosis and treatment node sequence based on the comprehensive diagnosis and treatment information model; and an optimization unit, used to receive the initial diagnosis and treatment node sequence from the information processing unit, adjust the priority of each node in the initial diagnosis and treatment node sequence according to a first influencing factor, and generate a diagnosis and treatment path after reordering, and send it to a management unit; a management unit, which generates a day chemotherapy appointment strategy and follow-up plan for the target patient based on the diagnosis and treatment path sent by the optimization unit, and sends a reminder content containing key appointment information through the patient terminal.

[0007] As a preferred solution of the coordination system for intelligent appointment treatment of day chemotherapy described in the present invention, the information processing unit includes a collection module, a construction module and a first generation module.

[0008] The acquisition module is used to obtain and pre-process the medical information of the target patient, and transmit the pre-processed medical information to the construction module; the medical information includes chemotherapy regimen information, previous chemotherapy records, basic patient information, and laboratory test results before chemotherapy.

[0009] The construction module is used to receive the pre-processed medical information, extract patient diagnosis and treatment parameters in the medical information, and construct a comprehensive diagnosis and treatment information model based on the patient diagnosis and treatment parameters; wherein the patient diagnosis and treatment parameters include a chemotherapy regimen parameter set, a patient status parameter set, and a treatment timing parameter set.

[0010] Constructing a comprehensive diagnosis and treatment information model based on the patient diagnosis and treatment parameters includes the following steps: combining the chemotherapy regimen parameter set, the patient status parameter set and the treatment timing parameter set to form a diagnosis and treatment parameter feature vector; establishing an association structure between the parameters in the diagnosis and treatment parameter feature vector; and constructing a comprehensive diagnosis and treatment information model based on the association structure and in combination with clinical standards and specifications.

[0011] The first generation module is used to generate an initial diagnosis and treatment node sequence based on the comprehensive diagnosis and treatment information model, specifically: analyzing the key time nodes in the comprehensive diagnosis and treatment information model; the key time nodes include a medication time node set, an inspection time node set and an evaluation time node set; based on the key time nodes, constructing an initial diagnosis and treatment node sequence.

[0012] As a preferred solution of the coordination system for intelligent appointment treatment of day chemotherapy described in the present invention, wherein: based on the key time nodes, an initial diagnosis and treatment node sequence is constructed, including the following steps: the medication time node set, the inspection time node set and the evaluation time node set are merged and sorted according to the time attribute to form an initial time sequence; each time node in the initial time sequence contains an operation type identifier and timestamp information; conflict detection and adjustment are performed on the initial time sequence to obtain an adjusted initial time sequence, specifically including: establishing a minimum time interval matrix between operation types; setting a first priority rule for conflict handling, which is medication time node, inspection time node, evaluation time node, etc. time nodes; in the initial time sequence, a conflict situation in which the time interval between adjacent time nodes is less than the value specified by the minimum time interval matrix is ​​identified. When a conflict is identified, based on the first priority rule, the low-priority time nodes are postponed until the minimum time interval requirement is met; if the postponed time node exceeds the available time range for day chemotherapy, it is adjusted to the next available date; the adjusted initial time sequence is marked according to the clinical standard specifications, specifically, a unique operation number is assigned to each time node, the expected duration of each time node is recorded, the preconditions and subsequent requirements of the operation are marked, and an initial diagnosis and treatment node sequence containing complete time information and operation attributes is generated.

[0013] As a preferred solution of the coordination system for intelligent appointment treatment of day chemotherapy described in the present invention, the optimization unit includes an adjustment module and a second generation module.

[0014] The adjustment module is used to receive the initial diagnosis and treatment node sequence from the first generation module, and adjust the priority of each node in the initial diagnosis and treatment node sequence according to the first influencing factor, specifically: determine the first influencing factor as a clinical priority factor set and an operational priority factor set; construct a multi-level fuzzy comprehensive evaluation system, including constructing a fuzzy relationship matrix, using a hierarchical analysis method to calculate the clinical priority factor weight vector and the operational priority factor weight vector, and using a fuzzy comprehensive evaluation operator to calculate the priority weight value of the node; assign a priority attribute to each node according to the priority weight value; the priority attribute includes a priority weight value, a priority level and a priority validity period; set and apply a second priority rule; the second priority rule includes a priority inheritance rule and a priority transfer rule, the priority inheritance rule is that for multiple nodes in the same treatment cycle, subsequent nodes inherit the priority weight value of the closest key node in time sequence, and determine the priority level and calculate the priority validity period; the priority transfer rule is that for associated diagnosis and treatment nodes in different treatment cycles, if the priority weight value of the source node has been calculated by a fuzzy comprehensive evaluation operator, then its associated nodes do not need to be recalculated using the fuzzy comprehensive evaluation operator, but the priority weight value of the associated node is determined based on the priority weight value of the source node and the clinical correlation coefficient.

[0015] The second generating module is used to reorder each node in the initial diagnosis and treatment node sequence after the priority is adjusted in the adjustment module to generate a diagnosis and treatment path, specifically: sorting the initial diagnosis and treatment node sequence after the priority is adjusted in descending order of priority level, descending order of priority weight value and ascending order of remaining time of priority validity period; according to the priority inheritance rules and priority transfer rules set in the adjustment module, on the basis of maintaining the inherent time sequence between nodes with inheritance relationship and transfer relationship, converting the sorted initial diagnosis and treatment node sequence into a diagnosis and treatment path.

[0016] As a preferred solution of the coordination system for intelligent appointment treatment of day chemotherapy described in the present invention, wherein: the management unit includes a third generation module and a reminder module; the third generation module generates a day chemotherapy appointment strategy and follow-up plan for the target patient based on the diagnosis and treatment pathway; the reminder module is used to send reminder content containing key appointment information through the patient terminal.

