47 results about "Drug classification" patented technology

The invention relates to the technical field of microfluidic drug delivery, and discloses an oral drug precise delivery and curative effect evaluation system based on microfluidics. The system comprises a signal acquisition and processing module, an instance identification and feature extraction module, and a path generation and curative effect evaluation module. The signal acquisition and processing module continuously acquires multi-dimensional signals of oral drug delivery through the microfluidic sensing array, and the multi-dimensional signals are integrated into a unified data stream after real-time correction and structure standardization. An instance identification module identifies a delivery instance therefrom, extracts a temporal identity, a spatial location descriptor, and a drug classification identifier. The path generation module divides intervals in combination with the time identifiers, aligns the spatial information to the standard oral cavity model, and generates a drug delivery path time sequence record. And the curative effect evaluation module calculates the drug distribution density of the target area according to drug classification aggregation examples, generates a curative effect evaluation data set, and realizes the precision of drug delivery monitoring and curative effect evaluation.

The embodiment of the invention relates to the technical field of data processing, and provides a medicine classification method of a medical system and a related device, and the method comprises the steps: obtaining package bar code image data and specification image data of a newly stored medicine; performing image recognition on the package bar code image data to obtain first medicine classification information; performing character classification information identification on the specification image data to obtain second medicine classification information; comparing the first medicine classification information with the second medicine classification information to obtain a medicine classification information comparison result; and determining a drug classification result according to a drug classification information comparison result, so that auxiliary judgment can be performed in combination with identification of a drug specification and correct judgment of a package bar code in a drug package bar code data identification process, and the technical problem of drug classification error caused by bar code misidentification due to overexposure is avoided.

Methods, systems and apparatus are described for classifying one or more candidate molecule drugs in relation to one or more desired target conditions for use in downstream processing of drug optimization. A candidate molecule drug inference dataset is received for one or more molecule drugs, the candidate molecule drug dataset comprising data representative of a set of physiochemical values for each candidate molecule drug and a set of pharmacokinetic (PK) values associated with a dosage regimen and target in relation to each candidate molecule drug, and where each candidate molecule drug of the candidate molecule drug dataset is classified as a large molecule drug. For each candidate molecule drug of the candidate molecule drug inference dataset, the corresponding set of physiochemical values and set of PK values for the dosage regimen and target are applied to a machine learning (ML) model configured for classifying whether each candidate molecule drug meets one or more desired conditions associated with pharmacological or pharmacodynamic effects. The ML model is trained using an ML algorithm to train model parameters defining the ML model for classifying whether each candidate molecule drug meets the one or more desired conditions based on a training dataset comprising data representative of a plurality of molecule drugs, each molecule drug represented by a corresponding set of physiochemical values and a set of PK values associated with the dosage regimen and the target, and annotated in relation to corresponding pharmacological or pharmacodynamic effects, responses and / or values in relation to the desired conditions. A set of candidate molecule drugs satisfying the desired conditions is output for downstream processing of drug optimization.

An example system for detecting and quantifying drug and / or chemical interactions with a biological sample is provided. The system includes a detection instrument with computing capability. The system includes an assay device capable of receiving a biological sample. Introduction of the biological sample into the assay device results in a biological process by which fibrin and platelets may accumulate at a reaction zone of the assay device. The assay device is capable of receiving one or more chemical reagents and one or more drug reagents. The fibrin and platelets, and their associated signals, accumulated at the reaction zone of the assay device are usable to determine at least one of a drug presence, a drug class, a drug level in relation to a threshold, or a drug concentration, within the biological sample.

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.

