Emergency medical resource prediction and planning system and method based on machine learning

Abstract

The invention relates to the technical field of emergency medical resource management, and discloses an emergency medical resource prediction and planning system and method based on machine learning, and the system comprises an emergency medical equipment consumption analysis module, an emergency medical equipment shortage analysis module, and an emergency medical resource prediction and planning result feedback module. Actual medical equipment inventory parameters of the emergency hospital in the current month are obtained online through a hospital material management platform, and reliable data support is provided for accurate statistics of medical resource shortage of the emergency hospital in the current month; the difference value between the predicted consumption of each type of medical equipment in the current month and the actual inventory of the emergency hospital is autonomously and efficiently measured through numerical analysis, scientific prediction statistics of the lack of each type of medical resources in the current month of the emergency hospital is achieved, and digital and intelligent management of the emergency medical resources is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of emergency medical resource management, and specifically to an emergency medical resource prediction and planning system and method based on machine learning. Background Art

[0002] Emergency means emergency treatment and rescue. That is, treatment in emergency situations. Its existence ensures that we can get professional and scientific treatment in the shortest time when we have sudden illnesses or accidental injuries. Medical resources refer to the general term for production factors that provide medical services, usually including personnel, medical expenses, medical institutions, medical beds, medical facilities and equipment, knowledge and skills, and information. Allocation of medical and health resources refers to the allocation and flow of medical and health resources within the medical and health industry or department. It includes two aspects of the allocation of health resources, namely incremental allocation and stock adjustment. The forecasting and planning of emergency medical resources effectively guarantees the effect of emergency treatment and rescue; among them, the forecasting and planning of emergency medical resources mainly focuses on the direction of medical equipment. The current forecasting and planning of emergency medical equipment is mainly based on the operation of management personnel. It cannot be based on the level and scale of emergency hospitals and the historical consumption of emergency medical equipment for scientific and accurate forecasting and planning, nor can it accurately predict, analyze and feedback the shortage of emergency medical equipment.

[0003] A Chinese invention patent with announcement number CN107680661B discloses a system and method for estimating medical resource demand, which collects multi-source extracted data; uses the extracted data to generate records; assigns a label to each record to obtain a labeled record; applies one or more techniques associated with the label of the identified entity to the labeled record to identify one or more entities within each labeled record; generates entity features and relationships between two or more entities based on the labeled records to achieve information prediction of medical resources; however, the above technical solutions cannot scientifically predict medical resources from an overall macro perspective. Summary of the invention

[0004] 1. Technical issues to be resolved In order to solve the problem that the current emergency medical equipment forecasting and planning is mainly based on the operation of management personnel, and cannot be based on the level and scale of the emergency hospital and the historical consumption of emergency medical equipment to carry out scientific and accurate forecasting and planning, and cannot accurately predict, analyze and feedback the shortage of emergency medical equipment, the above-mentioned accurate analysis of the monthly standard medical equipment consumption of emergency hospitals of the same level and scale and the historical monthly medical equipment consumption of emergency hospitals, scientific analysis of the best medical equipment consumption of emergency hospitals for the month, intelligent forecasting and planning of the shortage of medical equipment in emergency hospitals for the month, and visual feedback output of the shortage of medical equipment in emergency hospitals for the month are achieved, so as to realize the scientific and standardized management of emergency medical resources and improve the quality of emergency medical services.

[0005] (II) Technical solution The present invention is implemented by the following technical solution: a method for predicting and planning emergency medical resources, the method comprising the following steps: S1. Collect the scale data of emergency hospitals and the monthly historical time point data of emergency hospitals to be tested; S2. Analyze and process the monthly standard medical equipment consumption of emergency hospitals based on the emergency hospital grade scale data and the monthly standard medical equipment consumption data of emergency hospitals of different grades, and generate monthly standard medical equipment consumption data of emergency hospitals of the same grade; S3, based on the monthly historical time point data to be tested of the emergency hospital and the historical monthly medical equipment consumption data of the emergency hospital at different times, the historical monthly medical equipment consumption data of the emergency hospital in the previous year is analyzed and processed to generate the historical monthly medical equipment consumption data of the emergency hospital in the current month; S4, performing numerical analysis and processing on the best medical equipment consumption of the emergency hospital for the current month based on the monthly standard medical equipment consumption data of the emergency hospital of the same level and the historical monthly medical equipment consumption data of the emergency hospital for the current month, and generating the best medical equipment consumption data of the emergency hospital for the current month; S5. Collect the actual medical equipment inventory data of the emergency hospital in that month; S6. Perform numerical statistical processing on the shortage of medical equipment in the emergency hospital in the current month based on the actual medical equipment inventory data of the emergency hospital in the current month and the optimal medical equipment consumption data of the emergency hospital in the current month, generate and output the shortage of medical equipment in the emergency hospital in the current month; S7. Construct emergency medical resource forecasting and planning result data and execute emergency medical resource forecasting and planning result feedback output operation.

[0006] Preferably, the operation steps of collecting the emergency hospital grade scale data and the emergency hospital monthly historical time point data to be tested are as follows: S11, collecting hospital grade and scale text information of the emergency hospital to be predicted online through a data input dialog box and generating emergency hospital grade and scale data Y, wherein the emergency hospital grade and scale data includes first-level Class A hospitals, second-level Class A hospitals, third-level Class A hospitals, first-level Class B hospitals, second-level Class B hospitals and third-level Class B hospitals; The historical time point text information of the same month of the previous year of the emergency hospital to be predicted is collected online through the data input dialog box, and the monthly historical time point data P of the emergency hospital to be tested is generated. The monthly historical time point data P of the emergency hospital to be tested consists of year and month.

[0007] The present invention accurately inputs the grade and scale parameters of the emergency hospital through the data input dialog box, thereby providing data support for scientifically analyzing the standard monthly medical equipment consumption of emergency hospitals of the same grade and the historical monthly medical equipment consumption of emergency hospitals in the current month.