[0017] As a preferred solution of the coordination system for intelligent appointment treatment of day chemotherapy described in the present invention, it also includes: a system operation unit and a cloud interaction unit; the system operation unit is used to provide operation environment support and realize data exchange between the information processing unit, the optimization unit and the management unit; the system operation unit includes a power management module, a hardware monitoring module and a network communication module; the power management module is responsible for the power supply and power management of the system; the hardware monitoring module is used to monitor the hardware status of the system and send hardware status information to the network communication module; the network communication module is responsible for the network communication between the modules inside the system and between the system and external devices, receives the status information from the hardware monitoring module, and is responsible for the data transmission between all units.

[0018] As a preferred solution of the coordination system for intelligent appointment treatment of day chemotherapy described in the present invention, wherein: the cloud interaction unit is used to synchronize and back up the data of the information processing unit, optimization unit and management unit on the cloud, and supports remote operation; the cloud interaction unit includes a data synchronization module, a remote access module and a cloud backup module; the data synchronization module is responsible for real-time synchronization of local data with cloud data, receiving data from all other units, and exchanging data with the cloud; the remote access module is used to allow authorized users to remotely access the system through the cloud, receive remote access requests, and pass operation instructions to the corresponding unit; the cloud backup module is used to receive data from all units and send backup data to the cloud; the key appointment information includes appointment time, treatment preparation requirements and appointment adjustment information.

[0019] To further solve the above-mentioned technical problems, the present invention provides the following technical solutions: a coordination system for intelligent appointment treatment of day chemotherapy, comprising: an information processing unit obtains the medical information of the target patient, constructs a comprehensive diagnosis and treatment information model including the patient's diagnosis and treatment parameters, and generates an initial diagnosis and treatment node sequence based on the comprehensive diagnosis and treatment information model; an optimization unit receives the initial diagnosis and treatment node sequence from the information processing unit, adjusts the priority of each node in the initial diagnosis and treatment node sequence according to a first influencing factor, and generates a diagnosis and treatment path after re-sorting, and sends it to a management unit; the management unit generates a day chemotherapy appointment strategy and follow-up plan for the target patient based on the diagnosis and treatment path sent by the optimization unit, and sends a reminder content containing key appointment information through the patient terminal.

[0020] A computer device includes a memory and a processor, wherein the memory stores a computer program, and wherein the processor implements the steps of the coordination system for intelligent appointment treatment of day chemotherapy as described above when executing the computer program.

[0021] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of the coordination system for intelligent appointment treatment of day chemotherapy as described above are implemented.

[0022] The beneficial effects of the present invention are as follows: First, the information processing unit integrates the patient's diagnosis and treatment parameters, constructs a dynamic diagnosis and treatment information model, and generates an initial diagnosis and treatment node sequence, laying a data foundation for the accurate setting of priorities; secondly, the optimization unit adopts a multi-level fuzzy evaluation method, combined with the clinical priority factors of the patient's condition and the operational priority factors of resource utilization, to dynamically adjust and sort the priorities of the diagnosis and treatment nodes, effectively improving the utilization rate of resources and the rationality of the diagnosis and treatment path; finally, the management unit formulates personalized appointment strategies and follow-up plans based on the optimized diagnosis and treatment path, and reminds patients through the terminal, enhancing patient compliance and experience. The system architecture and evaluation mechanism of the present invention significantly improve the efficiency and safety of the day chemotherapy process, solve the problems of insufficient response and uneven resource scheduling in the prior art, and provide scientific support for dynamic coordination during chemotherapy. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0024] Figure 1 An overall flow chart of a coordination system for intelligent appointment treatment of day chemotherapy provided by an embodiment of the present invention;

[0025] Figure 2 A schematic diagram of the structure of a coordination system for intelligent appointment treatment of day chemotherapy provided by one embodiment of the present invention;

[0026] Figure 3 A diagram of computer equipment for the coordination system of the day chemotherapy intelligent appointment treatment of the present invention. DETAILED DESCRIPTION

[0027] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0028] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0029] Example 1, reference Figure 1 and Figure 2 , which is an embodiment of the present invention, provides a coordination system for intelligent appointment treatment of day chemotherapy.

[0030] In related technologies, there is a lack of comprehensive integration and dynamic updating of patient medical information, and usually only relies on single-dimensional or simple hierarchical priority settings, making it difficult to respond to changes in patients' conditions in real time. In addition, most existing solutions are based on static rule matching and sorting, lacking a dynamic evaluation mechanism for multi-dimensional factors, making it difficult for the system to flexibly adjust diagnosis and treatment priorities and paths when the condition is complex or resources are tight, resulting in inefficient resource utilization, long waiting times, and appointment conflicts, which directly affect patients' treatment effects and experience.

[0031] This application provides a method that can effectively solve the above-mentioned problems. Next, multiple embodiments will be combined to explain in detail how to implement the coordination system of the day chemotherapy intelligent appointment treatment;

[0032] Figure 1 The schematic diagram of the structure of a coordination system for intelligent appointment treatment of day chemotherapy is shown, including:

[0033] The information processing unit 100 , the optimization unit 200 , the management unit 300 , the system operation unit 400 , and the cloud interaction unit 500 .

[0034] Furthermore, the information processing unit 100 obtains medical information of the target patient, constructs a comprehensive diagnosis and treatment information model including the patient's diagnosis and treatment parameters, and generates an initial diagnosis and treatment node sequence based on the comprehensive diagnosis and treatment information model.

[0035] Specifically, the information processing unit 100 is composed of a collection module 101 , a construction module 102 and a first generation module 103 .

[0036] The acquisition module 101 acquires and preprocesses the medical information of the target patient, and transmits the preprocessed medical information to the construction module 102 .

[0037] The acquisition module 101 establishes a connection with various hospital information systems, including the hospital information system (HIS), the electronic medical record system (EMR) and the laboratory information system (LIS), through the network communication module 403 in the system operation unit 400, so as to obtain medical information. The medical information includes chemotherapy regimen information (including the type of chemotherapy drugs, dosage, administration method and treatment cycle), previous chemotherapy records (including treatment response, adverse reactions and complications records), patient basic information (including age, weight, body surface area, tumor stage and underlying diseases), and laboratory test results required before chemotherapy (including blood routine, liver and kidney function and coagulation function indicators). The acquired medical information is synchronized between local data and the cloud in real time through the data synchronization module 501 in the cloud interaction unit 500, and is backed up regularly by the cloud backup module 503.