The invention provides a traditional Chinese medicine compatibility prescription and application thereof. A four-type medicine classification system of'master, slave, ingredient and sum 'is adopted, the proportion of the master medicine is 50%, the proportion of the slave medicine is 25%, the proportion of the auxiliary medicine is 15%, the proportion of the sum medicine is 10%, the master medicine is a medicine aiming at core pathogenesis, the slave medicine is a medicine for assisting the master medicine or relieving side effects of the auxiliary medicine, the auxiliary medicine is a medicine for indirectly supporting the functions of the master medicine and the slave medicine, and the sum medicine is a medicine for coordinating the properties of the whole prescription. According to the traditional Chinese medicine compatibility prescription of'master, slave, compounding and mixing 'provided by the invention, the leading effect of the core medicine is highlighted and the synergistic effect of the auxiliary medicine can be considered by determining the function positioning and proportion of the master medicine, the slave medicine, the compounding medicine and the mixing medicine, so that the overall curative effect of the prescription is improved. A dynamic adjustment mechanism is emphasized, the medicine proportion and combination can be flexibly adjusted according to different stages of diseases and individual differences of patients, complex and changeable clinical requirements are effectively met, and the defect that roles are solidified in a traditional theory is overcome.

The utility model relates to the related technical field of transportation devices, in particular to a medicine classifying and transferring device. Comprising a base, universal wheels are installed at the lower end of the base, a protection structure is installed at the upper end of the base, a protection mechanism is arranged, and a push rod is installed at the upper end of the base; the protection mechanism comprises a protection box, an installation frame, a limiting ring, a connecting rod, a fixing bolt, a connecting groove, a connecting plate, a storage box, a sealing cover, a box door, a blocking frame, an air inlet fan, a support and a refrigeration piece, the installation frame is installed in the protection box through the limiting ring, the connecting rod and the fixing bolt, the installation frame passes through the interior of the protection box, the connecting rod penetrates through the limiting ring, and then the fixing bolt is fixed to the interior of the protection box. The connecting rod is fixed on the outer side of the protection box, the mounting frame can be mounted, and the fixing mode of the mounting frame mainly depends on the connecting rod, the limiting ring and the bolt, so that the connecting rod and the mounting frame can be easily dismounted only by loosening the fixing bolt during dismounting. By means of the design, a complex connection mode is avoided.

The veterinary treatment medicine classified storage device comprises a box body and a handle, a plurality of partition plates are evenly distributed in an inner cavity of the box body, a storage box is arranged at the tops of the partition plates, a fixing block is arranged on the front side of the storage box, a containing groove is formed in the front side of the fixing block, and the handle is arranged in the containing groove. Supporting plates are arranged on the left side and the right side of an inner cavity of the containing groove, fixing devices are arranged on the opposite sides of the two supporting plates, and control devices used in cooperation with the fixing devices are arranged on the opposite sides of the two supporting plates. The partition plate, the storage box, the containing groove, the supporting plate, a fixing device, a control device, a fixing groove and a protection plate are used in cooperation, and the problems that when an existing medicine box for veterinary treatment is used, a plurality of trays are usually arranged in an inner cavity of the box body, when medicine placed on the lower layer needs to be taken out, the tray on the upper layer needs to be taken out, and the medicine box is inconvenient to use are solved. And the medicine on the lower layer can be taken only when the medicine is taken, so that the taking process is relatively inconvenient.

The present invention relates to an intelligent drug classification system, which relates to the field of artificial intelligence technology. The system mainly includes: obtaining the outer packaging image of the drug to be classified through the graphic acquisition device; determining whether a drug identifier uniquely corresponding to the drug to be classified can be obtained according to the outer packaging image; if a drug identifier uniquely corresponding to the drug to be classified can be obtained, obtaining the detailed drug data corresponding to the drug identifier according to the drug database; if a drug identifier uniquely corresponding to the drug to be classified cannot be obtained, obtaining the instruction manual image of the drug to be classified; determining the corresponding detailed drug data according to the instruction manual image; processing the detailed drug data based on the user-defined classification basis to obtain the classification result corresponding to the drug to be classified.

The drug classification device (1) is equipped with a determination unit (64) that determines the type of drug based on an image captured by a first camera (131), and a return / classification unit (12) that classifies multiple types of drugs received in a mixed state in a first receiving unit (11) by type and stores them in a second receiving unit (14) based on the determination result by the determination unit.