[0008] Preferably, the monthly standard medical equipment consumption of emergency hospitals is analyzed and processed based on the emergency hospital grade scale data and the monthly standard medical equipment consumption data of emergency hospitals of different grades, and the operating steps for generating the monthly standard medical equipment consumption data of emergency hospitals of the same grade are as follows: S21. Establish a monthly standard medical equipment consumption data set for emergency hospitals of different levels ;in Indicates Monthly consumption data of standard medical equipment in graded emergency hospitals, Indicates the maximum value of the number of emergency hospital grade types. The monthly standard medical equipment consumption data of emergency hospitals of different grades indicates the consumption quantity of various types of medical equipment under normal monthly reception conditions of emergency hospitals of different hospital grades. The types of medical equipment include instruments, equipment, appliances and medical consumables; S22, comparing the emergency hospital grade scale data Y with the monthly standard medical equipment consumption data of emergency hospitals of different grades in the monthly standard medical equipment consumption data set A of emergency hospitals of different grades. According to the hospital grade character matching, search for the monthly standard medical equipment consumption data of the emergency hospitals of different grades corresponding to the emergency hospital grade scale data Y And generate a monthly standard medical equipment consumption data set B of emergency hospitals of the same level through data identification, and the steps for generating the monthly standard medical equipment consumption data set B of emergency hospitals of the same level are as follows: S221, initializing parameters and updating the maximum number of iterations T of the algorithm; S222, initializing the position of the medical equipment consumption identification seagull population, that is, updating the position of the medical equipment consumption identification seagull population in the search space of the monthly standard medical equipment consumption data set A of emergency hospitals of different levels; S223, calculating the monthly standard medical equipment consumption data of all the emergency hospitals of different levels in the monthly standard medical equipment consumption data set A. The fitness value of the emergency hospital grade scale data Y is obtained, and the monthly standard medical equipment consumption data of emergency hospitals of different grades with the largest fitness value matching the emergency hospital grade scale data Y is retained in the search space of the monthly standard medical equipment consumption data set A of emergency hospitals of different grades. The global optimal position of S224, Migration, global search: The migration behavior of the medical equipment consumption identification seagull mainly includes three steps. The first step is to meet the condition of avoiding collision between different medical equipment consumption identification seagulls in the search space of the monthly standard medical equipment consumption data set A of the emergency hospitals of different levels; the second step is to calculate the monthly standard medical equipment consumption data of the emergency hospitals of different levels that match the search space of the monthly standard medical equipment consumption data set A of the emergency hospitals of different levels and the emergency hospital grade scale data Y. The best location direction; third, according to the monthly standard medical equipment consumption data of the emergency hospitals of different levels that best matches the emergency hospital grade scale data Y Move the direction of the best position to a new position; S2241, calculating the new position of the medical equipment consumption identification seagull in the search space of the monthly standard medical equipment consumption data set A of the emergency hospitals of different levels without colliding with the adjacent medical equipment consumption identification seagulls during the movement ; , ;in Indicates the current position of the medical equipment consumption identification seagull in the search space of the monthly standard medical equipment consumption data set A of emergency hospitals of different levels, Indicates the current iteration number; It represents the movement behavior of the medical equipment consumption recognition seagull in the search space of the monthly standard medical equipment consumption data set A of emergency hospitals of different levels; Indicates control Function of the frequency of change, T represents the maximum number of iterations; S2242, calculating the monthly standard medical equipment consumption data of emergency hospitals of different grades that match the search space A of the monthly standard medical equipment consumption data set of emergency hospitals of different grades and the emergency hospital grade scale data Y. The best position direction ; , ,in Indicates that the monthly standard medical equipment consumption data set A of the different levels of emergency hospitals is searched in the search space for the monthly standard medical equipment consumption data of the different levels of emergency hospitals that matches the emergency hospital grade scale data Y. The current best position of represents a random number that balances global and local search capabilities, Represents a random number in the interval [0,1]; S2243, according to the monthly standard medical equipment consumption data of the emergency hospitals of different grades that best matches the emergency hospital grade scale data Y, Move to the new position in the direction of the best position , That is, according to the direction of the optimal position, all the monthly standard medical equipment consumption data of emergency hospitals of different levels that match the emergency hospital grade scale data Y are searched in the search space of the monthly standard medical equipment consumption data set A of emergency hospitals of different levels. new location; S225. Attacking prey, local search, medical equipment consumption identification. The seagull attacks the monthly standard medical equipment consumption data of emergency hospitals of different levels that matches the emergency hospital grade scale data Y in the search space of the monthly standard medical equipment consumption data set A of emergency hospitals of different levels. The prey performs spiral motion in the air, and at the same time identifies the monthly standard medical equipment consumption data of all emergency hospitals of different levels that match the emergency hospital level scale data Y. , medical device consumption identifies the new location of a seagull after attacking its prey , That is, the medical equipment consumption identification seagull searches for the monthly standard medical equipment consumption data of emergency hospitals of different levels that matches the emergency hospital grade scale data Y in the search space of the monthly standard medical equipment consumption data set A of emergency hospitals of different levels. prey; S226: Determine whether the maximum number of iterations is met, and then output the monthly standard medical equipment consumption data of the emergency hospitals of different grades that match the emergency hospital grade scale data Y. ; If not satisfied, return to step S223; S227: Output the monthly standard medical equipment consumption data of emergency hospitals of different grades that match the emergency hospital grade scale data Y in step S226. Generate a monthly standard medical equipment consumption data set for emergency hospitals of the same level through data identification , ;in Indicates The monthly standard medical equipment consumption data of emergency hospitals of the same level corresponding to the medical equipment, Indicates the maximum number of medical device types.

[0009] The present invention uses the Seagull optimization algorithm to accurately analyze the monthly standard medical equipment consumption of emergency hospitals by combining the emergency hospital grade scale parameters with the standard stored monthly standard medical equipment consumption of emergency hospitals of different grades, so as to achieve the effect of accurately counting the monthly standard medical equipment consumption of emergency hospitals of the same grade.

[0010] Preferably, the historical monthly medical equipment consumption data of the emergency hospital in the previous year for the current month is analyzed and processed based on the monthly historical time point data to be tested of the emergency hospital and the historical monthly medical equipment consumption data of the emergency hospital at different times, and the operating steps for generating the historical monthly medical equipment consumption data of the emergency hospital for the current month are as follows: S31. Establish a historical monthly medical equipment consumption data set for emergency hospitals at different times , ;in Indicates The historical monthly medical equipment consumption data of emergency hospitals at different times corresponding to historical months, Indicates the maximum value of the number of historical months, and the historical monthly medical equipment consumption data of emergency hospitals at different times indicate the consumption quantity of various types of medical equipment under the actual reception conditions of the emergency hospital to be predicted at different historical months in the past; S32, using a depth-first search algorithm to compare the monthly historical time point data P of the emergency hospital to be tested with the monthly historical medical equipment consumption data set C of the emergency hospital at different times. According to the historical month character search, analyze the emergency hospital's historical monthly medical equipment consumption data at different times corresponding to the emergency hospital's monthly historical time point data P to be tested. Generate the monthly medical equipment consumption data set of the emergency hospital through data identification ,in Indicates The historical monthly medical equipment consumption data of emergency hospitals corresponding to the type of medical equipment.

[0011] The present invention achieves the effect of digitally measuring the historical monthly medical equipment consumption of the emergency hospital for the current month by accurately identifying the historical monthly medical equipment consumption of the emergency hospital for the current month based on the emergency hospital's monthly historical time point parameters to be measured and scientifically preset historical monthly medical equipment consumption parameters of the emergency hospital at different times.

[0012] Preferably, the optimal medical equipment consumption data of the emergency hospital for the current month is analyzed and processed based on the monthly standard medical equipment consumption data of the emergency hospital of the same level and the historical monthly medical equipment consumption data of the emergency hospital for the current month, and the operation steps for generating the optimal medical equipment consumption data of the emergency hospital for the current month are as follows: S41, using a unified cost search algorithm to search the monthly standard medical equipment consumption data set B of the emergency hospitals of the same level for the monthly standard medical equipment consumption data of the emergency hospitals of the same level. The historical monthly medical equipment consumption data of the emergency hospital in the current month in the historical monthly medical equipment consumption data set D According to the keywords of medical equipment types, the maximum consumption values ​​of each medical equipment in the emergency hospital are screened in order, and the monthly standard medical equipment consumption data of the emergency hospital of the same level corresponding to the maximum consumption value of each medical equipment is searched out. Or the monthly medical equipment consumption data of the emergency hospital in the current month And generate the best medical equipment consumption data set of the emergency hospital in that month through numerical identification ,in Indicates The best medical equipment consumption data of emergency hospitals in that month corresponding to each type of medical equipment.