[0038] With the support of the system operation unit 400, the acquisition module 101 pre-processes the acquired data (i.e., the medical information of the target patient), including data cleaning, format unification, and data completion. Focus on recording the chemotherapy cycle date, treatment time, patient arrival and departure time, and other timing information of day chemotherapy, as well as appointment fulfillment. These pre-processed data are transmitted to the construction module 102 via the network communication module 403, and data synchronization and backup are achieved through the cloud interaction unit 500, supporting authorized users to view and analyze through the remote access module 502. In addition, the acquisition module 101 performs data verification with the support of the hardware monitoring module 402 in the system operation unit 400 to ensure the accuracy and reliability of the data, and provide a data basis for subsequent intelligent appointment decisions.

[0039] The construction module 102 receives the pre-processed medical information sent from the acquisition module 101, extracts the patient diagnosis and treatment parameters in the medical information, and constructs a comprehensive diagnosis and treatment information model based on the patient diagnosis and treatment parameters.

[0040] It should be noted that the patient diagnosis and treatment parameters include a chemotherapy regimen parameter set, a patient status parameter set, and a treatment timing parameter set. Among them, the chemotherapy regimen parameter set includes a drug dose vector, a route of administration, a drug type set, and a number of treatment cycles. The drug dose vector records the specific dosage of each drug. The route of administration records the method of administration used. The drug type set records the generic names of all drugs used. The number of treatment cycles records the current treatment cycle.

[0041] Chemotherapy regimen parameter set It is expressed as:

[0042] ;

[0043] Among them, t is the time node (unit: day); , is an m-dimensional drug dosage vector, where m is the number of drug types and each component represents the dosage of the corresponding drug (unit: mg / m²); , is an n-dimensional binary vector of drug administration routes, n is the number of optional drug administration routes, 1 indicates that the route is adopted, and 0 indicates that it is not adopted; It is a collection of drug types, including the generic names of all drugs currently in use; is the current treatment cycle number.

[0044] The patient status parameter set adopts an adaptive evaluation method based on the importance of clinical indicators. By calculating the coefficient of variation of clinical indicators, the degree of deviation from the reference value and the standard deviation, the weight coefficient of each clinical indicator is determined, and then integrated to form a quantitative expression of the patient status.

[0045] Patient status parameter set It is expressed as:

[0046] ;

[0047] Among them, L is the total number of clinical indicators; is the standardized value of the ith clinical indicator at time t; is the weight coefficient of the ith clinical indicator, calculated as follows:

[0048] ;

[0049] in, is the coefficient of variation of the ith clinical indicator; is the median of the reference range of the ith clinical indicator; is the standard deviation of the ith clinical indicator; is the weight adjustment coefficient and satisfies .

[0050] The treatment time series parameter set includes the treatment interval days, the single treatment time and the current cycle number. The treatment interval days records the interval time between two adjacent treatments. The single treatment time records the actual duration of each treatment. The current cycle number records the number of cycles that the treatment has been carried out.

[0051] Treatment timing parameter set It is expressed as:

[0052] ;

[0053] in, is the number of days between treatments; The actual time of a single treatment (unit: hours); The current cycle number.

[0054] Building a comprehensive diagnosis and treatment information model based on patient diagnosis and treatment parameters includes the following steps:

[0055] First, the chemotherapy regimen parameters were set , patient status parameter set and treatment timing parameter sets Combine to form the diagnostic parameter feature vector :

[0056] ;

[0057] Then, the association structure between the parameters in the diagnosis and treatment parameter feature vector is established, which is expressed as:

[0058] ;

[0059] in, is the parameter association function; is the parameter association structure matrix.

[0060] Finally, based on the association structure and combined with clinical standard specifications, a comprehensive diagnosis and treatment information model is constructed.

[0061] Specific, comprehensive diagnosis and treatment information model It is expressed as:

[0062] ;

[0063] in, is the information integration function; It is a set of clinical standards and specifications, which is a multi-dimensional medical standard system, including internationally accepted chemotherapy dosage standards, WHO / CTCAE adverse reaction grading standards, RECIST solid tumor efficacy evaluation standards, clinical test index reference intervals, drug interaction rule base and treatment pathway guidelines based on evidence-based medicine, which are used to standardize evaluation and guide clinical treatment decisions.

[0064] Preferably, the construction module 102 proposes a diagnosis and treatment information modeling method based on multi-dimensional parameters, and realizes the quantitative expression of key parameters in the patient treatment process by establishing a clinical indicator evaluation system with dynamic weights. This module uses a parameter association structure matrix to characterize the mutual influence between indicators of each dimension, improves the model's ability to express complex clinical scenarios, and provides a mathematical basis for intelligent appointment decision-making.

[0065] The first generation module 103 generates an initial diagnosis and treatment node sequence based on the comprehensive diagnosis and treatment information model, specifically including the following steps:

[0066] First, analyze the key time nodes in the comprehensive diagnosis and treatment information model. Among them, the key time nodes include the medication time node set, the inspection time node set and the evaluation time node set. The medication time node set is determined based on the chemotherapy regimen parameter set, including the first medication time, the start medication time of each cycle and the last medication time. The first medication time is the time node for the start of treatment, the start medication time of each cycle is the time node for the start of each treatment cycle, and the last medication time is the time node for the last medication.

[0067] Since the prior art only arranges the inspection time according to a fixed period and cannot dynamically adjust the inspection frequency according to the patient's status, the present invention introduces special inspection time nodes to improve the timeliness of monitoring the patient's abnormal condition. The inspection time node set is determined based on the patient's status parameter set, including regular inspection time nodes and special inspection time nodes.

[0068] Among them, the routine inspection time node is the inspection time that is carried out periodically, and the special inspection time node is the inspection time that is added additionally according to the change of the patient's status. The special inspection time node is dynamically generated based on the patient status parameter set, including: comparing each physiological indicator in the patient status parameter set with its standard reference range, and generating a targeted inspection time node when the physiological indicator deviates from the standard reference range; among them, the standard reference range includes an upper limit and a lower limit, which are used to determine whether the indicator is abnormal.

