46 results about "Drugs sales" patented technology

The invention discloses a drug retail industry drug sales prediction system, and belongs to the technical field of big data and artificial intelligence. The system comprises a data acquisition and preprocessing unit, a historical data analysis unit and a prediction unit, and further provides a drug sales prediction method in the drug retail industry, and the method comprises the steps of data acquisition and preprocessing; Historical data analysis and data normalization processing; Data prediction: respectively establishing a cubic exponential smoothing prediction model, a grey prediction model and an LSTM prediction model, and combining the cubic exponential smoothing prediction model, the grey prediction model and the LSTM prediction model to form a BP neural network combination prediction model; Finally, a combined prediction result based on the BP neural network is obtained, so that a prediction model is rapidly and accurately established according to historical sales data, sales data of the pharmacy drugs in a future period of time is predicted, and then data support is provided for warehouse drug storage so as to achieve the purpose of meeting drug supply and demand balance.

In an example embodiment, drug sale data is accessed from a prescription drug wholesaler regarding prescription drugs sold to the pharmacy by the prescription drug wholesaler during a period of time. Pharmacy claims data over the period of time is accessed, where the pharmacy claims data reflects a plurality of claims that were submitted for adjudication by the pharmacy during the period of time. A number of units of a prescription drug associated with the plurality of claims submitted during the period of time by the pharmacy for adjudication are determined based on the pharmacy claims data. This number of units of the prescription drug is compared with the number of units of the prescription drug sold to the pharmacy. A determination is then made as to whether a discrepancy exists based on the results of the comparison. Additional methods and systems are disclosed.

The invention discloses a medicine recommendation method and system. The drug recommendation method comprises the following steps: S1, obtaining a drug sales list, wherein the drug sales list comprises drug information of a plurality of drugs; setting a corresponding medicine label portrait for each medicine; wherein the drug label portrait comprises at least one drug label; wherein the medicine label is arranged according to the medicine information; S2, setting a user label portrait for each user; wherein the user tag portrait comprises at least one user tag, and the user tag is set according to user information; and S3, selecting drugs to be recommended from the drug sales list according to the user tag portrait and the drug tag portrait. According to the method and the device, accurateand personalized medicines conforming to the use characteristics of the medicines are recommended to the user.

The invention discloses an intelligent classified storage management system for medicines, comprising a storage space partitioning module, a medicines sales statistics module, a storage path module, amedicines storage module, a storage space detection module, a cloud server and a display terminal; the storage space partitioning module comprises a storage space partitioning module, a medicines sales statistics module, a storage path module, a medicines storage module, a storage space detection module, a cloud server and a display terminal. The storage space partition module is connected with the drug sales statistics module, and the cloud server is connected with the storage space partition module, the drug sales statistics module, the storage path module, the storage space detection module, the drug warehousing module and the display terminal. The invention can partition the storage space of each drug under each drug type, the rationality of storage space is improved, The invention can reasonably allocate the storage space between each storage sub-unit, meet the storage demand, and judge whether the transportation path of each drug stored in each storage sub-unit is correct, thusimproving the judgment of the correctness of the drug storage path, realizing the intelligent classification storage of drugs, improving the storage efficiency and accuracy, and facilitating the management of drugs.

The invention discloses a method for forecasting drug sales volume, which comprises the following steps: S1, establishing a basic information relationship: firstly, cleaning and arranging data, collecting bill information of all hospitals in a region, and constructing a tree information map of patients, diseases of patients in the past period, and drugs and medical devices used by patients; S2, calculating the characteristic index of the patient according to the list of the patient, and applying the canopy algorithm and the KMeans algorithm to carry on the machine learning, and classifying thepatient automatically; S3,using an ARIMA model of time series analysis to predict the number of patients of each type in the next year; S4, calculating the proportion of each disease of the drug or medical device, and obtaining the predicted value of the drug or medical device based on the disease composition according to the predicted value of each type of patient. The method has the advantagesof reasonable design, simple and reliable prediction mode, and convenient and accurate prediction of the sales volume of various medicines.

The invention discloses a method and a system for supervising online drug sales based on a database. The method comprises the following steps: obtaining a registration application of an online pharmacy and verifying the registration application; Successful registration of online pharmacies with approved registration requests; Storing the online pharmacy information with a successful registration mark into a pharmacy database; Determining at least one merchandise to be sold of an online pharmacy having a registration success mark, and setting drug identification information for each drug, and storing drug identification information and trade information for each drug in a drug database; Obtaining a trade request for the target drug; When the online pharmacy of the target drug has a successful registration mark, the drug identification information and the trading information of the target drug are verified; When the drug identification information of the target drug passes the verification and the trading status of the target drug is unsold, the target drug is sold; And change the trading status of the target drug to sold.

