57 results about "Drug identification" patented technology

The invention provides a drug identification information intelligent association method and system based on multi-source data fusion. According to the method, firstly, multi-source heterogeneous data generated in the medicine circulation process is obtained, then key information elements printed on the surface of a medicine package are recognized, meanwhile, a unique identifier bound with the medicine identity is extracted, and then a dynamic tracking link of a medicine transportation path is established; then cross-modal association matching is carried out on the key information element, the unique identifier and the dynamic tracking link to generate a dynamic mapping relation, finally the consistency of the dynamic mapping relation is verified, and the verified dynamic mapping relation is synchronously updated to a supervision terminal of a medicine circulation link. According to the technical scheme provided by the invention, the identification precision and timeliness of risks such as package tampering and path forgery are improved, the abnormal omission ratio caused by data acquisition errors or artificial tampering is reduced, and the reliability of cross-modal data collaborative verification is enhanced.

The invention provides a drug identification information efficient query method and system based on distributed cache. The method comprises the following steps: firstly, receiving and analyzing a drug identifier query request to generate a dynamic cache routing key, then positioning a target cache node, then matching a cache data block corresponding to a drug unique code in the target cache node, if matching succeeds, extracting a drug full life cycle record in the cache data block, and sending the drug full life cycle record to the target cache node; if the matching fails, initiating a cross-node retrieval request to the drug block chain database to return drug source data, splitting the drug source data into a core attribute set and an extended track set, and finally executing a dynamic combination operation on the core attribute set and the extended track set to generate a drug tracing result set and returning the drug tracing result set to the user terminal; according to the technical scheme provided by the invention, the query fluctuation defect of a single storage architecture is eliminated from the source, so that the whole system simultaneously meets three drug traceability core requirements of high concurrency, cross-mechanism and tamper-proofing.

The invention discloses a lung squamous cell carcinoma drug discovery method and system based on disturbance response scanning analysis, and belongs to the field of biological medicines.The method comprises the steps that lung squamous cell carcinoma protein expression profile data is downloaded and preprocessed, a robust network module is constructed and multi-scale analysis and evaluation are conducted, and drug genomic data are obtained based on drug genomic data. Predicting the drug sensitivity of the patient by using machine learning, and generating a DRN through difference analysis of the drug sensitivity; predicting drug-target protein binding affinity in combination with deep learning, quantifying node sensitivity through a PRS technology, calculating a DPI disturbance score and ranking drug priorities; high-ranking drugs are screened through comprehensive sensitivity analysis and literature investigation; a drug for a lung squamous carcinoma cell line is screened out through a pre-experiment and is relocated. According to the framework developed by the invention, by integrating proteomics, pharmacogenomics and dynamic network analysis, systematic analysis is provided for relocation drug identification of lung squamous cell carcinoma, and good news is brought to treatment of lung squamous cell carcinoma.

The invention discloses an automatic medicine identification system based on computer vision, and relates to the technical field of computer technology and artificial intelligence, and the system comprises a feature extraction module which is used for extracting an intrinsic identity vector and a degradation state vector from an obtained digital image of a to-be-identified medicine; the identity recognition module is used for generating an identity recognition result of the medicine according to the intrinsic identity vector and a preset classifier network; the quality evaluation module is used for generating a quality quantitative score of the medicine according to the degradation state vector and a preset degradation tolerance threshold value; and the risk discrimination module is used for generating a shoddy drug risk discrimination clue according to the degradation state vector, a preset certified product degradation mode library and a preset mode difference threshold. According to the invention, through a unique confrontation training mechanism, the system can respectively extract the characteristics representing the inherent identity of the medicine and the characteristics representing the appearance degradation state of the medicine from a single image, and the accuracy and robustness of recognition are greatly improved.