[0069] Analyze the patient status parameter set: when multiple abnormal indicators appear at the same time, determine the inspection item combination and set the corresponding time nodes according to clinical specifications; when a single indicator shows continuous abnormality for three consecutive times, increase the inspection frequency of the indicator; when the patient status parameters show reduced tolerance to the treatment plan, increase the inspection time nodes of related organ functions.

[0070] A priority mechanism is used to generate an inspection time series: when multiple indicators in the patient status parameter set need to be inspected at the same time, inspection items related to vital signs are given priority; the time schedule for subsequent key inspection items is planned based on the distribution of abnormal indicators recorded in the patient status parameter set.

[0071] The evaluation time node set is determined based on the treatment timing parameter set, including the efficacy evaluation time node and the adverse reaction evaluation time node. The efficacy evaluation time node is the time node for evaluating the treatment effect, and the adverse reaction evaluation time node is the time node for evaluating the adverse reaction of the patient.

[0072] Secondly, based on the key time nodes, the initial diagnosis and treatment node sequence is constructed, specifically:

[0073] 1. Combine the medication time node set, the inspection time node set, and the evaluation time node set, and sort them by time attribute to form an initial time series. Each time node in the initial time series contains an operation type identifier and timestamp information.

[0074] 2. Perform conflict detection and adjustment on the initial time series to obtain the adjusted initial time series, specifically including: establishing a minimum time interval matrix between operation types. It should be noted that the minimum time interval matrix defines the minimum safety interval time required between different operation types. Operation types include medication operation types, inspection operation types, and evaluation operation types. Among them, medication operation types include first medication, cycle start medication, continuous medication during the cycle, and last medication; inspection operation types include routine inspections and special inspections, among which routine inspections include blood routine tests, liver and kidney function tests, and coagulation function tests, and special inspections include single indicator abnormality tests, multi-indicator correlation tests, and organ function tests; evaluation operation types include efficacy evaluation and adverse reaction evaluation.

[0075] Set the first priority rule for conflict handling, which is medication time node, inspection time node, and evaluation time node in sequence; identify the conflict situation in the initial time sequence where the time interval between adjacent time nodes is less than the value specified by the minimum time interval matrix. When a conflict is identified, based on the first priority rule, postpone the low-priority time node until the minimum time interval requirement is met; if the postponed time node exceeds the available time range for day chemotherapy, adjust it to the next available date. It should be noted that the available time range for day chemotherapy refers to the time interval during each working day when the medical institution can perform day chemotherapy, including:

[0076] Daily start time: opening time of the day chemotherapy center of the medical institution;

[0077] Daily end time: the latest time to ensure that the patient completes all treatment operations and leaves the medical institution on the same day;

[0078] Weekdays: Day chemotherapy service hours set by the medical institution, usually Monday to Friday;

[0079] Reserved time: The reserved buffer time is taken into account for handling emergencies.

[0080] In addition, in this embodiment, the operation type and the time node form a "one-to-many" subordinate relationship, in which the operation type as the basic classification system defines basic attributes and rules (such as priority, minimum interval requirements, etc.), and the time node is a specific instance of these operation types. Each time node must and can only correspond to one operation type, inherit all the attributes of the type, and also contain specific execution time information. For example, the medication operation type of "cycle start medication" may correspond to multiple specific medication time nodes in the treatment process, and these time nodes will inherit the highest priority characteristics of the medication operation type. When the system is actually running, although the objects directly processed are specific time nodes, these processes are all based on the attributes and rules of the operation type to which they belong, thereby ensuring the standardization of classification and achieving flexibility in time scheduling.

[0081] 3. Label the adjusted initial time series according to clinical standard specifications, including:

[0082] Assign a unique operation number to each time node;

[0083] Record the estimated duration of each time point;

[0084] Mark the preconditions and follow-up requirements of the operation;

[0085] Generate an initial diagnosis and treatment node sequence containing complete time information and operation attributes.

[0086] After generating the initial diagnosis and treatment node, the first generation module 103 sends it to the adjustment module 201 in the optimization unit 200 .

[0087] Preferably, the first generation module 103 designs a time node generation algorithm based on clinical rules, and effectively solves the problem that the traditional fixed-cycle appointment plan is insufficiently responsive to changes in patient status by introducing dynamic inspection time nodes and operation interval constraint matrices. The operation type affiliation system established by this module enables the time node arrangement to comply with clinical norms while maintaining sufficient flexibility, significantly improving the executability of the day chemotherapy intelligent appointment plan.

[0088] Furthermore, the optimization unit 200 adjusts the priority of each node in the initial diagnosis and treatment node sequence according to the first influencing factor, and generates a diagnosis and treatment path after reordering. The optimization unit 200 is composed of an adjustment module 201 and a second generation module 202.

[0089] Specifically, the first influencing factors include real-time resource status and changes in the patient's condition.

[0090] Specifically, the adjustment module 201 receives the initial diagnosis and treatment node sequence sent from the first generation module 103, and adjusts the priority of each node in the initial diagnosis and treatment node sequence according to the first influencing factor, specifically:

[0091] Step 1: Determine the first influencing factor, including the clinical priority factor set and the operational priority factor set. The clinical priority factor set includes the urgency of treatment, the risk level of adverse reactions, the degree of abnormality of clinical indicators, and the treatment compliance score, and the operational priority factor set includes the degree of advance appointment, historical performance, resource utilization, and waiting time.

[0092] It should be noted that the clinical priority factors are concentrated, the urgency of treatment is based on the patient's disease progression and the treatment window, and the value range is 1 to 5; the risk level of adverse reactions is predicted based on previous adverse reaction records and the current patient status, and the value range is 0 to 3; the degree of abnormality of clinical indicators is calculated by quantifying the deviation of key medical indicators such as vital signs, laboratory test indicators, and imaging examination indicators, and the range is 0 to 1; the treatment compliance score is based on the historical treatment record assessment, and the value range is 0 to 100. The operational priority factors are concentrated, and the appointment advance degree ranges from 0 to 30 days; the historical fulfillment is calculated by the ratio of the actual number of fulfillments to the total number of appointments; the resource utilization rate is calculated by the ratio of the actual resource usage time to the total resource time; the waiting time is recorded in hours.