[0013] The present invention uses a unified cost search algorithm combined with the standard monthly equipment consumption of emergency hospitals of the same level and the historical monthly equipment consumption of emergency hospitals in the current month to perform intelligent forecasting and planning of the optimal medical equipment consumption of emergency hospitals in the current month, thereby achieving the effect of scientifically and accurately predicting the various types of medical resources required by emergency hospitals in the current month.

[0014] Preferably, the operation steps for collecting the actual medical equipment inventory data of the emergency hospital in that month are as follows: S51. The best medical equipment consumption data set of the emergency hospital in that month When the generation is completed, the actual inventory text information of various medical equipment of the emergency hospital in that month is collected online through the hospital material management platform and the actual inventory data set of medical equipment of the emergency hospital in that month is generated. ,in Indicates The actual medical equipment inventory data of emergency hospitals corresponding to the medical equipment in that month.

[0015] The present invention obtains the actual medical equipment inventory parameters of the emergency hospital in the current month online through the hospital material management platform, so as to provide reliable data support for accurately counting the shortage of medical resources in the emergency hospital in the current month.

[0016] Preferably, the steps of performing numerical statistical processing on the shortage of medical equipment in the emergency hospital for the month based on the actual medical equipment inventory data of the emergency hospital for the month and the optimal medical equipment consumption data of the emergency hospital for the month, generating and outputting the shortage of medical equipment in the emergency hospital for the month are as follows: S61, the actual medical equipment inventory data of the emergency hospital in the current month in the data set E of the actual medical equipment inventory data of the emergency hospital in the current month The best medical equipment consumption data collection for the emergency hospital in that month The best medical equipment consumption data for the month in the emergency hospital described in The inventory and consumption values ​​are subtracted in order according to the characters of the medical equipment types to generate a data set of the shortage of medical equipment in the emergency hospital for the month. ,in Indicates The emergency hospitals corresponding to the medical equipment are missing medical equipment quantity data for the month, among which , The value of includes positive, negative and zero. When it is a positive number, it means the emergency hospital is The actual inventory of this type of medical equipment in that month is greater than the predicted consumption; When it is a negative number, it means the emergency hospital is The actual inventory of a medical device in that month is less than the predicted consumption; When it is a positive number, it means the emergency hospital is The inventory of this medical equipment in the current month is equal to the predicted consumption; S62. Data collection of the shortage of medical equipment in the emergency hospital in that month Output data.

[0017] The present invention autonomously and efficiently measures the difference between the predicted consumption and actual inventory of various types of medical equipment in an emergency hospital that month through numerical analysis, thereby achieving the effect of scientifically predicting and counting the shortage of various types of medical resources in an emergency hospital that month.

[0018] Preferably, the steps of constructing the emergency medical resource forecasting planning result data and performing the emergency medical resource forecasting planning result feedback output operation are as follows: S71, the emergency hospital grade scale data Y, the emergency hospital monthly historical time point data P, the emergency hospital monthly medical equipment shortage data set Combine data to construct emergency medical resource forecasting and planning result data ; S72. The emergency medical resource prediction planning result data M is transmitted to the emergency medical resource management center through the Internet of Things and the emergency medical resource prediction result is fed back and outputted using a display screen.

[0019] The present invention achieves the effect of efficient collection and visual output of emergency medical resource forecasting and planning information by independently constructing emergency medical resource forecasting and planning result information and feeding back and outputting it.

[0020] A machine learning-based emergency medical resource prediction and planning system, used to implement the emergency medical resource prediction and planning method, the system comprising an emergency medical equipment consumption analysis module, an emergency medical equipment shortage analysis module, and an emergency medical resource prediction and planning result feedback module; The emergency medical equipment consumption analysis module includes an emergency hospital grade scale information collection unit, an emergency hospital to be tested monthly historical time information collection unit, a monthly standard medical equipment consumption storage unit for emergency hospitals of different grades, a monthly standard medical equipment consumption analysis unit for emergency hospitals of the same grade, a historical monthly medical equipment consumption storage unit for emergency hospitals at different times, an emergency hospital monthly historical medical equipment consumption analysis unit, and an emergency hospital best medical equipment consumption analysis unit for the current month; The emergency hospital grade scale information acquisition unit acquires the grade scale data of the emergency hospital through a data input dialog box; the emergency hospital monthly historical time information acquisition unit acquires the monthly historical time point data of the emergency hospital through a data input dialog box; the monthly standard medical equipment consumption storage unit of emergency hospitals of different grades is used to store the monthly standard medical equipment consumption data of emergency hospitals of different grades; the monthly standard medical equipment consumption analysis unit of emergency hospitals of the same grade performs monthly standard medical equipment consumption analysis and processing on the emergency hospital based on the grade scale data of the emergency hospital and the monthly standard medical equipment consumption data of emergency hospitals of different grades based on machine learning technology, and generates monthly standard medical equipment consumption data of emergency hospitals of the same grade; the monthly historical medical equipment consumption data of emergency hospitals of different times are stored in the storage unit. The monthly medical equipment consumption storage unit is used to store the historical monthly medical equipment consumption data of the emergency hospital at different times; the monthly historical medical equipment consumption analysis unit of the emergency hospital for the current month performs the analysis and processing of the monthly medical equipment consumption of the emergency hospital in the previous year based on the monthly historical time point data to be tested of the emergency hospital and the monthly historical medical equipment consumption data of the emergency hospital at different times, and generates the monthly historical medical equipment consumption data of the emergency hospital for the current month; the monthly best medical equipment consumption analysis unit of the emergency hospital performs the numerical analysis and processing of the monthly best medical equipment consumption of the emergency hospital based on the monthly standard medical equipment consumption data of the emergency hospital of the same level and the monthly historical medical equipment consumption data of the emergency hospital for the current month, and generates the monthly best medical equipment consumption data of the emergency hospital; The emergency medical equipment shortage analysis module includes an emergency hospital medical equipment inventory collection unit for the current month, an emergency hospital medical equipment shortage measurement unit for the current month, and an emergency hospital medical equipment shortage measurement result output unit for the current month; The emergency hospital's medical equipment inventory quantity collection unit for the current month collects the emergency hospital's actual medical equipment inventory quantity data for the current month through the hospital material management platform; the emergency hospital's medical equipment shortage quantity measurement unit for the current month performs numerical statistical processing of the emergency hospital's medical equipment shortage quantity for the current month based on the emergency hospital's actual medical equipment inventory quantity data for the current month and the emergency hospital's optimal medical equipment consumption quantity data for the current month to generate the emergency hospital's medical equipment shortage quantity data for the current month; the emergency hospital's medical equipment shortage quantity measurement result output unit for the current month is used to output the emergency hospital's medical equipment shortage quantity data for the current month; The emergency medical resource prediction and planning result feedback module includes an emergency medical resource prediction and planning result generation unit and an emergency medical resource prediction and planning result feedback output unit; The emergency medical resource forecasting and planning result generating unit is used to construct the emergency medical resource forecasting and planning result data; the emergency medical resource forecasting and planning result feedback output unit performs the emergency medical resource forecasting and planning result feedback output operation according to the emergency medical resource forecasting and planning result data.