The invention relates to the field of large model detection, and particularly discloses a privacy calculation-based drug identification, detection and classification method and system, a terminal and a medium, and the method comprises the steps: training a local drug identification, detection and classification model by using a local drug data source; transmitting model parameters of local model training to a federated learning center; the federated learning center performs aggregation calculation according to the model parameters sent by the providers to obtain globally optimized model parameters, and feeds back the globally optimized model parameters to the providers; and training the local model again by each provider based on the globally optimized model parameters until the local model converges, and detecting and classifying the target drug by using the trained local model. According to the invention, on the basis of not leaking drug data privacy, multiple data resources are integrated, and the accuracy of drug identification, the reliability of detection and the scientificity of classification are improved.

The invention relates to the field of intraoperative medication, and particularly discloses an automatic intraoperative medication management device based on an HIS system and a control system thereof.The automatic intraoperative medication management device comprises a database module used for inputting and storing intraoperative medication names and administration routes conventionally used in a hospital to form an intraoperative medication database; the system docking module is used for docking with an HIS (hospital information system) of a hospital, and can automatically obtain and display the intraoperative medication advice of the patient from the HIS by inputting the hospitalization number of the patient; according to the invention, through the intelligent identification module, by using a scanner and an intelligent identification technology, accurate checking of medicine carried by a patient in an operation is realized, the medicine use risk caused by wrong medicine identification is effectively avoided, the AI medicine use risk assessment module uses an advanced AI algorithm to comprehensively analyze the medical record, the allergy history and the current medicine use condition of the patient, and the accuracy of the medicine use risk assessment is improved. The medication risk is automatically evaluated, a scientific decision basis is provided for medical staff, and the medication safety is further improved.

The invention relates to the technical field of blockchain traceability, in particular to a blockchain-based drug storage traceability and search system, which comprises an identification information generation module, an on-chain drug identification module, a lattice mapping reading module, a state field verification module and a chain log right confirmation module. According to the method, the drug approval number, the drug general name code and the GTIN code are spliced into the unified identification reference string and are subjected to code verification, and the drug attributes are extracted and consistent matching is completed in combination with an on-chain data positioning mechanism, so that the accuracy of drug identity tracing is effectively guaranteed; the method comprises the following steps: extracting an inventory grid position state, screening legal storage information to realize real-time state verification and available grid position identification, establishing a current binding relationship through terminal number cross comparison and state field verification, realizing dynamic management of an actual storage state of a medicine, enhancing traceability, verifiability and right verifiability of the medicine in a storage link, and improving the efficiency of the medicine storage. And the transparency and accuracy of the whole medicine storage and search process are improved.

The present invention discloses a highly reliable method for identifying drugs based on the fusion of image, RFID and voice multi-source data. The main content of this method is as follows: First, the user provides a voice command to the robot, and the robot obtains the drug name information through voice recognition and enters the image recognition stage. In the image recognition stage, after image enhancement and RGB extraction of the image in front of the robot, the position information of the corresponding drug is obtained, and then the position information is sent to the robot and enters the RFID recognition stage. In the RFID recognition stage, the robot grabs the drug according to the target drug position information and places the drug on the RFID reader for identification. After ensuring accuracy, it enters the drug delivery stage. In the drug delivery stage, while delivering the drug to the user, the robot uses voice synthesis to inform the user of the drug name, usage dosage and properties as a third layer of guarantee. Through the present invention, highly reliable automatic identification of drugs can be achieved, thereby helping the elderly and disabled with limited mobility to take their medicine on time.

The application discloses a kind of narcotic drugs whole-process traceability management method and system, specifically related to medical information technology field, the method includes: obtaining the multimodal perception data generated in the circulation process of narcotic drugs, at least including operator identity data, drug object identity data, drug identification data, weight change data and operation image data;Multimodal perception data is input into the dynamic risk score model of edge computing node, the model extracts the behavior fingerprint characteristics of operator based on time series attention mechanism and outputs dynamic risk score;Determine whether dynamic risk score exceeds preset threshold, if exceeds, generate intercept instruction, otherwise generate release instruction and append storage traceability record.The application realizes the intelligent closed-loop traceability management of narcotic drugs whole process by multimodal fusion verification and adaptive risk assessment, effectively improves the real-time nature and data integrity of supervision.

