An artificial intelligence-based medical supply chain management method and system

Abstract

The application provides an artificial intelligence-based medical supply chain management method and system, and belongs to the technical field of supply chain management, and specifically comprises the following steps: acquiring the operation type of a hospital on the current day and the number of operating tables of different operation types, and determining the safe blood usage of the hospital in combination with the traffic flow of different roads at different time periods within the service range of the hospital; based on the road congestion data and the red light setting data of the transportation path between the hospital and the central blood station, an artificial intelligence-based prediction model is used to determine the correction factor of the hospital; the road transportation reliability of the hospital within the preset area of the hospital is determined, and the road transportation reliability and the safe blood usage of the hospital that does not meet the requirements are used to determine the compensation factor of the hospital; and the allocation blood amount of the hospital is determined through the correction factor, the compensation factor and the safe blood usage, thereby reducing the influence of the patient due to the untimely blood supply.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of supply chain management, and particularly relates to a medical supply chain management method and system based on artificial intelligence. BACKGROUND

[0002] Unlike other medical supplies, the reliability and real-time requirements of blood supply are higher. In the prior art, the blood supply is generally distributed in advance according to the blood demand and blood plan of the hospital, but the patients received by the hospital often have a certain randomness, so the blood plan may not meet the blood demand of the patients.

[0003] In order to solve the above technical problems, in the prior art, the demand prediction model is established by analyzing the blood supply data of multiple medical institutions in a specific area and part of the blood use data, the blood supply is dispatched according to the demand prediction model, and the blood supply efficiency is further analyzed in the invention patent CN202210959999.7 "Medical institution blood supply chain management method", but the following technical problems exist:

[0004] The distances of different hospitals to the central blood station of the city are different, and the road conditions and congestion of the central blood station and the hospital also have certain differences. Once there is an unexpected blood use event, the blood supply time efficiency will definitely have certain differences. Therefore, if the blood supply time efficiency cannot be used to determine the differentiated blood allocation, the blood supply time efficiency of the unexpected blood use event may not meet the requirements.

[0005] There may be other hospitals near the hospital whose supply time efficiency does not meet the requirements. Therefore, when blood is urgently needed, if the blood is allocated from the central blood station, the time efficiency may not be met, but the direct distribution from the hospital can meet the operation time efficiency requirements. Therefore, if the blood allocation of the hospital cannot be determined according to the supply time efficiency of the other hospital near the hospital whose supply time efficiency does not meet the requirements, the blood supply time efficiency of the unexpected blood use event may not meet the requirements.

[0006] In view of the above technical problems, the application provides a medical supply chain management method and system based on artificial intelligence. SUMMARY

[0007] To achieve the purpose of the application, the application adopts the following technical solutions:

[0008] According to one aspect of the application, a medical supply chain management method based on artificial intelligence is provided.

[0009] A medical supply chain management method based on artificial intelligence, characterized in that it specifically comprises:

[0010] S1 determines the blood supply reliability of the hospital by the historical transportation time length of the hospital and the central blood station in different time periods, judges whether the blood supply reliability of the hospital and other hospitals in the preset area range of the hospital meets the requirement, if yes, determines the allocation blood amount by the planned blood amount, if not, enters the next step;

[0011] S2 obtains the operation type of the hospital on the day and the operation table number of different operation types, and determines the safe blood amount of the hospital in combination with the traffic volume of different roads in different time periods within the service range of the hospital;

[0012] S3 determines the road transportation reliability between the hospital and the central blood station based on the road congestion data and the red light setting data of the transportation path between the hospital and the central blood station in different time periods, adopts an artificial intelligence-based prediction model, and determines the correction factor of the hospital based on the road transportation reliability of the hospital;

[0013] S4 determines the compensation factor of the hospital by the road transportation reliability of the hospital and the safe blood amount of the hospital in the preset area range of the hospital, and determines the allocation blood amount of the hospital by the correction factor, the compensation factor and the safe blood amount.

[0014] The beneficial effects of the application are:

[0015] 1. By judging whether the blood supply reliability of the hospital and other hospitals in the preset area range of the hospital meets the requirement, not only the influence of the transportation time length on the blood supply reliability of the hospital is considered, but also the blood supply reliability of other hospitals in the preset area range is considered, so that the use of patients in urgent need is not affected due to the blood supply reliability of a hospital not meeting the requirement, and the reliability of blood supply is ensured.