[0021] (III) Beneficial effects The present invention provides an emergency medical resource prediction and planning system and method based on machine learning. It has the following beneficial effects: 1. Accurately enter the grade scale parameters of emergency hospitals through the data input dialog box to provide data support for scientific analysis of the standard monthly and historical monthly medical equipment consumption of emergency hospitals of the same grade; accurately analyze the monthly standard medical equipment consumption of emergency hospitals by combining the grade scale parameters of emergency hospitals with the monthly standard medical equipment consumption of emergency hospitals of different grades stored in the standard based on machine learning intelligent algorithms, and achieve accurate statistics of the monthly standard medical equipment consumption of emergency hospitals of the same grade; accurately identify the monthly historical medical equipment consumption of emergency hospitals based on the monthly historical time point parameters of emergency hospitals to be tested combined with intelligent search algorithms and scientifically preset monthly historical medical equipment consumption parameters of emergency hospitals at different times, and achieve digital measurement of the monthly historical medical equipment consumption of emergency hospitals; use intelligent search algorithms combined with the standard monthly equipment consumption of emergency hospitals of the same grade and the monthly historical equipment consumption of emergency hospitals to perform intelligent prediction and planning of the best medical equipment consumption of emergency hospitals for the month, and achieve scientific and accurate prediction of various types of medical resources required by emergency hospitals for the month, thereby improving the efficiency and quality of emergency medical resource management; 2. Obtain the actual inventory parameters of medical equipment in the emergency hospital for the month online through the hospital material management platform to provide reliable data support for the accurate statistics of the shortage of medical resources in the emergency hospital for the month; use numerical analysis to independently and efficiently measure the difference between the predicted consumption and actual inventory of various types of medical equipment in the emergency hospital for the month, realize scientific prediction and statistics of the shortage of various types of medical resources in the emergency hospital for the month, and realize digital and intelligent management of emergency medical resources; 3. By collecting and processing data on emergency hospital grades, emergency hospital forecast time information, and emergency medical resource shortage information, scientifically and autonomously generate emergency medical resource forecast planning result information, and realize efficient collection of emergency medical resource forecast planning information; transmit emergency medical resource forecast planning result information to the emergency medical resource management center in real time through the Internet of Things, and use display screens to output visual feedback of emergency medical resource forecast planning result information, thereby improving the intuitiveness of emergency medical resource management. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A module schematic diagram of an emergency medical resource prediction and planning system based on machine learning provided by the present invention; Figure 2 A flowchart of an emergency medical resource prediction and planning method provided by the present invention. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] The embodiments of the system and method for predicting and planning emergency medical resources based on machine learning are as follows: Example 1: Please refer to Figure 1 - Figure 2 , a method for predicting and planning emergency medical resources, the method comprising the following steps: S1. Collect the scale data of emergency hospitals and the monthly historical time point data of emergency hospitals to be tested; S2. Analyze and process the monthly standard medical equipment consumption of emergency hospitals based on the grade and scale data of emergency hospitals and the monthly standard medical equipment consumption data of emergency hospitals of different grades, and generate the monthly standard medical equipment consumption data of emergency hospitals of the same grade; S3. Analyze and process the monthly medical equipment consumption of the emergency hospital in the previous year based on the monthly historical time point data of the emergency hospital to be tested and the historical monthly medical equipment consumption data of the emergency hospital at different times, and generate the monthly medical equipment consumption data of the emergency hospital in the current month; S4. Perform numerical analysis and processing on the best medical equipment consumption of the emergency hospital for the current month based on the monthly standard medical equipment consumption data of emergency hospitals of the same level and the historical monthly medical equipment consumption data of the emergency hospital for the current month, and generate the best medical equipment consumption data of the emergency hospital for the current month; S5. Collect the actual medical equipment inventory data of the emergency hospital in that month; S6. Perform numerical statistical processing on the shortage of medical equipment in the emergency hospital in the current month based on the actual medical equipment inventory data of the emergency hospital in the current month and the optimal medical equipment consumption data of the emergency hospital in the current month, generate the shortage data of medical equipment in the emergency hospital in the current month and output it; S7. Construct emergency medical resource forecasting and planning result data and execute emergency medical resource forecasting and planning result feedback output operation.

[0025] For further information, see Figure 1 - Figure 2 The steps for collecting emergency hospital grade and scale data and the monthly historical time point data of emergency hospitals to be tested are as follows: S11, collecting hospital grade and scale text information of the emergency hospital to be predicted online through the data input dialog box and generating emergency hospital grade and scale data Y, the emergency hospital grade and scale data including first-level Class A hospitals, second-level Class A hospitals, third-level Class A hospitals, first-level Class B hospitals, second-level Class B hospitals and third-level Class B hospitals; The historical time point text information of the same month of the previous year of the emergency hospital to be predicted is collected online through the data input dialog box, and the monthly historical time point data P of the emergency hospital to be tested is generated. The monthly historical time point data P of the emergency hospital to be tested consists of year and month.

