95 results about "Drug usage" patented technology

A method, computer program product, and computer system for a cloud-based medication tracking system. The system may include a plurality of intelligent injection devices across multiple healthcare facilities, each having: a barrel in fluid communication with a needle, a piston including a plunger, a microprocessor, a wireless communication module a supply chain tracking system configured to: monitor distribution of an injectable medication, verify availability of the injectable medication, track a global medication delivery pattern relating to the injectable medication, a machine learning system trained to: analyze medication usage data across healthcare entities, predict a supply chain event, optimize an inventory level, and improve a distribution datum.

The invention belongs to the field of liver cancer liver transplantation, and provides a liver cancer liver transplantation post-operation prognosis prediction system, which comprises a data acquisition module used for acquiring clinical data of a liver cancer patient from a plurality of data sources, including patient basic information, disease diagnosis information, drug use information and patient body function information; the data processing module is used for preprocessing the collected data, including data cleaning, missing value filling, data standardization and data integration, so as to ensure the quality and consistency of the data; by integrating multi-source data and combining advanced algorithms and models, accurate prediction of prognosis of patients after liver cancer liver transplantation is achieved, warning is automatically given out when a risk threshold value is reached, timely and accurate early warning information is provided for medical staff, and by collecting medicine use information and patient body function information, the patient prognosis is accurately predicted. And the physical condition of the patient can be obtained in real time through long-term monitoring, so that the prognosis prediction result is more accurate.

The invention relates to an old inpatient intestinal preparation failure risk prediction method and system, and the method comprises the steps: collecting the multi-dimensional electronic medical data of a patient from a hospital information system (HIS), a laboratory information system (LIS) and a pharmacy information system (PIS), carrying out the cleaning, missing value filling and standardization preprocessing of the original data, so as to construct a high-quality data set, and carrying out the prediction of the intestinal preparation failure risk of the old inpatient. Generating three core risk characteristics based on clinical knowledge: an age-weighted complication index, a specific drug use mark and a key physiological index anomaly mark; inputting the features into a preset rule engine, performing weighted calculation according to a fixed weight coefficient to obtain a comprehensive risk score, finally dividing patients into low, medium and high risk levels according to a risk threshold value determined by historical data, and outputting a result and storing the result into a database for clinical retrieval and early warning. The method can effectively evaluate the intestinal preparation failure risk of the elderly patient, and provides an objective basis for clinical intervention.

The invention discloses a thyroid disease full-period management system and method, and the system comprises a medical service module which is used for medical registration appointment; the data management module is used for collecting and storing human body life health indications of the patient in the hospital treatment period and in the remote re-treatment period; the follow-up diagnosis monitoring module is used for storing dose change data and setting regular review reminding; the health risk early warning module is used for performing correlation analysis on the disease health risk of the patient according to the human body life health indication and the dosage use data, and giving out doctor seeing guidance according to an analysis result; and the daily health management module is used for giving daily diet suggestions and exercise suggestions to the patient according to the analysis result of the health risk early warning module. The thyroid disease full-period management system shows obvious advantages in the aspects of optimizing the re-consultation process, improving the medical treatment efficiency, enhancing remote management, improving the medical compliance, providing personalized health guidance and the like, and provides more comprehensive, convenient and efficient health management services for patients.

The invention discloses a ward health education robot, and the robot is internally provided with a health education platform, and the health education platform comprises a personalized education module which is responsible for generating a personalized guidance scheme according to the personal information of a patient; the intelligent question and answer module is responsible for intelligently recommending related health knowledge and matters needing attention; the medicine use and treatment nursing management module is responsible for recording the medicine use condition of the patient and generating a schedule about the patient; the intelligent navigation and hospital guide module is responsible for realizing autonomous navigation of the patient from a ward to a designated place; the physical sign monitoring and analyzing module is responsible for collecting vital sign data of a patient and generating a health report and early warning information; according to the system, the emotion recognition and interaction optimization module recognizes the emotional state of the patient and adjusts the communication mode and content according to the emotional state, the anxiety and fear emotion of the patient can be relieved, and the confidence of the patient in fighting the disease is enhanced.