[0093] Step 2: Construct a multi-level fuzzy comprehensive evaluation system, including: construct a fuzzy relationship matrix, where the rows of the matrix represent eight evaluation factors: treatment urgency, adverse reaction risk level, clinical indicator abnormality, treatment compliance score, appointment advance degree, historical fulfillment, resource utilization and waiting time, and the columns of the matrix represent four evaluation levels: emergency, priority, routine and elective. The matrix elements range from 0 to 1, indicating the degree of membership of each factor to the evaluation level. The hierarchical analysis method is used to calculate the weight vector of clinical priority factors and the weight vector of operational priority factors, and the sum of all weights is 1.

[0094] Step 3: Use the fuzzy comprehensive evaluation operator to calculate the priority weight value of the node, where the evaluation level quantization value vector is set as 1.0, 0.75, 0.5, and 0.25, with 1.0 corresponding to the emergency level, 0.75 corresponding to the priority level, 0.5 corresponding to the regular level, and 0.25 corresponding to the elective level.

[0095] Step 4: Assign priority attributes to each node based on the calculated priority weight value, including the priority weight value (calculated in step 3), priority level, and priority validity period.

[0096] Among them, the priority level is divided into the following according to the priority weight value: when the weight value is between 0.8 and 1.0, it is the emergency level; when it is between 0.6 and 0.8, it is the priority level; when it is between 0.4 and 0.6, it is the routine level; when it is between 0 and 0.4, it is the elective level;

[0097] Priority validity period, through the formula Calculated, where T base is the basic validity period, P k is the priority weight value, T max is the maximum validity period; k is the node; when the calculated priority validity period is exceeded, steps 1 to 4 need to be re-executed to update the priority attribute of the node;

[0098] Step 5: Set and apply the second priority rule. Set the priority inheritance rule and priority transfer rule. Priority inheritance rule: For multiple nodes in the same treatment cycle, the diagnosis and treatment nodes that are necessary for treatment and have a decisive impact on the treatment effect are defined as key nodes. Subsequent nodes inherit the priority weight value of the closest key node in time sequence, and determine the priority level and calculate the priority validity period accordingly. For example, for a chemotherapy treatment cycle, it includes nodes such as pre-chemotherapy evaluation, drug configuration, establishment of infusion access, chemotherapy drug administration, and post-treatment observation, among which pre-chemotherapy evaluation and chemotherapy drug administration are key nodes. When the priority of the pre-chemotherapy evaluation is emergency level (priority weight value is 0.9), the two subsequent nodes of drug configuration and establishment of infusion access will inherit the priority weight value, and they are determined to be emergency level accordingly.

[0099] Priority transfer rules: For the associated diagnosis and treatment nodes of different treatment cycles, if the priority weight value of the source node has been calculated by the fuzzy comprehensive evaluation operator, then its associated nodes do not need to be recalculated using the fuzzy comprehensive evaluation operator, but the priority transfer ratio is determined according to its clinical relevance. The priority weight value of the associated node is determined by the product of the priority weight value of the source node and the clinical relevance coefficient, where the value range of the clinical relevance coefficient is (0, 1). After determining the priority weight value of the associated node, its priority level is determined accordingly, and its priority validity period is calculated. For example, for related examinations that need to be completed before radiotherapy, such as the blood routine examination node, when the priority weight value of the radiotherapy implementation node (source node) is 0.8, and the clinical relevance coefficient with the blood routine examination is 0.9, the priority weight value of the blood routine examination node is calculated to be 0.72, and its priority level is determined accordingly, and its priority validity period is calculated.

[0100] It should be noted that the source node refers to the node that serves as the starting point of priority transfer among the associated nodes. For example, chemotherapy drug administration requires the completion of blood routine examination first, and chemotherapy drug administration and blood routine examination form associated nodes, among which chemotherapy drug administration is the main treatment node, and its priority is directly calculated by the fuzzy comprehensive evaluation operator. Blood routine examination is an auxiliary examination node serving chemotherapy drug administration. Chemotherapy drug administration is the source node, and its priority weight value will affect the priority weight value of blood routine examination.

[0101] The second generating module 202 is used to reorder the nodes in the initial diagnosis and treatment node sequence after the priority is adjusted in the adjusting module 201, and generate a diagnosis and treatment path, specifically:

[0102] Step 1: Establish a three-level sorting rule to sort the initial diagnosis and treatment node sequence after adjusting the priority level in descending order (emergency>priority>routine>elective), in descending order of priority weight value, and in ascending order of remaining time of priority validity period.

[0103] Step 2: According to the priority inheritance rule and priority transfer rule set in the adjustment module 201, on the basis of maintaining the inherent time sequence between nodes with inheritance relationship and transfer relationship, the sorted initial diagnosis and treatment node sequence is converted into a diagnosis and treatment path.

[0104] Preferably, the optimization unit 200 constructs a multi-level fuzzy comprehensive evaluation system, quantifies and integrates clinical and operational multi-dimensional indicators into priority weight values, and sets priority inheritance rules and priority transfer rules, thereby realizing intelligent adjustment of the priorities of multiple nodes in the same treatment cycle and nodes associated with different treatment cycles. This method not only avoids the subjectivity and uncertainty brought about by the traditional method of relying solely on manual experience judgment or simple rule sorting, but also can respond to changes in patient conditions and resource status in a timely manner through the dynamic update mechanism of priority attributes and the introduction of clinical correlation coefficients, optimize the sorting of diagnosis and treatment paths while ensuring the necessary clinical implementation order, thereby improving the scientificity and flexibility of medical resource scheduling.

[0105] Furthermore, the management unit 300 generates a day chemotherapy reservation strategy and a follow-up plan for the target patient based on the diagnosis and treatment pathway, and sends reminder content containing key reservation information through the patient terminal.