[0026] The monthly standard medical equipment consumption of emergency hospitals is analyzed and processed based on the grade scale data of emergency hospitals and the monthly standard medical equipment consumption data of emergency hospitals of different grades. The steps for generating the monthly standard medical equipment consumption data of emergency hospitals of the same grade are as follows: S21. Establish a monthly standard medical equipment consumption data set for emergency hospitals of different levels ;in Indicates Monthly standard medical equipment consumption data of emergency hospitals of different grades corresponding to different emergency hospital grades, Indicates the maximum number of emergency hospital grade types; the monthly standard medical equipment consumption data of emergency hospitals of different grades indicates the consumption quantity of various types of medical equipment under normal monthly reception conditions of emergency hospitals of different hospital grades, and the types of medical equipment include instruments, equipment, appliances and medical consumables; S22, comparing the emergency hospital grade scale data Y with the monthly standard medical equipment consumption data of emergency hospitals of different grades in the monthly standard medical equipment consumption data set A of emergency hospitals of different grades. According to the hospital grade character matching, search for the monthly standard medical equipment consumption data of the emergency hospitals of different grades corresponding to the emergency hospital grade scale data Y And generate a monthly standard medical equipment consumption data set B of emergency hospitals of the same level through data identification, and the steps for generating the monthly standard medical equipment consumption data set B of emergency hospitals of the same level are as follows: S221, initializing parameters and updating the maximum number of iterations T of the algorithm; S222, initializing the position of the medical equipment consumption identification seagull population, that is, updating the position of the medical equipment consumption identification seagull population in the search space of the monthly standard medical equipment consumption data set A of emergency hospitals of different levels; S223, calculating the monthly standard medical equipment consumption data of all the emergency hospitals of different levels in the monthly standard medical equipment consumption data set A. The fitness value of the emergency hospital grade scale data Y is obtained, and the monthly standard medical equipment consumption data of emergency hospitals of different grades with the largest fitness value matching the emergency hospital grade scale data Y is retained in the search space of the monthly standard medical equipment consumption data set A of emergency hospitals of different grades. The global optimal position of S224, Migration, global search: The migration behavior of the medical equipment consumption identification seagull mainly includes three steps. The first step is to meet the condition of avoiding collision between different medical equipment consumption identification seagulls in the search space of the monthly standard medical equipment consumption data set A of the emergency hospitals of different levels; the second step is to calculate the monthly standard medical equipment consumption data of the emergency hospitals of different levels that match the search space of the monthly standard medical equipment consumption data set A of the emergency hospitals of different levels and the emergency hospital grade scale data Y. The best location direction; third, according to the monthly standard medical equipment consumption data of the emergency hospitals of different levels that best matches the emergency hospital grade scale data Y Move the direction of the best position to a new position; S2241, calculating the new position of the medical equipment consumption identification seagull in the search space of the monthly standard medical equipment consumption data set A of the emergency hospitals of different levels without colliding with the adjacent medical equipment consumption identification seagulls during the movement ; , ;in Indicates the current position of the medical equipment consumption identification seagull in the search space of the monthly standard medical equipment consumption data set A of emergency hospitals of different levels, Indicates the current iteration number; It represents the movement behavior of the medical equipment consumption recognition seagull in the search space of the monthly standard medical equipment consumption data set A of emergency hospitals of different levels; Indicates control Function of the frequency of change, T represents the maximum number of iterations; S2242, calculating the monthly standard medical equipment consumption data of emergency hospitals of different grades that match the search space A of the monthly standard medical equipment consumption data set of emergency hospitals of different grades and the emergency hospital grade scale data Y. The best position direction ; , ,in Indicates that the monthly standard medical equipment consumption data set A of the emergency hospitals of different grades is searched in the search space for the monthly standard medical equipment consumption data of the emergency hospitals of different grades that matches the emergency hospital grade scale data Y. The current best position of represents a random number that balances global and local search capabilities, Represents a random number in the interval [0,1]; S2243, according to the monthly standard medical equipment consumption data of the emergency hospitals of different grades that best matches the emergency hospital grade scale data Y, Move to the new position in the direction of the best position , That is, according to the direction of the optimal position, all the monthly standard medical equipment consumption data of emergency hospitals of different levels that match the emergency hospital grade scale data Y are searched in the search space of the monthly standard medical equipment consumption data set A of emergency hospitals of different levels. new location; S225. Attacking prey, local search, medical equipment consumption identification. The seagull attacks the monthly standard medical equipment consumption data of emergency hospitals of different levels that matches the emergency hospital grade scale data Y in the search space of the monthly standard medical equipment consumption data set A of emergency hospitals of different levels. The prey performs spiral motion in the air, and at the same time identifies the monthly standard medical equipment consumption data of all emergency hospitals of different levels that match the emergency hospital level scale data Y. , medical device consumption identifies the new location of a seagull after attacking its prey , That is, the medical equipment consumption identification seagull searches for the monthly standard medical equipment consumption data of emergency hospitals of different levels that matches the emergency hospital grade scale data Y in the search space of the monthly standard medical equipment consumption data set A of emergency hospitals of different levels. prey; S226: Determine whether the maximum number of iterations is met, and then output the monthly standard medical equipment consumption data of the emergency hospitals of different grades that match the emergency hospital grade scale data Y. ; If not satisfied, return to step S223; S227: Output the monthly standard medical equipment consumption data of emergency hospitals of different grades that match the emergency hospital grade scale data Y in step S226. Generate a monthly standard medical equipment consumption data set for emergency hospitals of the same level through data identification , ;in Indicates The monthly standard medical equipment consumption data of emergency hospitals of the same level corresponding to the medical equipment, Indicates the maximum number of medical device types.

[0027] Based on the monthly historical time point data of the emergency hospital to be tested and the historical monthly medical equipment consumption data of the emergency hospital at different times, the historical monthly medical equipment consumption of the emergency hospital in the previous year is analyzed and processed, and the operation steps for generating the historical monthly medical equipment consumption data of the emergency hospital in the current month are as follows: S31. Establish a historical monthly medical equipment consumption data set for emergency hospitals at different times , ;in Indicates The historical monthly medical equipment consumption data of emergency hospitals at different times corresponding to historical months, Indicates the maximum value of the number of historical months, and the historical monthly medical equipment consumption data of emergency hospitals at different times indicate the consumption quantity of various types of medical equipment under the actual reception conditions of the emergency hospital to be predicted at different historical months in the past; S32, using a depth-first search algorithm to compare the monthly historical time point data P of the emergency hospital to be tested with the monthly historical medical equipment consumption data set C of the emergency hospital at different times. According to the historical month character search, analyze the emergency hospital's historical monthly medical equipment consumption data at different times corresponding to the emergency hospital's monthly historical time point data P to be tested. Generate the monthly medical equipment consumption data set of the emergency hospital through data identification ,in Indicates The historical monthly medical equipment consumption data of emergency hospitals corresponding to the type of medical equipment.

[0028] According to the monthly standard medical equipment consumption data of emergency hospitals of the same level and the monthly historical medical equipment consumption data of emergency hospitals, the optimal medical equipment consumption data of the emergency hospital for the current month is analyzed and processed. The operation steps for generating the optimal medical equipment consumption data of the emergency hospital for the current month are as follows: S41, using a unified cost search algorithm to search the monthly standard medical equipment consumption data set B of the emergency hospitals of the same level for the monthly standard medical equipment consumption data of the emergency hospitals of the same level. The historical monthly medical equipment consumption data of the emergency hospital in the current month in the historical monthly medical equipment consumption data set D According to the keywords of medical equipment types, the maximum consumption values ​​of each medical equipment in the emergency hospital are screened in order, and the monthly standard medical equipment consumption data of the emergency hospital of the same level corresponding to the maximum consumption value of each medical equipment is searched out. Or the monthly medical equipment consumption data of the emergency hospital in the current month And generate the best medical equipment consumption data set of the emergency hospital in that month through numerical identification ,in Indicates The best medical equipment consumption data of emergency hospitals in that month corresponding to each type of medical equipment.