The invention discloses a medicine selling system, relates to a commercial mode of medicine selling, and belongs to the technical field of electronic commerce. Problems that an existing medicine selling mode is single in selling mode, low in purchasing and buying efficiency, and poor in traceability are solved. The system comprises a medical information module used for collecting prescription information of a doctor. The medicine sales information storage module is used for summarizing and storing prescription medicine sales information sent by the sales terminal. And the selling terminal is used for recording the medicine information of the sold prescription medicines and the information of the corresponding doctor prescriptions, forming the recorded information into prescription medicineselling information and sending the prescription medicine selling information to the medicine selling information storage module. The system can further comprise a sales supervision module used for monitoring the sales number of the drugs in the same prescription. The method is the development trend of a drug sales mode, can effectively realize drug sales direction tracking, and further realizeseffective monitoring of the prescription drug usage amount of a doctor and the number of prescription drugs purchased by a patient.

The invention provides a BP neural network-based drug sales prediction and decision-making method and system. The method comprises the steps of obtaining related data information of drug historical sales volume, performing preprocessing and abnormal data inspection on the related data information, and performing prediction by adopting a basic BP neural network based on the preprocessed drug historical sales volume data; correcting the short-term prediction result of the basic BP neural network based on the historical data of drug sales and the priori data of drug sales; and performing sales decision based on the output prediction result. According to the invention, the prediction precision is improved through a neural network drug sales prediction algorithm based on big data, and the prediction precision is further improved through each correction step. The drug sales volume of each period in a future period can be accurately predicted; and meanwhile, a series of reasonable decision schemes capable of changing the drug sales situation can be made based on the prediction conclusion in the prior art, so that the total drug sales amount in a future period of time is maximum.

The invention relates to the technical field of medical information sharing, and specifically relates to an electronic prescription sharing system and sharing method. The electronic prescription sharing method includes the steps: a medical institution issues an electronic prescription for a patient, and transmits personal information, diagnosis and treatment information and the electronic prescription of the patient to a server; the server collects, stores and manages the personal information, the diagnosis and treatment information and the electronic prescription, sent by the medical institution, of the patient; other medical institutions or drug sales organizations enter the personal information of the patient and transmit the personal information of the patient to the server for verification; and after the verification is passed, other medical institutions or drug sales organizations obtain the authority to process or view the electronic prescription information of the patient in the server. The electronic prescription sharing system and sharing method can separate medical treatment and drug sales through sharing of prescription information, can improve the right to select on one's own in purchasing prescription content and selecting medical treatment service, are beneficial to realizing efficient operation and full competition of various social organizations, and fully utilize the existing social resources can regulate the state of the industry, and can protect the interests of patients.

The invention discloses a query and statistical system for drug sale. The system is composed of a query and statistical unit and a data storage unit. The query and statistical unit consists of an inventory inquiry module, a drug expiry date inquiry module, a hard-to-sell drug inquiry module, a purchase unit ranking module, a drug sales ranking module, a monthly purchase-sell-stock report module, and a drug flow recording module. According to the system provided by the invention, the data storage unit stores all data information during processes of drug storage, delivery, selling, sales returning, and breakage and the query and statistical unit inquires all information during the drug selling process within designated time, so that all links of drug management can be managed effectively. Therefore, the management efficiency and the accuracy during the management process can be improved substantially.

The invention discloses a drug classification management data analysis system. The drug classification management data analysis system includes a division module, a drug sales volume statistics module, a temperature prediction and comparison module, a cloud server and a display terminal, wherein the division module is connected with the drug sales volume statistics module; and the cloud server isconnected with the temperature prediction and comparison module, the drug sales volume statistics module and the display terminal. The drug classification management data analysis system calculates the environmental mutation coefficient by classifying and counting the sales volume of all kinds of drugs in each pharmacy in each region, obtains and compares the outdoor environment information of theprevious year and the next half a month of the current year, and deduces the drug supply demanded by each pharmacy according to the environmental mutation coefficient and the sales volume of drugs inthe previous year, thus improving the drug supply efficiency and realizing reasonable management of drug supply.