The present application relates to the technical field of microfluidic drug delivery, and discloses a microfluidic-based oral drug precise delivery and efficacy evaluation system.The system comprises four modules of signal acquisition and processing, instance recognition and feature extraction, path generation and efficacy evaluation.The signal acquisition and processing module continuously acquires multi-dimensional signals of oral drug delivery through a microfluidic sensing array, and integrates the signals into a unified data stream after real-time correction and structural standardization.The instance recognition module identifies the delivery instance, extracts the time identifier, spatial position descriptor and drug classification identifier.The path generation module divides intervals in combination with the time identifier, aligns the spatial information to a standard oral model, and generates a drug delivery path time sequence record.The efficacy evaluation module aggregates instances according to drug classification, calculates the target area drug distribution density, generates an efficacy evaluation data set, and realizes the precision of drug delivery monitoring and efficacy evaluation.

The hierarchical classification management system based on the cardiology coronary heart disease drug library specifically involves the technical field of drug hierarchical classification management. The solution includes a data collection and processing module, a hierarchical classification module, a data analysis module, and an analysis visualization module. The data collection and processing module classifies and collects the classified data of all drugs taken to treat coronary heart disease in the current period of time. The hierarchical classification module calculates and outputs the i-th drug efficacy evaluation value YWL of all drugs in turn. i , the i-th drug classification index DJ i , optimization adjustment coefficient DT of the i-th drug i The data analysis module calculates all drugs and outputs the optimization adjustment coefficient DT of the i-th drug i The present invention realizes real-time updating of side effects, comprehensive consideration of drug interactions and individual differences, and dynamic adjustment of classification and grading management by arranging the i-th drug with a low value below the median.

The invention discloses a multi-mode intelligent child-mother medicine box which comprises a mother box body, a first child box and a second child box, an intelligent module used for displaying various data is arranged at the top of the mother box body, a dry storage area and a refrigerated storage area are arranged in the mother box body, and the dry storage area and the refrigerated storage area are filled with the first child box and the second child box respectively. Openings used for pushing the first sub-box and the second sub-box outwards are formed in one side of the dry storage area and one side of the cold storage area correspondingly, and opening mechanisms are arranged in the dry storage area and the cold storage area correspondingly and electrically connected with the intelligent module. A medicine classification mechanism is arranged above the dry storage area, a medicine conveying hole is formed in one side of the mother box body, a sealing mechanism is arranged on one side of the medicine conveying hole, the medicine conveying hole communicates with the medicine classification mechanism, and the medicine classification mechanism and the sealing mechanism are both electrically connected with the intelligent module. The design of the child box and the mother box is integrally utilized, the child box is convenient to carry, separated independent reminding is supported, the multi-mode recognition technology is integrated, the types and the number of medicines are automatically recognized, and intelligent medicine taking reminding is integrally achieved.

The application belongs to the field of drug classification management, in particular to a hospital pharmacy drug classification management device, which comprises multiple classification storage cabinets, transport vehicles and magnetic strips, the magnetic strips are attached to the ground, the bottom ends of the transport vehicles and the classification storage cabinets are provided with electric wheels and AGV navigation equipment, the front end of the classification storage cabinet is provided with a storage groove, the inner side of the storage groove is provided with multiple arrangement boxes, the inner side of the arrangement box is fixedly installed with a scissor type driving module one at one end, through the setting, the effects of mechanical medicine taking, medicine storage and classification storage cabinet directional movement are realized, the manual labor is greatly reduced, meanwhile, the pure mechanical operation and the final manual checking also reduce the occurrence of mistakes, the scissor type driving module one comprises two folding frames and an electric pull rod, by pulling the bottom end of the folding frame to make it merge, the folding frame is unfolded and lengthened, thereby completing the ejection work.

The invention discloses an AI-assisted hospital taboo and conflict drug warning system, which relates to the technical field of medical equipment, and comprises a data layer, a data processing layer, an AI monitoring and early warning layer and an interaction layer, and is characterized in that the data layer provides basic data and transmits the basic data to the data processing layer; the data processing layer trains a drug classification model based on the basic data and performs drug classification; the AI monitoring and early warning layer monitors the medicine preparation condition of a doctor in real time, carries out early warning if medicine conflicts exist in a medicine classification result, and continuously optimizes a medicine classification model at the same time; and the interaction layer presents the early warning as a warning to a doctor, and stores a warning record at the same time. The invention provides an auxiliary decision-making system based on artificial intelligence, which is used for automatically identifying drug conflicts and taboo and improving the safety of clinical medication.