[0029] Through the cooperation of the emergency hospital grade scale information collection unit and the emergency hospital monthly historical time information collection unit, the emergency hospital grade scale parameters are accurately entered using the data input dialog box to provide data support for the scientific analysis of the standard monthly medical equipment consumption of emergency hospitals of the same grade and the monthly historical medical equipment consumption of emergency hospitals of the current month; the monthly standard medical equipment consumption analysis unit of emergency hospitals of the same grade, based on the machine learning intelligent algorithm, combines the emergency hospital grade scale parameters with the monthly standard medical equipment consumption of emergency hospitals of different grades stored in the standard, and conducts an accurate analysis of the monthly standard medical equipment consumption of emergency hospitals of the same grade, so as to achieve accurate statistics of the monthly standard medical equipment consumption of emergency hospitals of the same grade; the monthly historical medical equipment consumption of emergency hospitals of the current month The consumption analysis unit accurately identifies the monthly medical equipment consumption of the emergency hospital based on the monthly historical time point parameters of the emergency hospital to be tested, combined with the intelligent search algorithm and the scientifically preset monthly medical equipment consumption parameters of the emergency hospital at different times, and realizes the digital measurement of the monthly medical equipment consumption of the emergency hospital; the emergency hospital's best medical equipment consumption analysis unit of the month uses an intelligent search algorithm combined with the standard monthly equipment consumption of emergency hospitals of the same level and the monthly historical equipment consumption of the emergency hospital to perform intelligent prediction and planning of the best medical equipment consumption of the emergency hospital that month, thereby realizing the scientific and accurate prediction of various medical resources required by the emergency hospital that month and improving the efficiency and quality of emergency medical resource management.

[0030] For further information, see Figure 1 - Figure 2 The steps to collect the actual medical equipment inventory data of the emergency hospital for the month are as follows: S51. Best medical equipment consumption data collection for the emergency hospital in that month When the generation is completed, the actual inventory text information of various medical equipment of the emergency hospital in that month is collected online through the hospital material management platform and the actual inventory data set of medical equipment of the emergency hospital in that month is generated. ,in Indicates The actual medical equipment inventory data of emergency hospitals corresponding to the medical equipment in that month.

[0031] The steps for performing numerical statistical processing on the shortage of medical equipment in the emergency hospital in the current month based on the actual medical equipment inventory data of the emergency hospital in the current month and the optimal medical equipment consumption data of the emergency hospital in the current month, and generating and outputting the shortage of medical equipment in the emergency hospital in the current month are as follows: S61, the actual medical equipment inventory data of the emergency hospital in the current month in the data set E of the actual medical equipment inventory data of the emergency hospital in the current month The best medical equipment consumption data collection for the emergency hospital in that month The best medical equipment consumption data for the month in the emergency hospital described in The inventory and consumption values ​​are subtracted in order according to the characters of the medical equipment types to generate a data set of the shortage of medical equipment in the emergency hospital for the month. ,in Indicates The emergency hospitals corresponding to the medical equipment are missing medical equipment quantity data for the month, among which , The value of includes positive, negative and zero. When it is a positive number, it means the emergency hospital is The actual inventory of this type of medical equipment in that month is greater than the predicted consumption; When it is a negative number, it means the emergency hospital is The actual inventory of a medical device in that month is less than the predicted consumption; When it is a positive number, it means the emergency hospital is The inventory of this medical equipment in the current month is equal to the predicted consumption; S62. Data collection of the shortage of medical equipment in the emergency hospital in that month Output data.

[0032] Through the emergency hospital's medical equipment inventory collection unit for the month, the hospital material management platform is used to obtain the emergency hospital's actual medical equipment inventory parameters for the month online, providing reliable data support for accurately counting the emergency hospital's medical resource shortages for the month; the emergency hospital's medical equipment shortage measurement unit for the month uses numerical analysis to independently and efficiently measure the difference between the predicted consumption and actual inventory of various types of medical equipment in the emergency hospital for the month, thereby achieving scientific prediction and statistics on the shortage of various types of medical resources in the emergency hospital for the month, and realizing digital and intelligent management of emergency medical resources.

[0033] For further information, see Figure 1 - Figure 2 The steps to construct the emergency medical resource forecasting and planning result data and perform the emergency medical resource forecasting and planning result feedback output operation are as follows: S71, the emergency hospital grade scale data Y, the emergency hospital monthly historical time point data P, the emergency hospital monthly medical equipment shortage data set Combine data to construct emergency medical resource forecasting and planning result data ; S72. The emergency medical resource prediction planning result data M is transmitted to the emergency medical resource management center through the Internet of Things and the emergency medical resource prediction result is fed back and outputted using a display screen.

[0034] Embodiment 2: See also Figure 1 - Figure 2, an emergency medical resource prediction and planning system based on machine learning, used to implement an emergency medical resource prediction and planning method, the system includes an emergency medical equipment consumption analysis module, an emergency medical equipment shortage analysis module, and an emergency medical resource prediction and planning result feedback module; The emergency medical equipment consumption analysis module includes an emergency hospital grade and scale information collection unit, an emergency hospital monthly historical time information collection unit, a storage unit for monthly standard medical equipment consumption of emergency hospitals of different grades, an analysis unit for monthly standard medical equipment consumption of emergency hospitals of the same grade, a storage unit for historical monthly medical equipment consumption of emergency hospitals at different times, an analysis unit for monthly historical medical equipment consumption of emergency hospitals in the current month, and an analysis unit for the best medical equipment consumption of the current month of emergency hospitals; The emergency hospital grade scale information collection unit collects the emergency hospital grade scale data through the data input dialog box; the emergency hospital monthly historical time information collection unit collects the emergency hospital monthly historical time point data through the data input dialog box; the monthly standard medical equipment consumption storage unit of emergency hospitals of different grades is used to store the monthly standard medical equipment consumption data of emergency hospitals of different grades; the monthly standard medical equipment consumption analysis unit of emergency hospitals of the same grade, based on machine learning technology, analyzes and processes the monthly standard medical equipment consumption of emergency hospitals based on the emergency hospital grade scale data and the monthly standard medical equipment consumption data of emergency hospitals of different grades, and generates the monthly standard medical equipment consumption data of emergency hospitals of the same grade; the monthly historical consumption data of emergency hospitals at different times The medical equipment consumption storage unit is used to store the historical monthly medical equipment consumption data of the emergency hospital at different times; the historical monthly medical equipment consumption analysis unit of the emergency hospital for the current month is used to analyze and process the historical monthly medical equipment consumption of the emergency hospital in the previous year for the current month based on the historical time point data of the emergency hospital to be tested in the monthly period and the historical monthly medical equipment consumption data of the emergency hospital at different times, and generate the historical monthly medical equipment consumption data of the emergency hospital for the current month; the best medical equipment consumption analysis unit of the emergency hospital for the current month is used to analyze and process the best medical equipment consumption value of the emergency hospital for the current month based on the monthly standard medical equipment consumption data of emergency hospitals of the same level and the historical monthly medical equipment consumption data of the emergency hospital for the current month, and generate the best medical equipment consumption data of the emergency hospital for the current month; The emergency medical equipment shortage analysis module includes an emergency hospital medical equipment inventory collection unit for the current month, an emergency hospital medical equipment shortage measurement unit for the current month, and an emergency hospital medical equipment shortage measurement result output unit for the current month; The emergency hospital's medical equipment inventory quantity collection unit for the current month collects the emergency hospital's actual medical equipment inventory quantity data for the current month through the hospital's material management platform; the emergency hospital's medical equipment shortage quantity measurement unit performs numerical statistical processing of the emergency hospital's medical equipment shortage quantity for the current month based on the emergency hospital's actual medical equipment inventory quantity data for the current month and the emergency hospital's optimal medical equipment consumption quantity data for the current month, and generates the emergency hospital's medical equipment shortage quantity data for the current month; the emergency hospital's medical equipment shortage quantity measurement result output unit is used to output the emergency hospital's medical equipment shortage quantity data for the current month; The emergency medical resource forecasting and planning result feedback module includes an emergency medical resource forecasting and planning result generating unit and an emergency medical resource forecasting and planning result feedback output unit; The emergency medical resource forecasting and planning result generating unit is used to construct the emergency medical resource forecasting and planning result data; the emergency medical resource forecasting and planning result feedback output unit performs the emergency medical resource forecasting and planning result feedback output operation according to the emergency medical resource forecasting and planning result data.