[0016] 2. By comprehensively considering the operation table number and the traffic volume of different roads in different time periods within the service range of the hospital to determine the safe blood amount of the hospital, not only the use demand of the operation itself is considered, but also the demand for unexpected blood use due to the difference in the probability of traffic accidents of different hospitals is fully considered by evaluating the traffic volume of the road, so that the reliability of blood supply is ensured.

[0017] 3. The allocation blood amount of the hospital is determined by the correction factor, the compensation factor and the safe blood amount, which not only considers the difference in the redundancy demand of the allocation blood amount of the hospital itself due to the unsmooth road transportation, but also comprehensively considers the safe blood amount of other hospitals in the preset area range, so that when other hospitals have blood use demand, the redundant blood amount of the hospital can be transported to meet the demand of other hospitals, and the blood use reliability of all hospitals in a certain area is ensured.

[0018] Further, the historical transportation time is determined according to historical transportation data of the central blood station and the hospital.

[0019] Further, the method for determining the blood supply reliability of the hospital comprises:

[0020] The same day is divided into multiple division time periods according to a preset time interval, and the blood supply reliability of different division time periods is determined according to the historical transportation time and the transportation time threshold of the division time period of the date under different date types.

[0021] The blood supply reliability of the hospital is determined by the blood supply reliability of different division time periods.

[0022] Further, the preset time interval is determined according to the length of the transportation path of the hospital and the central blood station, wherein the longer the length of the transportation path of the hospital and the central blood station, the shorter the preset time interval.

[0023] Further, the date type comprises holidays, weekends and weekdays.

[0024] Further, the planned blood consumption is determined according to the reported blood consumption of the hospital.

[0025] Further, the operation type is divided according to the risk degree of the operation, and specifically, the operation is divided into first-class operation, second-class operation, third-class operation and fourth-class operation.

[0026] The operation type of the hospital on the day and the number of operating tables of different operation types are obtained, and the safe blood consumption of the hospital is determined in combination with the traffic flow of different roads in different time periods within the service range of the hospital.

[0027] Further, the red light setting data comprises the number of red light intersections and the timing duration of different red lights.

[0028] In a second aspect, the present application provides a computer system, comprising a memory and a processor connected in communication, and a computer program stored on the memory and capable of running on the processor, characterized in that the processor executes the computer program to perform the above-mentioned medical supply chain management method based on artificial intelligence.

[0029] Other features and advantages will be set forth in the following description, and the objects and other advantages of the present application will be achieved and obtained by the structures particularly pointed out in the description and the drawings.

[0030] In order to make the above objectives, characteristics and advantages of the present application more apparent, more comprehensible, the following preferred embodiments are specifically described in detail below, and the accompanying drawings are referred to. BRIEF DESCRIPTION OF DRAWINGS

[0031] The above and other features and advantages of the present application will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

[0032] Figure 1 is a flowchart of a medical supply chain management method based on artificial intelligence;

[0033] Figure 2 is a flowchart of a method for determining blood supply reliability of a hospital;

[0034] Figure 3 is a flowchart of a method for determining safe blood usage amount of a hospital. DETAILED DESCRIPTION

[0035] In order to make the technical solutions in the specification better understood by the person skilled in the art, the technical solutions in the specification will be described clearly and completely below in conjunction with the drawings in the embodiments of the specification. Obviously, the described embodiments are only some of the embodiments of the specification, not all the embodiments. Based on the embodiments of the specification, all other embodiments obtained by the person skilled in the art without creative labor should belong to the protection scope of the specification.

[0036] Method class embodiments

[0037] To solve the above problems, according to one aspect of the present application, as shown in Figure 1 , a medical supply chain management method based on artificial intelligence is provided, characterized in that it specifically comprises:

[0038] S1 determines the blood supply reliability of the hospital by the historical transportation time length of the hospital and the central blood station in different time periods, judges whether the blood supply reliability of the hospital and other hospitals within the predetermined area range of the hospital meets the requirements, if yes, determines the allocation blood amount by the planned blood usage amount, if not, proceeds to the next step;

[0039] Specifically, the historical transportation time length is determined according to the historical transportation data of the central blood station and the hospital.