A drug traceability system provided by the present invention comprises a drug database, a production information management module, a quality information management module, a storage information management module, a sale information management module and a data terminal module, wherein the drug database is used for enterprises to upload the information of drugs to a server after the drugs are produced and adjust the drug information at any time, the production information management module is used to record the relevant information of the production equipment, the raw materials and the production technologies of the enterprises during a production process, the quality information management module is used to record the relevant information of the drug quality analysis and the quality control, the storage information management module is used to record the drug warehouse-in, warehouse shifting and warehouse-out relevant information, the sale information management module is used to record the relevant information during a drug sale process, and the data terminal module is used for the data pre-processing and the result query. The drug traceability system enables the visualization level of a drug supply chain to be enhanced and the drug traceability and product quality to be improved.

A method for mining user value of medicine purchased by users based on big data analysis is disclosed in the inventon. The method includes the following steps: S1, firstly, user interaction units, a member rank analysis system and a member classification system are respectively established in the whole member drug purchasing system, each time a member consumes and buys drugs in an Internet pharmacy, the types and prices of the drugs are stored in a large drug purchasing database through a storage module, and the system management module records the time when the member purchases the drugs andtransmits the records to the large drug purchasing database, which relates to the technical field of drug sales. A method for mining user value based on big data analysis of user purchasing medicine,the invention realizes the fast classification of the members according to the big data, achieves the purpose of mining the value of the members according to the members of different categories, realizes the mining of the drug purchase information of the members to increase the number of the members' re-purchase, thereby greatly facilitating the drug sales work of the Internet pharmacy.

The invention relates to the field of computer technology, in particular to a method for prohibiting expired drug sales based on POS collection. According to the method, retail units are involved; after a warehousing entry is newly added and a supplier unit is selected, the quantity, batch number, production date, saving after the effective date and review of drugs are input, and inventory data ofthe input drugs is generated. During POS collection, a one-dimensional barcode technology is adopted to recognize drug data, the drug batch number is selected, and meanwhile a system automatically judges whether the drugs are expired; and sales of the expired drugs is controlled to be prohibited through the system, and monitoring of drug quality management by the Food and Drug Administration is realized. The method for prohibiting expired drug sales based on POS collection can be applied to a drugstore for drug quality management.

The invention discloses a method for forecasting drug regional demand based on an association map and a neural network. The method includes the following steps: S1, firstly, a sales information miningmodule and a sales information clustering module are respectively established between the sales data association atlas database and the system management module, then people can interact with the system management module through the user interaction unit, and people can control the sales information mining module to mine the sales data information in the sales data association map library throughthe system management module. The invention relates to the technical field of drug selling. The method for forecasting drug regional demand based on an association map and neural network utilizes thespatial information and time information in the drug sales data to predict the future sales of drugs in the local drug sales region, grasp the regional characteristics of drug sales, and obtain moreaccurate forecasting results, which is conducive to the regional sales of drugs on the Internet.

The invention discloses a medicine combination recommendation method. The medicine combination recommendation method comprises the following steps: obtaining the purchase probability of each first medicine combination; obtaining business information of each first drug combination, wherein the business information comprises at least one of an inventory of the first drug combination and a profit ofthe first drug combination; determining a to-be-recommended medicine combination according to the purchase probability and the business information; and outputting the recommendation information of the to-be-recommended medicine combination. The invention further discloses a medicine combination recommendation device and a computer readable storage medium. According to the technical scheme, the appropriate drug combination is determined according to the probability that the user purchases each drug combination and the commercial requirements of the merchant for each drug combination, and the drug combination is recommended to the user, so that the demand of the user for purchasing drugs is met, the purpose of promoting drug sales is achieved, and the commercial requirements of the merchantfor drug inventory, profit and the like are met.

The invention discloses a drug association graph construction method based on network science and a convolutional neural network. The method includes the following steps that: feature extraction is performed on drug information, and a function association network between drugs is constructed through a convolutional neural network method on the basis of initial drug classifications given by pharmacists; a drug co-sale association network is constructed through a network science method on the basis of drug sales data; and the function association network and the drug co-sale association networkform a two-layer composite network, and comparison analysis is performed through the network science method, and a complete drug association graph is obtained; and the graph is visualized by means ofdimensionality reduction and graph embedding. With the drug association graph construction method based on the network science and the convolutional neural network of the invention, drug association relations can be automatically extracted from the drug sales data accurately and efficiently; and the association graph of drugs can be visually displayed, and users can know the drugs at a glance.

The invention provides a drug sales supervision system and method, and aims to solve the technical problem that an existing drug circulation mode difficultly supervises flow directions and sales situations of drugs. The system comprises a producer server, a regional merchant server and a regional drug supervision department server, wherein the producer server is used for sending drug electronic supervision codes to the regional drug supervision department server and sending drug reuse codes to the regional merchant server; the regional merchant server is used for receiving the drug reuse codes sent by the producer server and sending drug electronic supervision codes to the regional drug supervision department server; and the regional drug supervision department server is used for receiving the drug electronic supervision codes sent by the producer server and the regional merchant server. On the first aspect, the convenience is brought for drug sales; on the second aspect, scientific decisions can be made for business operations of production, sales and the like; and on the third aspect, drug supervision departments also can effectively supervise drug sales.