This utility model provides a drug identification device, relating to the field of dispensing device technology. The drug identification device includes: a first visual recognition component, a tray, a conveying module, a turntable, a second visual recognition component, and a controller. The drug identification device provided in this embodiment uses the first visual recognition component to acquire the quantity, type, and position of the drugs on the tray. This allows the controller to control the conveying module to accurately pick up and move the drugs to the turntable. By installing a second visual recognition component on the side of the turntable, the device captures and identifies the drug's name, appearance, and dosage, enabling accurate and automatic drug identification, saving manpower, avoiding errors in drug use, and preventing risks to patient treatment outcomes.

The present invention relates to the field of data processing technology, and discloses a drug data matching method, device, equipment and storage medium. By matching the drug identification information in the drug input data from the drug standard library, if no match is found, the drug production information is continued to be used to match from the drug standard library. If a match is found, the specification information in the input data and the matched standard drug data is standardized and then matched. If the match is consistent, it is determined that the input data is successful, otherwise, the match fails. The above method is used to achieve drug data matching. Since two matches are set, the parameter dimensions of each match are different, thereby improving the accuracy of drug data matching correction, while also reducing the amount of data processed at one time, and improving matching efficiency. In addition, the present invention also relates to blockchain technology, and drug data can be stored in the blockchain.

The embodiment of the invention discloses a medicine identification method and device, equipment and a storage medium, and relates to the technical field of image identification, and the method comprises the steps: obtaining a two-dimensional surface image and three-dimensional contour data of a medicine; and analyzing the two-dimensional surface image based on a feature extraction rule to extract surface structure features of the medicine. And converting the three-dimensional contour data into spatial structure characteristics. And fusing the surface structure features, the spatial structure features and the obtained physical features and text features of the medicine to obtain joint features. And performing multi-label classification on the joint features by using a drug classification model to determine category information corresponding to the drugs. By performing feature extraction on the two-dimensional surface image and the three-dimensional contour data, the structural features of the medicine can be obtained more comprehensively and meticulously. By combining the physical characteristics and the text characteristics of the medicine, the combined characteristics covering the information of multiple dimensions can be obtained. And the accuracy of medicine identification is effectively improved.

This application discloses a portable drug detection device and method, relating to the field of drug identification technology, with the main objective of addressing the problem of poor detection effectiveness in existing drug testing methods. It includes: a Raman spectroscopy component, an ion mobility spectrometry component, a processor, a power module, a display component, and a sample inlet module disposed on the ion mobility spectrometry component. The processor is electrically connected to the Raman spectroscopy component, the ion mobility spectrometry component, and the display component, and is used to identify and process the spectra acquired by the Raman spectroscopy component and the ion mobility spectrometry component to obtain drug detection results. The power module is electrically connected to the Raman spectroscopy component, the ion mobility spectrometry component, and the processor, and is used to provide power. The display component is used to display the drug detection results. The sample inlet module is used to insert sample test strips.

This invention provides a pharmacy search device, a pharmacy search method, and a pharmacy search program that provide useful information about the possibility of dispensing medications by pharmacies. [Solution] In a communication system S connected to a network NW, a pharmacy reservation server 1 is connected to one or more inventory systems 2, multiple pharmacy terminals 3, multiple user terminals 4. The pharmacy reservation server acquires drug identification information to identify the drug to be dispensed, and based on the dispensing information stored in a dispensing information storage means that stores dispensing information indicating the dispensed drug and the dispensing pharmacy, it searches for pharmacies that have a history of dispensing the drug identified by the acquired drug identification information, and transmits search result information indicating the search result to the terminal device.

The invention discloses a drug production quality identification method and platform based on big data, and relates to the technical field of drug identification. For each batch of drugs, equipment fluctuation information in the production process is acquired, and equipment fluctuation values are calculated; acquiring medicine raw material change information in the production process and calculating a raw material change value; obtaining production scale information in the production process, and calculating a production scale value; and according to the equipment fluctuation value, the raw material change value and the production scale value, calculating a quality identification change value, and according to the quality identification change value, judging whether to change the production quality identification times of the medicines in the corresponding batch. In this way, the identification frequency can be adjusted according to the actual volatility, process complexity or potential risk dynamics and the like of different batches of products; according to the dynamic identification strategy, high-risk batch identification can be sufficient, quality hidden danger omission is avoided, and the production flexibility and the quality guarantee capability of the big data quality identification method can be further improved.