The invention provides a cyclodextrin-based nano anti-tumor medicine preparation as well as a preparation method and application thereof, and belongs to the technical field of medicines. The preparation method comprises the following steps: preparing a graphene quantum dot deposition gold nanocage modified by a silane coupling agent, carrying out a Schiff base reaction on the graphene quantum dot deposition gold nanocage and aldehyde substituted-beta-cyclodextrin to prepare a composite carrier, and coating a targeted peptide-drug compound through the reaction, thereby preparing the cyclodextrin-based nano anti-tumor drug preparation. According to the cyclodextrin-based nano anti-tumor medicine preparation prepared by the invention, the anti-tumor medicine effect is obviously improved, meanwhile, the medicine resistance of the medicine can be reversed, the damage to normal tissues is reduced, the use amount of the medicine is reduced, the side effect after the medicine is used is reduced, the compliance of a patient is improved, and meanwhile, the stability and biocompatibility of the medicine can be improved; wide application prospects are realized.

The invention relates to the technical field of medical evaluation, in particular to a basic drug use tendency evaluation method and device, a medium and a product. The method comprises the following steps: acquiring a disease type, a patient specific attribute and medication information of a target patient; according to a standard evidence-based intensity database, determining intermediate evidence-based intensity of each drug type in the medication information in disease types, patient specific attributes and medication schemes; obtaining attribute information of a target hospital seeing a doctor by the target patient, and adjusting the intermediate evidence-based intensity based on the attribute information to obtain the actual evidence-based intensity of the target patient; determining the average standard evidence-based intensity of each base drug type corresponding to the disease type; and calculating a difference value between the actual evidence-based intensity and the average standard evidence-based intensity as a base drug use tendency degree, and generating a drug use rationality evaluation result for the target patient according to the base drug use tendency degree. According to the invention, multi-dimensional evaluation can be carried out on the drug use rationality of the patient, and the accuracy of the evaluation result is improved.

The invention relates to a safety monitoring method for rehabilitation training of an elderly weak patient. The safety monitoring method is used for automatically optimizing the rehabilitation training process of the elderly weak patient. According to the method, physical strength level, disease history and medicine use condition information of a patient are collected, physiological data of a rehabilitation person are monitored in real time in combination with various sensors, heart rate, blood oxygen, body temperature, myoelectric activity, fall detection, an accelerometer and a gyroscope, and a corresponding training scheme or adjustment suggestion is generated; the system outputs the physical health state of the rehabilitation person through the attention neural network; the body health state and the real-time data of the sensor serve as rule engine algorithm input, and then decision suggestions in rehabilitation training are made in real time; the method can reduce the health risk in training, and is especially suitable for personalized rehabilitation training of weak elderly patients.

The invention relates to an intelligent platform management system carrying infusion port patients, and relates to the technical field of data management, and the system comprises a monitoring unit which is used for collecting impedance data, temperature data and medicine use time sequence data; the intelligent analysis unit is used for constructing a dynamic health baseline of the patient, calling a preset machine learning model based on the dynamic health baseline and outputting a complication risk level of the patient; the closed-loop execution unit is used for triggering a three-dimensional life behavior guidance scheme matched with the patient state based on the complication risk level, calculating a corresponding infusion port maintenance period based on the real-time smoothness score, and generating a medicine supply instruction in combination with medicine use time sequence data; and the hierarchical interaction platform is used for generating an early warning view containing the risk level of the patient and the key attention information based on the complication risk level, and pushing maintenance appointment suggestions and planning contents at the patient side based on the maintenance period of the infusion port. The system can improve the management efficiency and safety of the patients in the infusion port.