The invention discloses an intelligent pharmacy system, belonging to the technical field of pharmacies. The system comprises a mobile terminal function system and a pharmacy function system, wherein the mobile terminal function system comprises a member management system, a shopping cart management system, a payment management system, a commodity advertisement system, an order management system, abackground management system and a distribution management system; and the pharmacy function system comprises a card-swiping charging management system and a financial management system. According tothe intelligent pharmacy system, the mobile terminal function system is arranged, so the advanced technology of the mobile internet can be fully realized, a medicine purchaser is connected with a pharmacy, and the pharmacy is helped to better provide professional services to the user; online and offline sales are realized by using an Internet-based member management method and an Internet-based marketing method; and the pharmacy is managed by cooperative usage of the pharmacy function system for drug purchase management, drug sales management, drug inventory management, related document queryfunction reports and other function systems, so management efficiency can be improved.

The invention discloses a shared medicine box. An outer cover is provided with an operation screen, a sliding block is freely moved by the sliding block and a sliding rod, a motor is fixed on the sliding block, a rotating disc and a protrusion are arranged on the motor, a central shaft is arranged in a cassette, and a coil spring and a rotary buckle are connected at both ends of the central shaft.A universal wheel is arranged at the lower end of the casing, and a scanner is arranged on the side. The scanner is used for scanning a code to input the drug information, which is convenient and quick and does not easily make mistakes, and the universal wheel and a clamping board are arranged at the bottom of the box to facilitate the movement and fixation of the box. A condition can be input through the operation screen, the box undergoes intelligent analysis and recommends drugs or guides for medical treatment, and convenience is provided for disease treatment. The box uses the sliding block to position a medicine, greatly reduces the complexity of equipment and facilitates the reduction of manufacturing costs. A variety of payment methods are available for all types of people. Remotecontrol in a background provides convenience for management. The cost of drug sales is reduced, the price of drugs is reduced, and the economic burden of drug purchasers is relived.

The invention discloses a drug online sales management system and a drug sales method using the same; the system comprises a first client terminal, a second client terminal, a third client terminal, a wireless network, and a merchant terminal. A client login module, an identity verification module, a medicine data module, a medicine ordering module, a medicine payment module and a background processing module are arranged in the first client terminal; the merchant terminal is internally provided with a medicine order processing module and an after-sales processing module. According to the drug online sales management system and the drug sales method using the same, drug data in the display area can be viewed in the first client terminal, the second client terminal and the third client terminal, wherein the data dynamically changes along with screening conditions such as gender, age group, store grade, store business circle, indication and the like; and then the center map depicts coordinate points of chain drugstores in the urban area, and names of the drugstores and coordinate distribution conditions of surrounding buildings can be displayed after the center map is amplified into the map.

The embodiment of the invention discloses a drug supervision method and device based on a block chain, a server and a medium. The method comprises the following steps: obtaining drug related information uploading requests of a drug manufacturer user, a drug distributor user, a pharmacy user and a logistics company user, uploading circulation information of drugs in each link to a block chain, verifying drug information of two associated nodes according to an intelligent contract, and when a verification result is abnormal, sending warning information to related users. Through the technical scheme of the embodiment of the invention, multi-party collaboration of drugs of drug manufacturers, drug dealers, pharmacy users and logistics companies can be realized, information in links of drug production, drug circulation, drug sales, logistics distribution and the like is stored in the block chain, all parties jointly maintain the block chain system, data cannot be changed randomly, and the drug supervision user can perform full-process drug tracing on the target drug and respond to abnormal information in time, so that drug supervision is more intelligent.

The embodiment of the invention provides a medicine sales reward method and system. The method comprises the following steps: creating a sales reward configuration platform; wherein the platform can be configured according to a reward scheme; and configuring a corresponding reward scheme in the platform according to the actual sales scheme of the medicine, and then obtaining a medicine sales reward result output by the platform. According to the embodiment of the invention, multiple reward schemes are configured on the sales reward configuration platform, so that the pharmacy sales can obtain the drug sales reward result output by the platform after configuring the corresponding reward scheme in the platform according to the actual sales scheme of the drug, and therefore, the targeted development rule configuration content of each reward scheme is not needed; code redundancy is reduced, and system reusability is higher.