72 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 relates to the technical field of internet of things and intelligent control, and provides a medicine distribution device based on the internet of things. An existing medicine distribution system mainly depends on manual operation or single automatic equipment, so that the efficiency and precision in the distribution process are low, the medicine identification technology bureau is limited to simple package bar code scanning, and identification and distribution of unpackaged medicines are difficult to process. According to the multi-modal data fusion technology, two-dimensional images, three-dimensional forms and spectral data are combined, medicine is accurately recognized, and automatic grabbing and accurate distribution are achieved through the mechanical arm and the force feedback control device. And the control layer adopts an inverse kinematics algorithm, a path planning algorithm and fuzzy logic control to ensure accurate operation and safe grabbing of the mechanical arm. The system also utilizes a reinforcement learning algorithm to dynamically optimize a drug distribution strategy, and improves the accuracy and flexibility of the distribution process through a real-time feedback mechanism.

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 provides a full-scene intelligent risk early warning system for a drug circulation process and a use method thereof, and relates to the technical field of drug circulation risk early warning. Identification code configuration is performed on drugs, a drug circulation evaluation coefficient is calculated, risk circulation judgment is performed on drug identification information corresponding to a preset circulation link; sorting the medicine circulation evaluation coefficients according to preset circulation links, calculating a link state change difference value, determining corresponding preset risk level information, and performing preliminary early warning; the method comprises the following steps: carrying out synchronous grade labeling on a preset circulation link, obtaining a grade labeling link, calculating a risk monitoring frequency coefficient, adjusting a risk monitoring frequency, calculating a risk grade change coefficient, judging grade change, carrying out corresponding grade risk early warning, and obtaining depth early warning information. Real-time monitoring and accurate early warning of the whole medicine circulation process are achieved through intelligent and automatic means, and the safety and efficiency of medicine circulation are 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 traditional Chinese medicine analysis, and discloses a codonopsis pilosula root traditional Chinese medicine in-blood pharmacodynamic substance mass spectrometry imaging method and application thereof, and the method comprises the following steps: S1, pharmacodynamic research and serum drug chemical analysis of codonopsis pilosula treatment diseases: (1) establishment of an animal model: taking a spleen deficiency model as an example, (2) serum drug chemical analysis, and (3) establishment of an animal model: taking a spleen deficiency model as an example; and S2, researching the distribution of the blood-entering components in the traditional Chinese medicine. Differential distribution of various medicinal effect substances in different tissues of the plant is accurately identified and positioned by utilizing a mass spectrum imaging technology, and deep mass spectrum imaging analysis is quickly performed on the tissues of the target micro-region, so that the type and content information of the components entering the blood is obtained; according to the technology, space metabonomics is added, and the whole action mechanism of the codonopsis pilosula for treating diseases is explored, including codonopsis pilosula pharmacodynamics research and searching of pharmacodynamic substance components and spatial distribution of the pharmacodynamic substance components in codonopsis pilosula roots.

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.

To automatically recognize the orientation, posture, shape, size, kind, use period and other properties of a medicine and stores the medicine with a high degree of freedom.SOLUTION: A medicine supply device 1 comprises a recognition unit 300 and a storage unit 500. According to a size included in the properties of a medicine recognized by the recognition unit 300, a storage area is set at the time of storage. Medicines are stored in the storage unit 500 with association between identification information of the medicines and their storage areas. In addition, the medicine supply device 1 has a determination processing unit which can determine whether a medicine can be handled on the basis of the properties of the medicine recognized by the recognition unit 300.SELECTED DRAWING: Figure 1

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 utility model discloses a medicine identification device which comprises a base and a tray arranged on the upper side of the base, a medicine collector is arranged on one side of the tray, a medicine collecting groove is formed in the medicine collector, a medicine outlet is formed in the front side of the medicine collector, and an opening is formed in the side, facing the tray, of the medicine collecting groove. The tray is used for putting the zero-opening medicine, after the zero-opening medicine is recognized, the medicine is conveyed into the medicine collector by inclining the tray, and then the medicine is collected into a packaging bag or a packaging box through an opening in the front side of the medicine collector, so that the medicine putting efficiency and the medicine collecting efficiency are improved.

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 rapid medicine identification method based on a cloud platform, and belongs to the technical field of medical informatization, and the method comprises the following steps: medicine data collection, medicine data analysis and processing, cloud platform construction, application program design, system test and optimization, and online release. Data are uploaded to the cloud end through the cloud platform and processed, doctors, patients and pharmaceutical enterprises can more conveniently and quickly obtain related information of drugs, including drug names, specifications, indications, usage and dosage, drug inventory and the like, drug identification codes can be quickly identified, data sharing can be realized on different devices, and meanwhile, the system is more convenient to use. In addition, the system can also monitor and trace the medicines, timely find problems and take measures, so that the safety and effectiveness of the medicines are improved, and finally, based on a quick medicine identification method, a pharmaceutical enterprise can also realize digital management and control, improve the production efficiency and reduce the cost, so that higher commercial value is obtained.

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 embodiments of the present disclosure disclose information interaction methods, devices, electronic devices and computer-readable media. A specific implementation of the method includes: receiving drug order information submitted by a user, wherein the drug order information includes a user identifier, an order type and at least one drug information; matching an alternative identifier corresponding to the user identifier from an alternative identifier group stored in a drug information system; in response to a successful match, selecting a drug association identifier group that matches the order type from a drug association identifier group stored in the drug information system; transcoding the drug identifier of at least one drug information included in the drug order information through the drug association identifier group to obtain the transcoded drug order information; and obtaining drug order processing information corresponding to the transcoded drug order information. This implementation achieves unified monitoring of drug information during drug circulation, and improves the efficiency of monitoring drug circulation.

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.

This invention provides a UV spectroscopy apparatus and method for controlled drug waste diversion detection. The spectroscopy apparatus employs sample cells which have optimized optical path length such that the measured maximum absorbance of the drug is less than the detection limit of the system. Hence the full unsaturated absorption spectrum of the drug is revealed in the UV wavelength region from 230 nm (or even down to 195 nm) to 400 nm. This full spectrum analysis improves the specificity for drug identification and the accuracy for drug concentration verification. The spectral library of the apparatus comprises the spectra of common controlled drugs, excipients, as well as typical diluents, which enables the identification of controlled drugs from different manufacturers and / or diluted with different types of diluents.