A method and system for generating procurement plans for chain pharmacies based on big data, relating to the field of procurement management, is disclosed. The method includes: first, collecting historical sales data, real-time inventory data, and external environmental data to construct a multidimensional database; then, standardizing the data and constructing a drug classification matrix using a data mining model; next, using causal analysis to identify key factors influencing drug demand and establishing a weight matrix of demand influencing factors; calculating procurement parameters such as safety stock levels, economic order quantities, procurement trigger points, and procurement cycles based on this weight matrix; and finally, combining a supplier evaluation system to generate a procurement plan including a list of drugs to be procured, procurement quantities, procurement time, and supplier selection. This method, through multidimensional data analysis and causal relationship mining, achieves scientific and precise procurement decisions, improves procurement efficiency, and reduces inventory costs.

The invention relates to the technical field of respiratory drug delivery, in particular to an inhalation drug delivery device for the respiratory and critical disease medicine department, which comprises a box body and a suction nozzle arranged on the front side of the box body through a drug delivery pipe, and further comprises a drug classification treatment mechanism arranged in the box body, and the top of the drug classification treatment mechanism is connected to a drug adding pipe arranged on the top of the box body; the medicine classifying and processing mechanism is installed at the bottom of the machine body and used for classifying and processing different types of medicine, the conveying box is installed at the bottom of the medicine classifying and processing mechanism, connected with the medicine feeding pipe and used for conveying various kinds of medicine, and the problems that in the prior art, an inhalation medicine feeding device can only conduct inhalation medicine feeding on single vaporous or powdery medicine, and certain limitation exists are solved; the problems that medicine inhaled by a patient is not uniform and medicine attached and accumulated at a suction nozzle cannot be cleaned in time due to the fact that the medicine inhaled by the patient is not uniform and particle or block-shaped medicine contained in powdery medicine cannot be effectively treated in time and meanwhile the function of stirring the medicine is lacked are solved.

The invention discloses a drug classification method based on colloid AuNPs (at) AgCl and a soft voting model, and the method comprises the steps: preparing colloidal gold nanoparticles AuNPs based on a seed growth method; a colloidal AuNPs (at) AgCl solution with an AgCl activation layer is prepared; the method comprises the following steps: taking colloid AuNPs (at) AgCl as an SERS (Surface Enhanced Raman Scattering) substrate, and obtaining Raman spectrum data of a unitary drug and a binary drug; performing normalization processing and feature screening on the Raman spectrum data in sequence to obtain a feature set; and assigning a weight to each base classifier through a soft voting method, obtaining an integrated classifier, and classifying the unitary drugs and the binary drugs. According to the soft voting ensemble learning classifier, four base classifiers including an extreme random tree, a random forest, a support vector machine and XGBoost are integrated, the classifier can quickly classify and identify unitary drugs and binary drugs, and the classification accuracy is greatly improved.

This invention discloses an intelligent drug scheduling method and system based on drug classification and joint constraint solving, belonging to the field of pharmaceutical information technology. The method includes: 1. Classifying drugs into four categories according to dosing strictness: blood concentration-dependent, local-acting, on-demand, and circadian rhythm-dependent, with each category corresponding to a different drug scheduling strictness strategy; 2. Extracting the independent constraints and inter-drug constraints for each drug, and performing multi-source verification and confidence labeling on the interval requirements; 3. Jointly solving the drug scheduling time for all drugs using the user's lifestyle as an anchor point; 4. Performing four-dimensional verification of the drug scheduling scheme based on interval rationality, dosing conditions, drug compatibility, and executability; 5. Supporting dynamic adjustments such as missed doses, adding medication, and changing medications. This invention solves the problems of existing medication reminder products that independently schedule each drug, cannot detect interval conflicts, do not consider differences in drug classification strictness, and do not anchor to lifestyle, significantly improving the safety and executability of drug scheduling in multi-drug use scenarios.