[0106] Specifically, the management unit 300 includes a third generating module 301 and a reminding module 302 .

[0107] The third generation module 301 generates a day chemotherapy appointment strategy and a follow-up plan for the target patient based on the diagnosis and treatment pathway, specifically:

[0108] Step 1: Based on the diagnosis and treatment pathway generated by the second generation module 202, a day chemotherapy reservation strategy is generated: according to the time information and operation attributes of each node in the diagnosis and treatment pathway, a specific reservation time period is allocated to each node, and a reservation list including the reservation date, reservation time and operation content is formed, which serves as a specific execution basis for the patient to receive various diagnosis and treatment operations of day chemotherapy;

[0109] Step 2: Set up a corresponding follow-up plan based on the diagnosis and treatment pathway: Based on the distribution of assessment time nodes, examination time nodes, and medication time nodes in the diagnosis and treatment pathway, formulate a corresponding follow-up schedule and follow-up content to ensure continuous monitoring and timely evaluation of the patient's treatment process.

[0110] The reminder module 302 is used to send reminder content containing key appointment information through the patient terminal. Among them, the key appointment information includes appointment time, treatment preparation requirements and appointment adjustment information. Specifically, the reminder module 302 establishes an information interaction interface with the patient terminal through the network communication module 403, and synchronizes data with the cloud interaction unit 500. According to the appointment strategy and follow-up plan generated by the third generation module 301, differentiated reminder frequencies and reminder methods are set, and the reminder content containing key appointment information is sent to the patient terminal, wherein the sending record of the reminder content is synchronized in the cloud through the data synchronization module 501, and backed up by the cloud backup module 503.

[0111] Furthermore, the system operation unit 400 is used to provide operating environment support and implement data exchange between the information processing unit 100, the optimization unit 200 and the management unit 300. The system operation unit 400 includes a power management module 401, a hardware monitoring module 402 and a network communication module 403.

[0112] Among them, the power management module 401 is responsible for the power supply and power management of the system; the hardware monitoring module 402 is used to monitor the system hardware status and send hardware status information to the network communication module 403; the network communication module 403 is responsible for the network communication between the modules inside the system and between the system and external devices, receives the status information from the hardware monitoring module 402, and is responsible for data transmission between all units.

[0113] Furthermore, the cloud interaction unit 500 is used to perform cloud synchronization and backup of data of the information processing unit 100 , the optimization unit 200 and the management unit 300 , and supports remote operation. The cloud interaction unit 500 includes a data synchronization module 501 , a remote access module 502 and a cloud backup module 503 .

[0114] Among them, the data synchronization module 501 is responsible for the real-time synchronization of local data and cloud data, receives data from all other units, and exchanges data with the cloud; the remote access module 502 is used to allow authorized users to remotely access the system through the cloud, receive remote access requests, and pass operation instructions to the corresponding unit; the cloud backup module 503 is used to receive data from all units and send backup data to the cloud.

[0115] In summary, the present invention realizes the intelligent coordination and management of day chemotherapy appointments by introducing information processing units, optimization units and management units, and has the following beneficial effects: first, the information processing unit integrates the patient's diagnosis and treatment parameters, constructs a dynamic diagnosis and treatment information model, and generates an initial diagnosis and treatment node sequence, laying a data foundation for the accurate setting of priorities; secondly, the optimization unit adopts a multi-level fuzzy evaluation method, combined with the clinical priority factors of the patient's condition and the operational priority factors of resource utilization, to dynamically adjust and sort the priorities of the diagnosis and treatment nodes, effectively improving the utilization rate of resources and the rationality of the diagnosis and treatment path; finally, the management unit formulates personalized appointment strategies and follow-up plans based on the optimized diagnosis and treatment path, and reminds patients through the terminal, enhancing patient compliance and experience. The system architecture and evaluation mechanism of the present invention significantly improve the efficiency and safety of the day chemotherapy process, solve the problems of insufficient response and uneven resource scheduling in the prior art, and provide scientific support for dynamic coordination during chemotherapy.

[0116] Example 2, reference Figure 1 and Figure 2 , which is an embodiment of the present invention, provides a coordination method for intelligent appointment treatment of day chemotherapy, comprising:

[0117] S1: The information processing unit 100 obtains medical information of a target patient, constructs a comprehensive diagnosis and treatment information model including diagnosis and treatment parameters of the patient, and generates an initial diagnosis and treatment node sequence based on the comprehensive diagnosis and treatment information model;

[0118] S2: The optimization unit 200 receives the initial diagnosis and treatment node sequence from the information processing unit 100, adjusts the priority of each node in the initial diagnosis and treatment node sequence according to the first influencing factor, generates a diagnosis and treatment path after reordering, and sends it to the management unit 300;

[0119] S3: The management unit 300 generates a day chemotherapy appointment strategy and a follow-up plan for the target patient based on the diagnosis and treatment pathway sent by the optimization unit 200, and sends a reminder content containing key appointment information through the patient terminal.

[0120] Example 3, reference Figure 3, is an embodiment of the present invention, which is different from the previous embodiment in that: if the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0121] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0122] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0123] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0124] Example 4 is an embodiment of the present invention, which provides a coordination system for intelligent appointment treatment of day chemotherapy. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0125] This experiment aims to verify the innovation and advantages of the coordination system for intelligent appointment treatment of day chemotherapy proposed in the present invention in terms of patient treatment path optimization, resource allocation efficiency, and patient waiting time. The present invention uses the patient's medical data and diagnosis and treatment parameters to generate an optimized treatment path, ultimately improving patient compliance and medical resource utilization. This experiment selected 60 day chemotherapy patients and divided them into two groups, "traditional appointment system" and "present invention", with 30 people in each group, and the test period was 8 weeks.

[0126] Test equipment and data collection: Record patient medical information through the collection module.

[0127] Data preprocessing and model building: After the system collects patient data, the data preprocessing module performs data cleaning and standardization to ensure accuracy. The building module builds a comprehensive diagnosis and treatment information model based on patient diagnosis and treatment parameters, including chemotherapy regimen parameter set, patient status parameter set, and treatment timing parameter set, to generate an initial diagnosis and treatment node sequence containing key nodes.