[0035] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for predicting and planning emergency medical resources, characterized in that: The method comprises the following steps: S1. Collect the scale data of emergency hospitals and the monthly historical time point data of emergency hospitals to be tested; S2. Analyze and process the monthly standard medical equipment consumption of emergency hospitals based on the emergency hospital grade scale data and the monthly standard medical equipment consumption data of emergency hospitals of different grades, and generate monthly standard medical equipment consumption data of emergency hospitals of the same grade; S3, based on the monthly historical time point data to be tested of the emergency hospital and the historical monthly medical equipment consumption data of the emergency hospital at different times, the historical monthly medical equipment consumption data of the emergency hospital in the previous year is analyzed and processed to generate the historical monthly medical equipment consumption data of the emergency hospital in the current month; S4, performing numerical analysis and processing on the best medical equipment consumption of the emergency hospital for the current month based on the monthly standard medical equipment consumption data of the emergency hospital of the same level and the historical monthly medical equipment consumption data of the emergency hospital for the current month, and generating the best medical equipment consumption data of the emergency hospital for the current month; S5. Collect the actual medical equipment inventory data of the emergency hospital in that month; S6. Perform numerical statistical processing on the shortage of medical equipment in the emergency hospital in the current month based on the actual medical equipment inventory data of the emergency hospital in the current month and the optimal medical equipment consumption data of the emergency hospital in the current month, generate and output the shortage of medical equipment in the emergency hospital in the current month; S7. Construct emergency medical resource forecasting and planning result data and execute emergency medical resource forecasting and planning result feedback output operation.

2. According to the method for predicting and planning emergency medical resources according to claim 1, it is characterized in that: The S1 comprises the following steps: S11, collecting hospital grade and scale text information of the emergency hospital to be predicted online through a data input dialog box and generating emergency hospital grade and scale data Y; The historical time point text information of the same month of the previous year of the emergency hospital to be predicted is collected online through the data input dialog box, and the monthly historical time point data P of the emergency hospital to be predicted is generated.

3. The method for predicting and planning emergency medical resources according to claim 2, characterized in that: The S2 comprises the following steps: S21. Establish a monthly standard medical equipment consumption data set for emergency hospitals of different levels ; in Indicates Monthly standard medical equipment consumption data of emergency hospitals of different grades corresponding to different emergency hospital grades, Indicates the maximum number of emergency hospital grade types; S22, comparing the emergency hospital grade scale data Y with the monthly standard medical equipment consumption data of emergency hospitals of different grades in the monthly standard medical equipment consumption data set A of emergency hospitals of different grades. According to the hospital grade character matching, search for the monthly standard medical equipment consumption data of the emergency hospitals of different grades corresponding to the emergency hospital grade scale data Y And generate a monthly standard medical equipment consumption data set B of emergency hospitals of the same level through data identification, and the steps for generating the monthly standard medical equipment consumption data set B of emergency hospitals of the same level are as follows: S221, initializing parameters and updating the maximum number of iterations T of the algorithm; S222, initializing the position of the medical equipment consumption identification seagull population, that is, updating the position of the medical equipment consumption identification seagull population in the search space of the monthly standard medical equipment consumption data set A of emergency hospitals of different levels; S223, calculating the monthly standard medical equipment consumption data of all the emergency hospitals of different levels in the monthly standard medical equipment consumption data set A. The fitness value of the emergency hospital grade scale data Y is obtained, and the monthly standard medical equipment consumption data of emergency hospitals of different grades with the largest fitness value matching the emergency hospital grade scale data Y is retained in the search space of the monthly standard medical equipment consumption data set A of emergency hospitals of different grades. The global optimal position of S224, Migration, global search: The migration behavior of the medical equipment consumption identification seagull mainly includes three steps. The first step is to meet the condition of avoiding collision between different medical equipment consumption identification seagulls in the search space of the monthly standard medical equipment consumption data set A of the emergency hospitals of different levels; the second step is to calculate the monthly standard medical equipment consumption data of the emergency hospitals of different levels that match the search space of the monthly standard medical equipment consumption data set A of the emergency hospitals of different levels and the emergency hospital grade scale data Y. The best location direction; third, according to the monthly standard medical equipment consumption data of the emergency hospitals of different levels that best matches the emergency hospital grade scale data Y Move the direction of the best position to a new position; S2241, calculating a new position of the medical equipment consumption identification seagull that does not collide with an adjacent medical equipment consumption identification seagull during the movement of the medical equipment consumption identification seagull in the search space of the monthly standard medical equipment consumption data set A of emergency hospitals of different levels; S2242, calculating the monthly standard medical equipment consumption data of emergency hospitals of different grades that match the search space A of the monthly standard medical equipment consumption data set of emergency hospitals of different grades and the emergency hospital grade scale data Y. The best position direction; S2243, according to the monthly standard medical equipment consumption data of the emergency hospitals of different grades that best matches the emergency hospital grade scale data Y, Move the direction of the best position to a new position; S225. Attacking prey, local search, medical equipment consumption identification. The seagull attacks the monthly standard medical equipment consumption data of emergency hospitals of different levels that matches the emergency hospital grade scale data Y in the search space of the monthly standard medical equipment consumption data set A of emergency hospitals of different levels. The prey performs spiral motion in the air, and at the same time identifies the monthly standard medical equipment consumption data of all emergency hospitals of different levels that match the emergency hospital level scale data Y. , medical equipment consumption identifies the new location of a seagull after it attacks its prey; S226: Determine whether the maximum number of iterations is met, and then output the monthly standard medical equipment consumption data of the emergency hospitals of different grades that match the emergency hospital grade scale data Y. ; If not satisfied, return to step S223; S227: Output the monthly standard medical equipment consumption data of emergency hospitals of different grades that match the emergency hospital grade scale data Y in step S226. Generate a monthly standard medical equipment consumption data set for emergency hospitals of the same level through data identification , ;in Indicates The monthly standard medical equipment consumption data of emergency hospitals of the same level corresponding to the medical equipment, Indicates the maximum number of medical device types.