(Task) Drugs can be classified regardless of whether drug data is registered. (Solution) The drug classification device (1) is equipped with a transport / classification unit (12) that receives drugs determined to have drug data corresponding to image data in the confirmed area (Ar11) of the second receiving section (14) for each type, and receives drugs determined not to have drug data corresponding to image data in the temporary determination area (Ar12).

The invention relates to the technical field of medicine storage, and discloses a medicine classified storage device which comprises a refrigerated cabinet and a cabinet door arranged on the refrigerated cabinet, a plurality of regularly distributed placing grooves are formed in the refrigerated cabinet, drawers are placed in the placing grooves, and a cold supply cavity is formed in the refrigerated cabinet and located at the top of the placing grooves; according to the invention, the plurality of regularly distributed placing grooves are formed in the refrigerated cabinet, and the drawable drawers are placed in the placing grooves, so that various medicines can be respectively stored in different drawers, the classified storage of the medicines is realized, and in the process of taking and placing the medicines, when one drawer is opened, the adjusting mechanism can be triggered, so that the medicines can be taken out of the refrigerated cabinet. The sliding plate slides in the sliding cavity, the first communication hole and the second communication hole are staggered, at the moment, the containing groove is disconnected from cold air, and therefore cold storage of other medicine cannot be affected in the process of taking and placing the medicine in the drawer.

Millions of people take different medications multiple times a day and need to manually sort medicines into pill organizers, which can cause medication inaccuracies. There is an urgent need for a home-based pill dispenser system to keep track of dosage and its changes in real time, be user friendly, and dispense pills per dose and timing without the need to sort out pills in advance. This invention describes a pill dispenser system with custom designed wheel rotation systems containing grooves on the wheel for specific pill sizes to receive pills one at a time from a receptacle above in the groove of the wheel, and with desired wheel rotation dispense the pill into a receptacle below. The rotation of the wheel is controlled by a 5V stepper motor, an Arduino™, and a custom Android™ application.

This invention discloses a pharmaceutical sales forecasting system and method based on the IPSO-LSTM model. It includes a data acquisition and processing module, a drug classification module, a drug demand forecasting module, and a data visualization module. The data acquisition and processing module collects historical drug data and preprocesses it. The drug classification module provides drug classification services. The drug demand forecasting module uses the IPSO-LSTM algorithm to predict hospital drug demand, predict epidemic spread, and combine regional environmental conditions and past pharmaceutical sales data of various hospitals to make predictions. The predicted data is provided to sales personnel for sales coordination with hospitals. The data visualization module provides a visual interface to display various data. This invention, through IPSO-LSTM model prediction and analysis, can effectively predict hospital demand for drugs during normal times and emergencies, optimize pharmaceutical supply chain logistics decisions, and help improve the quality of pharmaceutical services.

The invention belongs to the technical field of in-vitro drug evaluation model construction, and particularly relates to bio-ink, an in-vitro humanized neural model and application of the bio-ink in construction of an opioid drug classification prediction model and a dose-effect relationship. The bio-ink comprises a neuroma cell line, methacrylated gelatin, a photoinitiator and a basement membrane matrix. The in-vitro humanized neural model prepared on the basis of the bio-ink provided by the invention has cell-cell and cell-matrix microenvironment interaction characteristics, the complexity of in-vivo tissues can be more truly reduced, and the structure and function of human neurons can be highly biomimetic simulated on the cellular level; the biomimetic property is obviously superior to that of traditional two-dimensional culture and animal experiments, and the accuracy and reliability of drug toxicity and dependency evaluation are improved.