[0128] Priority adjustment and treatment pathway generation: The fuzzy comprehensive evaluation system of the optimization unit dynamically adjusts the node priority based on the first influencing factor, prioritizes emergency nodes, and generates personalized treatment pathways after adjustment, which are transmitted to the management unit. The management unit arranges time nodes such as chemotherapy, examinations, and follow-up according to the treatment pathway to ensure that patients follow a reasonable treatment plan.

[0129] Results recording and comparison: The system sends appointment reminders through the patient terminal and records the patient's arrival, treatment and departure time at the chemotherapy center. Data such as patient waiting time, appointment accuracy and treatment path compliance are recorded separately for subsequent data analysis.

[0130] Table 1 Comparison of the effects of day-case chemotherapy appointment systems

[0131] index Traditional reservation system The present invention Waiting time (minutes) 45 20 Treatment pathway compliance rate (%) 70 95 Resource utilization (%) 80 95 Booking success rate (%) 85 98 Timely rate of adverse reaction monitoring (%) 60 90

[0132] Table 2 Comparison of treatment indicators of patients in a single cycle

[0133] index Traditional reservation system The present invention Monitoring cycle number 3 5 Chemotherapy completion rate (%) 88 98 Special inspection times 2 4 Timely rate of abnormal indicator inspection (%) 70 92 Patient compliance score ( / 100 points) 75 90

[0134] As shown in Tables 1 and 2, the present invention improves resource utilization and patient compliance, and demonstrates innovation in multiple indicators compared to traditional systems. First, in terms of patient waiting time, the average waiting time for patients in the present invention is 20 minutes, which is significantly lower than the 45 minutes of traditional systems. This is due to the dynamic adjustment of the priority of diagnosis and treatment nodes in the present invention, which gives priority to key nodes, thereby reducing unnecessary waiting time. Secondly, in terms of treatment path compliance rate, the present invention reached 95%, an increase of 25% over traditional systems. This is because the present invention generates personalized diagnosis and treatment paths based on changes in the patient's condition, reducing compliance problems caused by fixed path settings.

[0135] Secondly, in terms of resource utilization and appointment success rate, the resource utilization rate of the present invention is 95%, and the appointment success rate is 98%, both of which are significantly higher than the traditional system. This reflects the optimization strategy of the present invention in resource allocation, giving priority to patients in urgent need of resources, thereby improving the overall resource utilization efficiency. In addition, in terms of the timeliness of adverse reaction monitoring, the timely monitoring rate of the present invention reached 90%, while the traditional system was only 60%. This is particularly critical, reflecting the innovative advantages of the present invention in dynamic monitoring and timely response, reducing the risk of treatment delays due to sudden changes in the disease.

[0136] Finally, in terms of treatment index monitoring, the present invention improves the timeliness of detecting abnormal indicators of patients by introducing dynamic inspection nodes. The present invention performs an average of 5 monitorings in a single cycle, while the traditional system only performs 3 monitorings. In addition, the patient compliance score in the present invention averages 90 points, which is significantly better than the 75 points of the traditional system. This further proves that the present invention improves the patient's compliance during the treatment process through personalized reminder functions and accurate appointment plans, thereby optimizing the chemotherapy treatment effect.

[0137] In summary, the present invention is significantly superior to traditional appointment systems in terms of waiting time, treatment compliance, resource utilization, appointment accuracy, and timeliness of adverse reaction monitoring, which verifies its innovation and practicality in day-case chemotherapy, and provides a scientific basis and effective means for improving chemotherapy treatment efficiency and improving patient experience.

[0138] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A coordination system for intelligent appointment treatment of day chemotherapy, characterized in that: include: An information processing unit (100) is used to obtain medical information of a target patient, construct a comprehensive diagnosis and treatment information model including diagnosis and treatment parameters of the patient, and generate an initial diagnosis and treatment node sequence based on the comprehensive diagnosis and treatment information model; and An optimization unit (200) is used to receive the initial diagnosis and treatment node sequence from the information processing unit (100), adjust the priority of each node in the initial diagnosis and treatment node sequence according to the first influencing factor, and generate a diagnosis and treatment path after re-ordering, and send it to the management unit (300); A management unit (300) generates a day chemotherapy appointment strategy and a follow-up plan for a target patient based on the diagnosis and treatment pathway sent by the optimization unit (200), and sends reminder content containing key appointment information through a patient terminal; The information processing unit (100) comprises a collection module (101), a construction module (102) and a first generation module (103); The acquisition module (101) is used to acquire and pre-process the medical information of the target patient, and transmit the pre-processed medical information to the construction module (102); the medical information includes chemotherapy regimen information, previous chemotherapy records, basic patient information, and laboratory test results before chemotherapy; The construction module (102) is used to receive the pre-processed medical information, extract patient diagnosis and treatment parameters from the medical information, and construct a comprehensive diagnosis and treatment information model based on the patient diagnosis and treatment parameters; wherein the patient diagnosis and treatment parameters include a chemotherapy regimen parameter set, a patient status parameter set, and a treatment timing parameter set; Constructing a comprehensive diagnosis and treatment information model based on the patient diagnosis and treatment parameters includes the following steps: Combining the chemotherapy regimen parameter set, the patient status parameter set and the treatment timing parameter set to form a diagnosis and treatment parameter feature vector; Establishing an association structure between parameters in the diagnosis and treatment parameter feature vector; Based on the association structure and combined with clinical standard specifications, a comprehensive diagnosis and treatment information model is constructed; The first generating module (103) is used to generate an initial diagnosis and treatment node sequence based on the comprehensive diagnosis and treatment information model, specifically: Analyze the key time nodes in the comprehensive diagnosis and treatment information model; the key time nodes include a medication time node set, an examination time node set, and an evaluation time node set; Based on the key time nodes, construct an initial diagnosis and treatment node sequence; Based on the key time nodes, constructing an initial diagnosis and treatment node sequence includes the following steps: The medication time node set, the inspection time node set, and the evaluation time node set are combined and sorted according to the time attribute to form an initial time sequence; each time node in the initial time sequence contains an operation type identifier and timestamp information; The initial time sequence is subjected to conflict detection and adjustment to obtain an adjusted initial time sequence, specifically including: establishing a minimum time interval matrix between operation types; setting a first priority rule for conflict handling, which is, in sequence, a medication time node, an inspection time node, and an evaluation time node; identifying a conflict situation in which the time interval between adjacent time nodes is less than a value specified by the minimum time interval matrix in the initial time sequence; when a conflict is identified, based on the first priority rule, postponing the low-priority time node backward until the minimum time interval requirement is met; if the postponed time node exceeds the available time range for day chemotherapy, adjusting it to the next available date; The adjusted initial time series is marked according to the clinical standard specifications, specifically by assigning a unique operation number to each time node, recording the estimated duration of each time node, marking the preconditions and subsequent requirements of the operation, and generating an initial diagnosis and treatment node sequence containing complete time information and operation attributes.