4. The method for predicting and planning emergency medical resources according to claim 3, characterized in that: The S3 comprises the following steps: S31. Establish a historical monthly medical equipment consumption data set for emergency hospitals at different times , ; in Indicates The historical monthly medical equipment consumption data of emergency hospitals at different times corresponding to historical months, Indicates the maximum number of historical months; S32, using a depth-first search algorithm to compare the monthly historical time point data P of the emergency hospital to be tested with the monthly historical medical equipment consumption data set C of the emergency hospital at different times. According to the historical month character search, analyze the emergency hospital's historical monthly medical equipment consumption data at different times corresponding to the emergency hospital's monthly historical time point data P to be tested. Generate the monthly medical equipment consumption data set of the emergency hospital through data identification ,in Indicates The historical monthly medical equipment consumption data of emergency hospitals corresponding to the type of medical equipment.

5. The method for predicting and planning emergency medical resources according to claim 4, characterized in that: The S4 comprises the following steps: S41, using a unified cost search algorithm to search the monthly standard medical equipment consumption data set B of the emergency hospitals of the same level for the monthly standard medical equipment consumption data of the emergency hospitals of the same level. The historical monthly medical equipment consumption data of the emergency hospital in the current month in the historical monthly medical equipment consumption data set D According to the keywords of medical equipment types, the maximum consumption values ​​of each medical equipment in the emergency hospital are screened in order, and the monthly standard medical equipment consumption data of the emergency hospital of the same level corresponding to the maximum consumption value of each medical equipment is searched out. Or the monthly medical equipment consumption data of the emergency hospital in the current month And generate the best medical equipment consumption data set of the emergency hospital in that month through numerical identification ,in Indicates The best medical equipment consumption data of emergency hospitals in that month corresponding to each type of medical equipment.

6. The method for predicting and planning emergency medical resources according to claim 5, characterized in that: The S5 comprises the following steps: S51. The best medical equipment consumption data set of the emergency hospital in that month When the generation is completed, the actual inventory text information of various medical equipment of the emergency hospital in that month is collected online through the hospital material management platform and the actual inventory data set of medical equipment of the emergency hospital in that month is generated. ,in Indicates The actual medical equipment inventory data of emergency hospitals corresponding to the medical equipment in that month.

7. The method for predicting and planning emergency medical resources according to claim 6, characterized in that: The S6 comprises the following steps: S61, the actual medical equipment inventory data of the emergency hospital in the current month in the data set E of the actual medical equipment inventory data of the emergency hospital in the current month The best medical equipment consumption data collection for the emergency hospital in that month The best medical equipment consumption data for the month in the emergency hospital described in The inventory and consumption values ​​are subtracted in order according to the characters of the medical equipment types to generate a data set of the shortage of medical equipment in the emergency hospital for the month. ,in Indicates The emergency hospitals corresponding to the medical equipment are missing medical equipment quantity data for the month, among which ; S62. Data collection of the shortage of medical equipment in the emergency hospital in that month Output data.

8. The method for predicting and planning emergency medical resources according to claim 7, characterized in that: The S7 comprises the following steps: S71, the emergency hospital grade scale data Y, the emergency hospital monthly historical time point data P, the emergency hospital monthly medical equipment shortage data set Combine data to construct emergency medical resource forecasting and planning result data ; S72. The emergency medical resource prediction planning result data M is transmitted to the emergency medical resource management center through the Internet of Things and the emergency medical resource prediction result is fed back and outputted using a display screen.

9. A machine learning-based emergency medical resource prediction and planning system, used to implement an emergency medical resource prediction and planning method according to any one of claims 1 to 8, characterized in that: The system includes an emergency medical equipment consumption analysis module, an emergency medical equipment shortage analysis module, and an emergency medical resource forecasting and planning result feedback module; The emergency medical equipment consumption analysis module includes an emergency hospital grade scale information collection unit, an emergency hospital to be tested monthly historical time information collection unit, a monthly standard medical equipment consumption storage unit for emergency hospitals of different grades, a monthly standard medical equipment consumption analysis unit for emergency hospitals of the same grade, a historical monthly medical equipment consumption storage unit for emergency hospitals at different times, an emergency hospital monthly historical medical equipment consumption analysis unit, and an emergency hospital best medical equipment consumption analysis unit for the current month; The emergency hospital grade scale information acquisition unit acquires the grade scale data of the emergency hospital through a data input dialog box; the emergency hospital monthly historical time information acquisition unit acquires the monthly historical time point data of the emergency hospital through a data input dialog box; the monthly standard medical equipment consumption storage unit of emergency hospitals of different grades is used to store the monthly standard medical equipment consumption data of emergency hospitals of different grades; the monthly standard medical equipment consumption analysis unit of emergency hospitals of the same grade performs monthly standard medical equipment consumption analysis and processing on the emergency hospital based on the grade scale data of the emergency hospital and the monthly standard medical equipment consumption data of emergency hospitals of different grades based on machine learning technology, and generates monthly standard medical equipment consumption data of emergency hospitals of the same grade; the monthly historical medical equipment consumption data of emergency hospitals of different times are stored in the storage unit. The monthly medical equipment consumption storage unit is used to store the historical monthly medical equipment consumption data of the emergency hospital at different times; the monthly historical medical equipment consumption analysis unit of the emergency hospital for the current month performs the analysis and processing of the monthly medical equipment consumption of the emergency hospital in the previous year based on the monthly historical time point data to be tested of the emergency hospital and the monthly historical medical equipment consumption data of the emergency hospital at different times, and generates the monthly historical medical equipment consumption data of the emergency hospital for the current month; the monthly best medical equipment consumption analysis unit of the emergency hospital performs the numerical analysis and processing of the monthly best medical equipment consumption of the emergency hospital based on the monthly standard medical equipment consumption data of the emergency hospital of the same level and the monthly historical medical equipment consumption data of the emergency hospital for the current month, and generates the monthly best medical equipment consumption data of the emergency hospital; The emergency medical equipment shortage analysis module includes an emergency hospital medical equipment inventory collection unit for the current month, an emergency hospital medical equipment shortage measurement unit for the current month, and an emergency hospital medical equipment shortage measurement result output unit for the current month; The emergency hospital's medical equipment inventory quantity collection unit for the current month collects the emergency hospital's actual medical equipment inventory quantity data for the current month through the hospital material management platform; the emergency hospital's medical equipment shortage quantity measurement unit for the current month performs numerical statistical processing of the emergency hospital's medical equipment shortage quantity for the current month based on the emergency hospital's actual medical equipment inventory quantity data for the current month and the emergency hospital's optimal medical equipment consumption quantity data for the current month to generate the emergency hospital's medical equipment shortage quantity data for the current month; the emergency hospital's medical equipment shortage quantity measurement result output unit for the current month is used to output the emergency hospital's medical equipment shortage quantity data for the current month; The emergency medical resource prediction and planning result feedback module includes an emergency medical resource prediction and planning result generation unit and an emergency medical resource prediction and planning result feedback output unit; The emergency medical resource forecasting and planning result generating unit is used to construct the emergency medical resource forecasting and planning result data; the emergency medical resource forecasting and planning result feedback output unit performs the emergency medical resource forecasting and planning result feedback output operation according to the emergency medical resource forecasting and planning result data.

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