18 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 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 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.

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.

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).

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 relates to the technical field of medicine sorting, in particular to a hospital pharmacy medicine sorting device which comprises medicine placing frames and a sorting frame, the sorting frame is arranged between the two sets of medicine placing frames, partition plates are fixedly connected to the interiors of the medicine placing frames at equal intervals, and communicating grooves corresponding to the gap positions of the partition plates are formed in the sorting frame. A positioning conveying mechanism is arranged in the sorting frame, a medicine classifying mechanism is arranged on the outer side of the positioning conveying mechanism, and a fixed-point medicine taking mechanism is arranged in the medicine placing frame. Through the arrangement of the medicine classification mechanism, automatic and accurate classification of medicines is achieved, physical isolation of the medicines is achieved through a division bar structure, classification orderliness is ensured through cooperation with intermittent conveying of a conveying belt, the medicines of patients with odd numbers and even numbers are distinguished, the classified medicines directly correspond to patient numbering intervals, secondary screening is not needed when pharmacists take the medicines, and the efficiency is improved. The queuing pressure in the medicine taking peak period is effectively relieved, and the problem of rapid medicine taking of the patient is fundamentally solved.

The application relates to the technical field of pharmaceutical management, in particular to a pharmaceutical classification management device and system, which device comprises a management box, the top of the management box is communicated with a medicine adding hopper; a treatment box is fixed to the inner side wall of the management box, the bottom of the treatment box is communicated with a plurality of classification pipes; a classification frame is fixedly connected to the inner side wall of the treatment box, a feeding hole is formed in the bottom of the classification frame, a placing plate is vertically and slidingly matched with the inner side wall of the classification frame, and the placing plate is located below the medicine adding pipe; an adjusting assembly for adjusting the height and angle of the placing plate is arranged below the placing plate; a conveying assembly for separately conveying the medicine at the placing plate is arranged in the classification frame; and a guiding assembly for directionally guiding the medicine according to the medicine type is arranged in the treatment box. Through the design of the treatment box and the classification frame, the independent conveying and targeted guiding of a large quantity of medicines can be realized, the classification storage work can be continuously and automatically carried out, and the work efficiency of the medicine classification management is effectively improved.

The invention relates to the technical field of biological medicine, and discloses a multi-modal data analysis method for drug screening safety evaluation. By setting experiment duration and sampling intervals, multi-modal data such as genes and metabolites are collected from a drug treatment group and a control group at multiple time points, dimension standardization is performed on the two groups of data based on statistical characteristics of the control group, a comprehensive state vector is constructed, state changes of adjacent time points are utilized to form a discrete time differential component and a state evolution function, and a state evolution function is established. The method comprises the following steps: generating two groups of theoretical trajectories through initial state iteration, comparing the theoretical trajectories with actual observation at each time point to evaluate a multi-dimensional error, performing double accumulation in time and state dimensions to obtain a toxicity index of a drug treatment group and a baseline toxicity index of a control group, and calculating a dimensionless safety score for drug grading according to the relationship between the toxicity index and the baseline toxicity index. Therefore, the limitation of dependence on a single index or a single time point is overcome, and the multi-modal data fusion and full-cycle toxicity quantification capabilities are improved.

An exemplary system for detecting and quantifying drug and / or chemical interactions with a biological sample is provided. The system includes a detection instrument having computing capabilities. The system includes an assay device capable of receiving the biological sample. Introduction of the biological sample into the assay device results in a biological process that may result in the accumulation of fibrin and platelets in 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 accumulated in the reaction zone of the assay device and their associated signals can be used to determine at least one of the presence of a drug, a drug class, a drug level relative to a threshold, or a drug concentration in the biological sample.

The application discloses a breast cancer candidate drug classification prediction method based on AFNN and ADE, and comprises the following steps: performing feature selection on known experimental data by using a random forest RF algorithm, and selecting molecular descriptors with influence; constructing a compound biological activity pIC 50 prediction model based on AFNN; performing parameter optimization on the compound biological activity pIC 50 prediction model based on AFNN by using an adaptive gradient descent algorithm; establishing an ADME / T property classification model based on a probability neural network; and processing a constraint optimization problem by using an adaptive differential evolution algorithm ADE to find the optimal value corresponding to the compound molecular descriptor. The application can find the optimal value corresponding to the compound molecular descriptor, so that the compound has better antagonistic effect on ER alpha activity and has ADME / T properties.

This invention relates to the field of intelligent drug classification and sorting technology, specifically disclosing a multi-specification drug classification and sorting method and computing device based on AI visual recognition. The method includes: in response to a trigger signal indicating that a drug has entered the sorting area, acquiring the current multimodal technical feature data of the drug; comparing the current multimodal technical feature data with a pre-set drug packaging benchmark feature library to determine whether the drug has undergone packaging changes. This invention introduces a dynamic elastic registration mechanism based on edge anchor points and utilizes a thin-plate spline interpolation model to perform non-rigid mesh deformation on the multimodal data. Without requiring re-physical calibration, the algorithm adaptively eliminates data alignment errors caused by soft packaging deformation during high-speed transmission, ensuring the purity of feature extraction.