The classified medicine supply device comprises a machine body integrated with an intelligent module of an intelligent diagnosis and treatment ecological system, the front side of the machine body is rotationally connected with a hatch cover, the front side of the hatch cover is slidably connected with a pull ring, one end of the pull ring is fixedly connected with a plurality of baffles sliding on the inner wall of the hatch cover, and the tops of the baffles are fixedly connected with outer columns; two sliding blocks are fixedly connected to the inner wall of the outer column, an inner column is slidably connected to the outer portions of the two sliding blocks, a plurality of plastic balls are fixedly connected to the surface of the inner column, a first bevel gear is fixedly connected to the top of the inner column, and a plurality of counting wheels are rotatably connected to the inner wall of the hatch cover. According to the device, through rotation of the counting wheel, medicine quantity marks on the surface of the counting wheel are synchronously changed, medical staff can directly observe the medicine remaining amount through the window corresponding to the hatch cover, the medical staff can conveniently find the medicine shortage situation in time and supplement the medicine, and the situation that normal development of nursing work of the obstetrics and gynecology department is affected due to the insufficient medicine is effectively avoided.

The present invention discloses a drug classification management system based on a deep forest multi-label classification learning model. The data acquisition module is used to collect drug feature data and perform normalization preprocessing on the drug feature data to obtain normalized drug feature data; the data analysis module is used to analyze the pre-processed drug feature data; the label classification module is used to provide drug label classification services, and classify drugs with different data features based on the data features of the drugs; the environmental monitoring module is used to monitor the warehouse where the drugs are stored and provide real-time environmental data to facilitate the storage and management of the drugs; the data visualization module is used to provide a visual interface to display drug label classification data to help drug administrators obtain drug information in real time. The present invention performs multi-label classification on drugs to achieve hierarchical management of drugs and efficient drug information retrieval.

The utility model provides a medical medicine classified storage and quick medicine taking device, and relates to the technical field of medical auxiliary tools, the medical medicine classified storage and quick medicine taking device comprises a device body and a base, the middle position of the top surface of the device body is provided with an air hole in a penetrating mode, and the middle position of the top surface of the base is vertically provided with a supporting sleeve; an adjusting rod is slidably inserted into the supporting sleeve, a sealing bearing is movably installed on the outer side surface of the adjusting rod, a connecting rod is arranged on the peripheral side face of the sealing bearing, the other end of the connecting rod is fixed to the inner wall of the air hole, a containing cavity is formed in the peripheral side face of the device body, and a containing frame is slidably inserted into the containing cavity; through cooperative use of the device body, the placing cavity, the placing frame, the pushing plate, a sealing bearing, an adjusting rod and a connecting rod, medical medicinal materials are convenient to store and take, the mode is simple to operate, a medical worker does not need to walk circularly to find the medical medicinal materials, the working efficiency is improved, and the physical strength of the medical worker is also saved.

The application provides a kind of anesthetic information visual management method and system, it is related to medical information technology field, including response to the input instruction of user, current anesthetic information is collected;The current anesthetic information includes: the current anesthetic drug used to current patient;In combination with the original drug information corresponding to the current anesthetic drug and / or the operation instruction of the user, current drug information is generated;In response to the confirmation instruction of user, current drug information is visually displayed on target page;Specifically, the current display information corresponding to the current anesthetic drug is constructed;The drug display area in current display information is updated in combination with current anesthetic drug and drug classification characteristics;The time period display area in current display information is updated based on time characteristics;The dose display area in current display information is updated based on operation characteristics, through the visual dynamic update of drug data, improve management efficiency and accuracy, optimize medical operation experience.

The invention relates to the technical field of drug identification, and discloses an artificial intelligence-based drug automatic identification system, which comprises an application end, a collection end and a display end, the application end comprises a database, a medicine information acquisition module, a data preprocessing module, a medicine classification module, a medicine identification module and an information acquisition module; through the arrangement of the medicine classification module and the medicine identification module, each to-be-identified medicine in the to-be-identified medicine bag can be obtained firstly, then the shape of each to-be-identified medicine is analyzed to obtain the shape, the shape can be obtained through an edge detection algorithm, the contour of an object can be extracted through edge detection, and then the shape of the object is judged; according to the technical scheme, after the to-be-recognized medicines are classified into the corresponding categories, subsequent recognition can be better carried out on the to-be-recognized medicines, different medicines have different categories, recognition is carried out after the medicines are classified into the corresponding categories, the subsequent recognition range of the to-be-recognized medicines can be shortened, and the accuracy of medicine recognition can be improved.