The present application relates to a kind of drug rapid detection method, equipment and medium based on photonic crystal image, comprising: image pre-processing, to locate the position of photonic crystal in image and cut image, so that only photonic crystal is left in the image after cutting;Extract the color feature vector of the photonic crystal, and carry out dimension reduction processing;The color feature vector after dimension reduction is converted, identified and compared based on support vector machine, and the drug identification of the to-be-measured body fluid is completed.The present application is based on the color difference of different drugs and photonic crystal after reaction, judges what kind of drug, such as amphetamine, pseudoephedrine, chloroephedrine, methylcathinone or methamphetamine, contained in the to-be-measured liquid by comparing with standard spectrum, fast, low cost, mass detection, low equipment cost.

The invention discloses a visual detection method of a paper-based colorimetric sensor array chip for medicine authenticity identification. A colorimetric sensor array is composed of a compound formed by a bipyridine derivative and a dye through electrostatic interaction. The invention also discloses a synthesis method of the bipyridine derivative. During detection, optical signal changes after the sensor array reacts with the antibiotics are obtained through image RGB analysis or absorbance spectrophotometry analysis, high-flux and high-sensitivity identification of various antibiotics is achieved through a pattern recognition algorithm, and the accuracy rate can reach 100%. The invention further provides a portable sensor based on a paper base and matched image analysis software, and on-site rapid detection and authenticity identification of the antibiotics are achieved. The method is simple to operate and low in cost, and has a wide application prospect in the fields of food safety and drug anti-counterfeiting.

The application discloses a drug production quality identification method and platform based on big data, relates to the technical field of drug identification, and comprises the following steps: for each batch of drugs, obtaining equipment fluctuation information in the production process to calculate an equipment fluctuation value; obtaining drug raw material change information in the production process to calculate a raw material change value; obtaining production scale information in the production process to calculate a production scale value; calculating a quality identification change value according to the equipment fluctuation value, the raw material change value and the production scale value, and judging whether the production quality identification frequency of the corresponding batch of drugs needs to be changed according to the quality identification change value. In this way, the identification frequency can be adjusted according to the actual fluctuation, process complexity or potential risk of different batches of products, and the dynamic identification strategy can ensure that high-risk batches are identified sufficiently and quality hidden dangers are not omitted, so that the big data quality identification method can be further improved in production flexibility and quality guarantee capability.

The embodiment of the invention provides a medicine identification method based on AI visual identification and a medication guidance system, and the method comprises the steps: carrying out the multi-angle image collection of a passing medicine through a plurality of image collection devices disposed on the side surface, the top surface and the bottom surface of a target transmission region when the medicine passes through the target transmission region of a conveyor belt, the conveyor belt is provided with a transparent belt; carrying out drug traceability code identification on the collected image; and if the identification of the traceability code of a certain drug fails, extracting the pictures of the target drug in the images at all angles, performing similarity comparison with the drug image database through the AI image identification model, determining the drug with the highest similarity as the target drug, and outputting the drug traceability information of the target drug. And the integrity of image information is improved through multi-angle image acquisition. Traditional bar code recognition and AI image recognition are combined, the robustness and the fault-tolerant capability of the system are enhanced, and the medication safety and the reliability of the tracing process are guaranteed.

The embodiment of the invention provides an intelligent medical insurance fund dynamic supervision method and system. The intelligent medical insurance fund dynamic supervision method and system can solve the problems of data vulnerabilities and low efficiency in supervision. The method comprises the following steps: acquiring medicine identification information of a medicine corresponding to a target prescription, and searching first contour feature information corresponding to the medicine in a preset medicine information base according to the medicine identification information; a perspective imaging device is controlled to collect first particle accumulation image information of the medicine outer package in the first state; a perspective imaging device is controlled to collect second particle accumulation image information of the medicine outer package in a second state; calculating according to the first particle accumulation image information and the second particle accumulation image information to obtain second outline feature information of the medicine; and comparing the first contour feature information with the second contour feature information, and generating alarm information when the first contour feature information is not matched with the second contour feature information.