[0040] It should be noted that the method for determining the blood supply reliability of the hospital is:

[0041] The same day is divided into multiple time periods according to a preset time interval. The supply reliability of different time periods is determined based on the historical transportation time and transportation time threshold of the time periods under different date types.

[0042] The reliability of the hospital's blood supply was determined by assessing the supply reliability across different time periods.

[0043] Specifically, the preset time interval is determined based on the length of the transportation route between the hospital and the central blood station, wherein the longer the transportation route between the hospital and the central blood station, the shorter the preset time interval.

[0044] Furthermore, the date types include public holidays, weekends, and weekdays.

[0045] In another possible embodiment, such as Figure 2 As shown, the method for determining the reliability of the hospital's blood supply is as follows:

[0046] The same day is divided into multiple time periods according to a preset time interval. Based on the historical transportation time of the time periods on different dates and the transportation time threshold, the dates whose historical transportation time exceeds the transportation time threshold are determined and are regarded as problem transportation dates. It is then determined whether the hospital has problem transportation dates. If yes, proceed to the next step; otherwise, it is determined that the hospital's blood supply reliability meets the requirements.

[0047] Obtain the total number of problematic transportation dates for the hospital in different time periods, and determine the comprehensive deviation of the hospital's problematic transportation dates by combining the deviation of the historical transportation duration of different problematic transportation dates with the transportation duration threshold. Determine whether the comprehensive deviation of the hospital's problematic transportation dates meets the requirements. If not, proceed to the next step. If yes, determine that the hospital's blood supply reliability meets the requirements.

[0048] Based on the number of problematic transport dates in different time periods, the deviation of the historical transport duration of different problematic transport dates from the transport duration threshold, and the average historical transport duration of dates under different date types, the supply reliability of different time periods is determined. It is then determined whether the number of time periods where the supply reliability does not meet the requirements is met. If not, proceed to the next step; if yes, it is determined that the blood supply reliability of the hospital meets the requirements.

[0049] The supply reliability of the hospital is determined by obtaining the supply reliability of different time periods and combining the number of time periods where the supply reliability does not meet the requirements with the comprehensive deviation of the problematic transportation date of the hospital.

[0050] In another possible embodiment, the method for determining the blood supply reliability of the hospital is:

[0051] S11 divides the time period in the same day into multiple division time periods according to a preset time interval, determines the dates with the historical transportation time length of the different division time periods greater than the transportation time length threshold value according to the historical transportation time length of the different division time periods and the transportation time length threshold value, and takes the dates as the problem transportation dates, judges whether the hospital has the problem transportation dates, if yes, proceeds to the next step, and if not, determines that the blood supply reliability of the hospital meets the requirement;

[0052] S12 determines the supply reliability of the different division time periods according to the number of the problem transportation dates of the different division time periods, the deviation amount of the historical transportation time length of the different problem transportation dates from the transportation time length threshold value, and the mean value of the historical transportation time length of the dates under different date types, judges whether the number of the division time periods with the supply reliability not meeting the requirement meets the requirement, if not, proceeds to step S14, and if yes, proceeds to step S13;

[0053] S13 judges whether there are adjacent division time periods with the supply reliability not meeting the requirement according to the different division time periods with the supply reliability not meeting the requirement, if yes, proceeds to the next step, and if not, determines that the blood supply reliability of the hospital meets the requirement;

[0054] S14 takes the adjacent division time periods with the supply reliability not meeting the requirement as the continuous problem division time periods, and determines the supply reliability of the continuous problem division time periods according to the continuous time length of the different continuous problem division time periods and the supply reliability;

[0055] S15 obtains the supply reliability of the different division time periods, and determines the blood supply reliability of the hospital in combination with the number of the division time periods with the supply reliability not meeting the requirement and the supply reliability of the continuous problem division time periods of the hospital.

[0056] Specifically, the planned blood consumption is determined according to the reported blood consumption of the hospital.

[0057] S2 obtains the operation types of the hospital on the current day and the number of operating tables of different operation types, and determines the safe blood consumption of the hospital in combination with the traffic of different roads in different time periods within the service range of the hospital;

[0058] It should be noted that the operation types are divided according to the risk degree of the operation, and specifically, the operation is divided into first-class operation, second-class operation, third-class operation and fourth-class operation.