The present application relates to the technical field of knowledge graph, in particular to a multi-task hepatitis B drug screening method and system based on knowledge graph assistance, comprising the following steps: based on hepatitis B virus genotype sequence data recorded over time, patient drug use records and drug sensitivity. In the present application, multi-dimensional dynamic time series data such as virus genotype sequence data, patient drug use records and drug sensitivity are integrated, the interaction events between entities are marked by time stamp, the dynamic characteristics such as virus variation track and drug efficacy change are embedded in the graph node attributes, so that the knowledge representation can reflect the time dependence in the real scene. Based on biological pathway annotation information and protein interaction data, the hyperedge connection multi-entity set is defined, the limitation of traditional knowledge graph which only supports binary relationship is expanded, the drug combination and multi-target synergistic mechanism are explicitly modeled, and the misjudgment of combination effect caused by the simplification of interaction relationship is avoided.

The invention relates to the technical field of medical care data processing, and discloses a medical care data processing method and system based on artificial intelligence, and the method comprises the steps: recording a medicine taking moment, a medicine effect starting moment and a medicine effect ending moment when a user takes medicines of each dose type; executing a work intensity evaluation strategy for each time period, monitoring the typewriting frequency of the user in each time period, and calculating the work intensity of each time period according to the time period score of the user; according to historical workdays, executing a drug effect intensity matching strategy, and calculating the corresponding work intensity of the drugs of each dose category under the optimal work completion degree; executing an intelligent medicine taking time period matching strategy, and calculating the optimal medicine taking time and dosage type based on the predicted working intensity of the next workday; and a night dose intelligent back-pushing module is executed, the dose type of the medicine taken before sleep in the next workday is calculated, the matching degree between the medicine use and the work performance is improved, and the work efficiency and the state stability are maintained to the maximum extent.

The invention discloses a multi-view-based prediction method and module for learning an echinococcosis-resistant drug combination, and the method comprises the steps: integrating the pathway information of a disease and the similarity information of the disease, extracting the individual input of the disease, the molecular fingerprint information of a drug used by the drug, and the similarity information of the drug, and employing a multi-view-angle feature extraction expert module to achieve the prediction of the echinococcosis-resistant drug combination. And constructing high-order representation from different angles, and connecting representation of a drug combination synergistic effect and a drug-drug interaction task through a gating mechanism by utilizing a self-adaptive task fusion module. According to the method, an echinococcosis-resistant drug combination prediction model based on multi-view multi-task learning is designed, the model pays attention to safe drug use while paying attention to synergistic drug combination, adverse reactions among drugs are avoided, and therefore intelligent prediction of echinococcosis-resistant drug combination is achieved.

The present disclosure relates to the method of treating neurological disease in a recreational drug user by administering an effective amount of soticlestat or a pharmaceutically acceptable salt thereof, wherein the treatment does not produce the potential of drug abuse.

The present invention relates to a gene construct and use thereof. The gene construct is used for inhibiting the excessive excitation of neurons caused by excessive use or abuse of addictive substances. The gene construct comprises a neuronal inhibitory protein-coding gene and a promoter operably linked to the neuronal inhibitory protein-coding gene. The gene construct exhibits significant advantages in terms of precise targeting, closed-loop regulation, retention of natural reward responses, reduction of side effects, and improvement of safety, as well as potential long-acting properties and sustainability. This strategy provides a novel idea and method for the treatment of drug use disorders, and is expected to become an important breakthrough in the field of drug use disorders in the future.

The invention discloses a tacrolimus-containing pellet pharmaceutical composition, the pharmaceutical composition is composed of an enteric pellet and a sustained-release pellet, the enteric pellet comprises 0.5-5% of tacrolimus, 10-80% of a filler, 2-10% of a disintegrating agent, 1-5% of an adhesive, 0.5-2% of a flow aid, 0.5-1% of a lubricant, and 5-13% of an enteric coating material; the sustained-release pellet comprises 0.5 to 2% of tacrolimus, 10 to 80% of a filling agent, 2 to 10% of a disintegrating agent, 1 to 5% of an adhesive, 0.1 to 1% of a flow aid, 0.1 to 1% of a lubricant, 5 to 15% of a sustained-release coating material and 0.1 to 0.5% of a plasticizer. The pellet pharmaceutical composition containing tacrolimus disclosed by the invention can maintain longer blood concentration and longer action time, so that the medicine taking frequency is reduced, the compliance of a patient is improved, the toxic and side effects are reduced, and the effectiveness and safety of medicine use are further ensured.