The present invention discloses an intelligent drug supply and dispensing device for a pharmacy, comprising: a drug supply device and a drug dispensing device. The drug supply device is provided with a drug identification mechanism and a drug conveying mechanism. The first drug identification mechanism is arranged on a workbench, and the drug conveying mechanism is arranged on one side of the workbench. The drug dispensing device is arranged on one side of the drug conveying mechanism. The drug dispensing device is provided with a drug dispensing box body. The drug dispensing box body is provided with a detection device for detecting the position of the drug. A second drug identification mechanism is arranged at the entrance of the drug dispensing box body. A rolling device is arranged inside the drug dispensing box body. A group of drug conveying devices and a group of drug placement areas are arranged around the rolling device. The entrance of the drug conveying device is connected to the drug conveying mechanism. A drug placement table is arranged on one side of the drug dispensing box body. By integrating the drug supply device and the drug dispensing device, the present invention conveys the drugs to be shelved to the drug dispensing device through the drug supply device, realizing automatic drug supply and automatic drug dispensing, which can not only ensure the correctness of drug dispensing, but also greatly improve the efficiency of drug dispensing.

The invention provides a drug target affinity prediction method and device, and a medium, and relates to the field of drug identification, the method comprises the following steps: obtaining three-dimensional structure data, and carrying out feature extraction to obtain geometric features and chemical features; fusing the geometric features and the chemical features through a geometric perception graph neural network to obtain compound features; decomposing the compound characteristics into drug characteristics and target characteristics; performing graph clustering on the drug features and the target features, and aggregating the atomic-level features into functional-level cluster features; performing statistical attention enhancement on the functional-level cluster features to obtain final features, splicing the final features, and performing fusion and dimension reduction through a multi-layer perceptron to obtain a global feature vector of the compound; and inputting the global feature vector of the compound into an affinity regression predictor, and predicting to obtain a binding affinity value between the drug and the target. According to the method, the accuracy and generalization of affinity prediction are effectively improved by comprehensively considering the three-dimensional structure and the overall statistical semantic information of the drug target.

The present disclosure relates to a dose detection system for use in combination with a medication delivery device. In one aspect, the system includes a module keyed to the device and including a sensor operable to detect the relative angular position of a sensed element attached to the medication delivery device. The system determines the type of medication contained by the device, and / or the type of device, based on the detected angular position of the sensed element. In another aspect, the dose detection system is used in combination with a medication delivery device including a dose setting member which rotates relative to an actuator during dose delivery. The dose detection system includes a sensor and is operable to detect the relative angular positions of a sensed element attached to the dose setting member during dose delivery and to determine the amount of dose delivered. Related methods are also disclosed.

The embodiment of the application provides a drug component identification method and related equipment, and belongs to the technical field of drug identification. The method comprises the following steps: obtaining preset drug sample data, including positive drug sample data and negative drug sample data, wherein the positive drug sample data comprises a first thin layer chromatogram, and the negative drug sample data comprises a second thin layer chromatogram; constructing a model training atlas set through the first thin layer chromatogram, so as to train a preset twin neural network model, and obtain a first twin neural network model; constructing a model test atlas set through the first thin layer chromatogram and the second thin layer chromatogram, so as to optimize parameters of the model in combination with the model training atlas set, and obtain a target neural network model; and inputting a to-be-identified thin layer chromatogram into the target neural network model for component identification analysis, and obtaining a component identification result. The embodiment of the application can try not to use control samples and control medicinal materials in drug identification, so that the economic, green and environmentally-friendly purposes are achieved.