[0059] Obtaining the operation types of the hospital on the day and the operation table numbers of different operation types, and determining the safe blood usage of the hospital in combination with the traffic volumes of different roads in different time periods within the service range of the hospital;

[0060] In one possible embodiment, as shown in Figure 3 the method for determining the safe blood usage of the hospital is as follows:

[0061] Determining the basic blood usage of different operation types according to the operation table numbers of different operation types, and determining the basic safe blood usage of the hospital in combination with the preset blood usage correction factors of different operation types;

[0062] Determining the accident occurrence probabilities of different roads within the service range of the hospital through the traffic volumes of the different roads of the hospital in different time periods, and determining the comprehensive accident occurrence probability of the hospital based on the accident occurrence probabilities of different roads;

[0063] Determining the safe blood usage of the hospital based on the comprehensive accident occurrence probability of the hospital and the basic safe blood usage of the hospital.

[0064] Further, determining the safe blood usage of the hospital based on the comprehensive accident occurrence probability of the hospital and the basic safe blood usage of the hospital, specifically including:

[0065] Determining the accidental operation blood usage of the hospital based on the comprehensive accident occurrence probability, and determining the safe blood usage of the hospital through the accidental operation blood usage of the hospital and the basic safe blood usage.

[0066] In another possible embodiment, the method for determining the safe blood usage of the hospital is as follows:

[0067] Determining the basic blood usage of different operation types according to the operation table numbers of different operation types, and determining the basic safe blood usage of the hospital in combination with the preset blood usage correction factors of different operation types;

[0068] Determining whether there is a road with a traffic volume greater than a preset traffic volume threshold value in a time period, through the traffic volumes of the different roads of the hospital in different time periods, if yes, proceeding to the next step, and if no, determining the safe blood usage of the hospital through the basic safe blood usage;

[0069] The time period with traffic volume greater than a preset traffic volume threshold is regarded as a peak time period, and the determination of the probability of traffic accidents of roads with peak time periods is performed according to the number of peak time periods of different roads and the traffic volume of different peak time periods, to determine whether there is a road with peak time periods whose probability of traffic accidents does not meet the requirements, if yes, proceed to the next step, if no, determine the safe blood volume of the hospital through the basic safe blood volume;

[0070] The road with peak time periods is regarded as a risk road, and the determination of the comprehensive probability of traffic accidents of the hospital is performed according to the number of risk roads, the probability of traffic accidents of different risk roads, and the traffic volume of other roads except the risk roads in different time periods, to determine the safe blood volume of the hospital based on the comprehensive probability of traffic accidents of the hospital and the basic safe blood volume of the hospital.

[0071] S3 determines the road transportation reliability between the hospital and the central blood station based on the road congestion data and the traffic light setting data of different time periods of the transportation path between the hospital and the central blood station, using an artificial intelligence-based prediction model, and determines the correction factor of the hospital based on the road transportation reliability of the hospital;

[0072] Specifically, the traffic light setting data includes the number of traffic light intersections and the timing duration of different traffic lights.

[0073] In one possible embodiment, the method for determining the road transportation reliability is as follows:

[0074] The number of congested road sections and the congestion degree of different congested road sections in different time periods are determined based on the road congestion data of different time periods of the transportation path between the hospital and the central blood station, and the road transportation reliability in different time periods is determined in combination with the number of traffic light settings on the transportation path and the length of the transportation path;

[0075] The road transportation reliability between the hospital and the central blood station is determined using a prediction model based on the PSO-BP algorithm through the road transportation reliability in different time periods.

[0076] It should be noted that the congestion degree of the congested road section is determined according to the ratio of the average vehicle passing time of the congested road section to the average vehicle passing time of the congested road section when it is not congested.