2. The coordination system for intelligent appointment treatment of day chemotherapy as claimed in claim 1, characterized in that: The optimization unit (200) comprises an adjustment module (201) and a second generation module (202); The adjustment module (201) is used to receive the initial diagnosis and treatment node sequence from the first generation module (103), and adjust the priority of each node in the initial diagnosis and treatment node sequence according to the first influencing factor, specifically: Determining the first influencing factors as a clinical priority factor set and an operational priority factor set; Construct a multi-level fuzzy comprehensive evaluation system, including constructing a fuzzy relationship matrix, using the analytic hierarchy process to calculate the weight vector of clinical priority factors and the weight vector of operational priority factors, and using the fuzzy comprehensive evaluation operator to calculate the priority weight value of the node; Assigning a priority attribute to each node according to the priority weight value; the priority attribute includes a priority weight value, a priority level and a priority validity period; Setting and applying a second priority rule; the second priority rule includes a priority inheritance rule and a priority transfer rule, wherein the priority inheritance rule is that for multiple nodes in the same treatment cycle, subsequent nodes inherit the priority weight value of the closest key node in terms of timing, and determine the priority level and calculate the priority validity period; The priority transfer rule is that for the associated diagnosis and treatment nodes of different treatment cycles, if the priority weight value of the source node has been calculated by the fuzzy comprehensive evaluation operator, then its associated nodes do not need to be recalculated using the fuzzy comprehensive evaluation operator, but the priority weight value of the associated node is determined based on the priority weight value of the source node and the clinical correlation coefficient; The second generating module (202) is used to reorder the nodes in the initial diagnosis and treatment node sequence after the priority is adjusted in the adjusting module (201) to generate a diagnosis and treatment path, specifically: Sort the initial diagnosis and treatment node sequence after priority adjustment in descending order of priority level, descending order of priority weight value, and ascending order of remaining time of priority validity period; According to the priority inheritance rule and the priority transfer rule set in the adjustment module (201), the sorted initial diagnosis and treatment node sequence is converted into a diagnosis and treatment path on the basis of maintaining the inherent time sequence between nodes with inheritance relationship and transfer relationship.

3. The coordination system for intelligent appointment treatment of day chemotherapy as claimed in claim 2, characterized in that: The management unit (300) comprises a third generation module (301) and a reminder module (302); The third generation module (301) generates a day chemotherapy appointment strategy and a follow-up plan for the target patient based on the diagnosis and treatment pathway; the reminder module (302) is used to send reminder content containing key appointment information through the patient terminal.

4. The coordination system for intelligent appointment treatment of day chemotherapy as claimed in claim 3, characterized in that: It also includes a system operation unit (400) and a cloud interaction unit (500); The system operation unit (400) is used to provide operation environment support and realize data exchange between the information processing unit (100), the optimization unit (200) and the management unit (300); The system operation unit (400) comprises a power management module (401), a hardware monitoring module (402) and a network communication module (403); The power management module (401) is responsible for the power supply and power management of the system; the hardware monitoring module (402) is used to monitor the hardware status of the system and send hardware status information to the network communication module (403); the network communication module (403) is responsible for the network communication between the modules within the system and between the system and external devices, receives the status information from the hardware monitoring module (402), and is responsible for the data transmission between all units.

5. The coordination system for intelligent appointment treatment of day chemotherapy as claimed in claim 4, characterized in that: The cloud interaction unit (500) is used to perform cloud synchronization and backup of data of the information processing unit (100), the optimization unit (200) and the management unit (300), and supports remote operation; the cloud interaction unit (500) comprises a data synchronization module (501), a remote access module (502) and a cloud backup module (503); The data synchronization module (501) is responsible for real-time synchronization of local data and cloud data, receives data from all other units, and exchanges data with the cloud; the remote access module (502) is used to allow authorized users to remotely access the system through the cloud, receive remote access requests, and transmit operation instructions to the corresponding unit; the cloud backup module (503) is used to receive data from all units and send backup data to the cloud; The key appointment information includes appointment time, treatment preparation requirements and appointment adjustment information.

6. A method using the coordination system for day chemotherapy intelligent appointment treatment as claimed in any one of claims 1 to 5, characterized in that: include: The information processing unit (100) acquires medical information of a target patient, constructs a comprehensive diagnosis and treatment information model including diagnosis and treatment parameters of the patient, and generates an initial diagnosis and treatment node sequence based on the comprehensive diagnosis and treatment information model; The optimization unit (200) receives the initial diagnosis and treatment node sequence from the information processing unit (100), adjusts the priority of each node in the initial diagnosis and treatment node sequence according to the first influencing factor, generates a diagnosis and treatment path after re-ordering, and sends it to the management unit (300); The management unit (300) generates a daytime chemotherapy appointment strategy and a follow-up plan for the target patient based on the diagnosis and treatment pathway sent by the optimization unit (200), and sends reminder content containing key appointment information through the patient terminal.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the coordination system for intelligent appointment treatment of day chemotherapy according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the coordination system for intelligent appointment treatment of day chemotherapy according to any one of claims 1 to 5 are implemented.

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