To provide a new system, method, apparatus, and program.SOLUTION: A method includes: storing medicine identification information for specifying a medicine described in a prescription in association with prescription identification information for specifying the prescription; reading a prescription code corresponding to the prescription identification information or inputting information for specifying the prescription identification information; reading a medicine code corresponding to the medicine identification information attached to a package of the medicine; and referring to the stored information, and determining if the medicine identification information corresponding to the read medicine code and the prescription identification information corresponding to the prescription code correspond to each other, or referring to the stored information, and determining if the medicine identification information corresponding to the read medicine code and the prescription identification information specified by the input information correspond to each other.SELECTED DRAWING: Figure 8

The invention discloses a medication management method and system for an intelligent medicine chest, and the method comprises the following steps: S1, carrying out the cooperative starting of hardware; s2, data acquisition and primary processing; s3, carrying out data cross validation and identification confirmation; s4, intelligently dividing a storage area; s5, performing real-time monitoring and early warning on the period of validity; s6, generating and executing a personalized medicine dispensing scheme; s7, medicine taking process supervision and data recording. The medicine taking management system of the intelligent medicine box comprises a medicine box hardware control module; a data acquisition and identification module; a data storage module; a medicine box matching applet function module; an intelligent medical care platform web end function module; an intelligent analysis module; and a safety and maintenance module. According to the invention, through cooperative work of the image acquisition device, the spectrum analyzer and the RFID reader, drug information is acquired from multiple dimensions, and the accuracy of drug identification is greatly improved by using a deep learning algorithm and a professional spectrum comparison technology.

The application discloses a kind of injection drug identification methods based on machine vision, specifically comprising: the drug to be identified is placed in visual identification area;Rotating the drug to be identified and / or camera unit to switch the orientation of the feature identification point of the drug to be identified relative to the camera unit, so that the feature identification point of the drug to be identified falls into the visual capture range of the camera unit;The feature identification point image of the drug to be identified is captured by the camera unit;The drug information of the drug to be identified is identified according to the feature identification point image captured by the camera unit.The application also discloses an injection drug identification system and an intelligent dispensing equipment.The injection drug identification method, system and intelligent dispensing equipment provided by the application ensure that the feature identification point of the drug to be identified can be successfully captured by the camera unit for drug information identification by rotating the drug to be identified and / or the camera unit, and this identification method only needs to set a single camera unit, which can save cost and space.

Accurately identify chemicals from images containing the word "chemical". [Solution] The drug identification support system comprises an image acquisition unit that captures an image obtained by photographing a string of characters indicating a drug prescribed to an individual, and a drug name output unit that outputs the drug name of at least one drug string that matches a drug name in a drug master from among a group of multiple character strings recognized in the image, as a drug candidate identified in the image. The drug name output unit does not output the drug name of the drug string as a drug candidate if the drug name of the drug string is a pre-set non-output drug.

The present disclosure relates to a dose detection system for use in combination with a medication delivery device. In one aspect, the system includes a module keyed to the device and including a sensor operable to detect the relative angular position of a sensed element attached to the medication delivery device. The system determines the type of medication contained by the device, and / or the type of device, based on the detected angular position of the sensed element. In another aspect, the dose detection system is used in combination with a medication delivery device including a dose setting member which rotates relative to an actuator during dose delivery. The dose detection system includes a sensor and is operable to detect the relative angular positions of a sensed element attached to the dose setting member during dose delivery and to determine the amount of dose delivered. Related methods are also disclosed.

The application discloses a computer vision-based automatic drug identification system, and relates to the technical field of computer technology and artificial intelligence, and comprises the following modules: a feature extraction module, which is used for extracting an intrinsic identity vector and a degradation state vector from a digital image of a to-be-identified drug; an identity recognition module, which is used for generating an identity recognition result of the drug according to the intrinsic identity vector and a preset classifier network; a quality evaluation module, which is used for generating a quality quantification score of the drug according to the degradation state vector and a preset degradation tolerance threshold; and a risk screening module, which is used for generating a fake and inferior drug risk screening clue according to the degradation state vector, a preset genuine degradation mode library and a preset mode difference threshold. Through a unique adversarial training mechanism, the system can extract features representing the inherent identity of the drug and features representing the appearance degradation state of the drug from a single image, so that the accuracy and robustness of identification are greatly improved.