[0077] In another possible embodiment, the method for determining the road transportation reliability is as follows:

[0078] The basic road transportation reliability between the hospital and the central blood station is determined using a prediction model based on the PSO-BP algorithm through the number of traffic light settings on the transportation path and the length of the transportation path;

[0079] determine whether there is a period with a congested road section based on road congestion data of different time periods of a transportation path between the hospital and the central blood station, if yes, proceed to the next step, if no, take the basic road transportation reliability as the road transportation reliability between the hospital and the central blood station;

[0080] determine the number of congested road sections of different time periods, and determine the comprehensive congestion degree of different time periods in combination with the congestion degree of different congested road sections, determine whether there is a period with a comprehensive congestion degree not meeting the requirements, if yes, proceed to the next step, if no, take the basic road transportation reliability as the road transportation reliability between the hospital and the central blood station;

[0081] take the period with a comprehensive congestion degree not meeting the requirements as a serious congestion period, and determine the continuous congestion period and the congestion duration of the continuous congestion period according to the corresponding time of the serious congestion period, and determine the comprehensive congestion degree of the continuous congestion period in combination with the number of continuous congestion periods;

[0082] obtain the number of serious congestion periods and the comprehensive congestion degree of different time periods, and correct the basic road transportation reliability in combination with the comprehensive congestion degree of the continuous congestion period to obtain the road transportation reliability between the hospital and the central blood station.

[0083] It should be noted that the correction factor of the hospital is determined according to a preset reliability interval corresponding to the road transportation reliability between the hospital and the central blood station, and specifically, the correction factor is determined by the correction factor corresponding to the preset reliability interval.

[0084] S4 determines the compensation factor of the hospital by the road transportation reliability of the hospital whose road transportation reliability in a preset area of the hospital does not meet the requirements and the safe blood consumption, and determines the allocated blood amount of the hospital by the correction factor, the compensation factor and the safe blood consumption.

[0085] It should be noted that the method for determining the compensation factor of the hospital is:

[0086] take the hospital whose road transportation reliability in a preset area of the hospital does not meet the requirements as a screening hospital, and determine the compensation factor of different screening hospitals according to the road transportation reliability, the safe blood consumption of the screening hospital and the distance between the screening hospital and the hospital;

[0087] determine the compensation factor of the hospital by the compensation factors of different screening hospitals.

[0088] Embodiment 2

[0089] In another aspect, the present application provides a computer system comprising a memory and a processor connected in communication, and a computer program stored on the memory and capable of running on the processor, characterized in that the processor, when running the computer program, performs the above-mentioned artificial intelligence-based medical supply chain management method.

[0090] With the above embodiments, the present application has the following beneficial effects:

[0091] 1. By judging whether the blood supply reliability of the hospital and other hospitals within the preset area of the hospital meets the requirements, not only the influence of the transportation time on the blood supply reliability of the hospital is considered, but also the blood supply reliability of other hospitals within the preset area is considered, so as to avoid the influence of the blood supply reliability of a hospital not meeting the requirements on the use of patients in urgent need, and ensure the reliability of blood supply.

[0092] 2. By comprehensively considering the number of operating tables and the traffic of different roads in different time periods within the service range of the hospital to determine the safe blood use amount of the hospital, not only the use demand of the operation itself is considered, but also the demand for accidental blood use due to the difference in the probability of traffic accidents of different hospitals is fully considered through the evaluation of the traffic of the road, so as to ensure the reliability of blood supply.

[0093] 3. By the correction factor, the compensation factor and the safe blood use amount, the allocation blood amount of the hospital is determined, which not only considers the difference in the redundancy demand of the allocation blood amount of the hospital itself due to the unsmooth road transportation, but also comprehensively considers the safe blood use amount of other hospitals within the preset area, so that when other hospitals have blood use demand, the redundant blood amount of the hospital can be transferred to meet the demand of other hospitals, and the blood use reliability of all hospitals in a certain area is ensured.

[0094] Each of the embodiments in the specification is described in a progressive manner, and the same and similar parts between the embodiments can be referred to each other. Each embodiment focuses on the difference from other embodiments. Especially, for the device, equipment and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the part of the method embodiment.

[0095] The above describes specific embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different than the order in which they are recited, and still achieve desirable results. In addition, the processes depicted in the figures do not necessarily require the particular order shown, or sequential order, to achieve the desired results. In certain implementations, multitasking and parallel processing can be advantageous.

[0096] The above merely provides one or more embodiments of the present specification and is not intended to limit the present specification. One or more embodiments of the present specification can have various changes and modifications for those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of the present specification should be included in the scope of claims of the present specification.

Claims

1. An artificial intelligence-based medical supply chain management method, characterized by, Specifically comprising: The blood supply reliability of the hospital is determined by the historical transportation time length of the hospital and the central blood station in different time periods, and whether the blood supply reliability of the hospital and other hospitals within the preset area range of the hospital meets the requirements is determined. If yes, the allocation blood amount is determined by the planned blood amount, and if not, the next step is entered; The type of operation of the hospital on the day and the number of operating tables of different operation types are obtained, and the safe blood use amount of the hospital is determined in combination with the traffic flow of different roads in different time periods within the service range of the hospital; Based on the road congestion data and the red light setting data of the transportation path between the hospital and the central blood station, an artificial intelligence-based prediction model is used to determine the road transportation reliability between the hospital and the central blood station, and a correction factor of the hospital is determined based on the road transportation reliability of the hospital; The compensation factor of the hospital is determined by the road transportation reliability and the safe blood use amount of the hospital within the preset area of the hospital whose road transportation reliability does not meet the requirements, and the allocation blood amount of the hospital is determined by the correction factor, the compensation factor and the safe blood use amount; The method for determining the compensation factor of the hospital is: The hospitals whose road transportation reliability within the preset area of the hospital does not meet the requirements are selected as screening hospitals, and the compensation factors of different screening hospitals are determined according to the road transportation reliability, the safe blood use amount of the screening hospitals and the distance between the screening hospitals and the hospital; The compensation factor of the hospital is determined by the compensation factors of different screening hospitals; The method for determining the blood supply reliability of the hospital is: The time periods within the same day are divided into multiple division time periods according to a preset time interval, and the supply reliability of different division time periods is determined according to the historical transportation time length and the transportation time length threshold of the division time periods of the date under different date types; The blood supply reliability of the hospital is determined by the supply reliability of different division time periods; The method for determining the safe blood use amount of the hospital is: The basic blood use amount of different operation types is determined according to the number of operating tables of different operation types, and the basic safe blood use amount of the hospital is determined in combination with the preset blood use amount correction factor of different operation types; The accident occurrence probability of different roads within the service range of the hospital is determined by the traffic flow of different roads of the hospital in different time periods, and the comprehensive accident occurrence probability of the hospital is determined based on the accident occurrence probability of different roads; The safe blood use amount of the hospital is determined based on the comprehensive accident occurrence probability of the hospital and the basic safe blood use amount of the hospital.

2. The artificial intelligence-based medical supply chain management method of claim 1, wherein, The historical transportation time length is determined according to the historical transportation data of the central blood station and the hospital. 3.The artificial intelligence-based medical supply chain management method of claim 1, wherein, The preset time interval is determined according to the length of the transportation path between the hospital and the central blood station, wherein the longer the length of the transportation path between the hospital and the central blood station, the shorter the preset time interval.

4. The artificial intelligence-based medical supply chain management method of claim 1, wherein, The operation type is classified according to the risk degree of the operation, and the operation is classified into a first-class operation, a second-class operation, a third-class operation and a fourth-class operation.

5. The artificial intelligence-based medical supply chain management method of claim 1, wherein, The safety blood consumption of the hospital is determined based on the comprehensive probability of traffic accidents and the basic safety blood consumption of the hospital, and specifically includes: The safety blood consumption of the hospital is determined based on the comprehensive probability of traffic accidents and the basic safety blood consumption of the hospital, and specifically includes:

6. The artificial intelligence-based medical supply chain management method of claim 1, wherein, The method for determining the road transportation reliability comprises the following steps: The number of congestion road sections and the congestion degree of different congestion road sections in different time periods are determined based on the road congestion data of the transportation path between the hospital and the central blood station in different time periods, and the road transportation reliability in different time periods is determined in combination with the number of traffic light settings on the transportation path and the length of the transportation path; The road transportation reliability between the hospital and the central blood station is determined by the road transportation reliability in different time periods and a prediction model based on a PSO-BP algorithm.

7. A computer system comprising: The memory and the processor connected in communication, and the computer program stored on the memory and capable of running on the processor, characterized in that: when the processor runs the computer program, it executes the artificial intelligence-based medical supply chain management method of any one of claims 1-6.

Images