This invention relates to the application of PGG in the preparation of drugs for treating acute leukemia, belonging to the field of biomedical technology. To address the problems of narrow application range and easy development of drug resistance in existing acute leukemia treatments, this invention provides the application of PGG in the preparation of drugs for treating acute leukemia. Experiments have shown that PGG can inhibit the viability, proliferation, and colony formation of human acute myeloid leukemia cells (MOLM-13) and human acute lymphoblastic leukemia cells (Jurkat), and induce their apoptosis. In animal models, intraperitoneal injection of PGG can prolong the survival days of mice with acute leukemia and reduce the infiltration of leukemia cells in the liver, spleen, and bone marrow tissues. In this invention, PGG directly inhibits the viability of acute leukemia cells and can simultaneously inhibit AML and ALL, without relying on specific gene mutations, resulting in a lower risk of drug resistance, more flexible clinical use, and broader patient coverage, showing promising clinical application prospects.

The present description relates to a method for treating a patient having a mood disorder, comprising administering to a subject in need a pharmaceutical composition comprising a base compound consisting substantially of N-ethyl-2-(5-fluoro-1H-indol-3-yl)-N-methylethan-1-amine or a pharmaceutically acceptable salt thereof in a specified dosage regimen.

The present invention discloses a method and system for early warning of abnormal doctor drug usage based on machine learning, including: a data layer, which is mainly a data center, which collects risk analysis data on drug and consumables usage, departments, suppliers, etc. from the hospital, and performs data cleaning, and manages the data at the same time, including personnel management and query statistics; a business layer, which mainly uses algorithm models to achieve key personnel monitoring and data intelligent analysis, including clue mining, correlation factor analysis and data visualization analysis; an application layer, including an intelligent early warning and forecasting function module, which realizes red, yellow and green three-level risk warnings through business layer big data analysis according to threshold settings, and performs visual display. The present invention adopts a visual graded early warning mechanism and uses an anomaly detection algorithm model to detect doctor drug usage. The detection results are more accurate and the warning effect is more obvious. At the same time, the detection results provide a reference basis for abnormal usage for subsequent relevant departments.

A system and method for managing medication titration using real-time walking and balance data collected from mobile electronic devices are disclosed. Smartphone sensors, including accelerometers and gyroscopes, capture mobility metrics such as gait speed, stride characteristics, postural stability, and fall risk. The mobility data is integrated with additional physiological metrics and a patient's electronic medical records. Analytical algorithms, including machine-learning models, evaluate changes in mobility to identify correlations between medication usage and functional performance. Based on detected changes, the system generates alerts and recommendations to assist healthcare providers in adjusting medication dosages. The invention supports proactive and personalized medication management, particularly for medications that affect balance or fall risk, and improves patient safety by enabling data-driven clinical decision-making using real-world mobility insights.

This invention belongs to the field of drug detection, specifically relating to a method for constructing a fingerprint spectrum of Cibotium barometz and a method for determining the content of its active ingredients. The construction method includes the preparation of a test solution and detection using high-performance liquid chromatography (HPLC) to obtain the fingerprint spectrum of Cibotium barometz. This invention establishes a comprehensive and rapid method for detecting Cibotium barometz drug preparations, which is of great significance for its comprehensive quality detection and overall quality control. The characteristic spectrum obtained by this construction method has at least 12 common characteristic peaks, a stable baseline, and good peak resolution. Furthermore, the relative retention times of each characteristic peak are calculated based on protocatechuic acid, which is beneficial for the comprehensive quality detection and overall quality control of Cibotium barometz preparations, and helps improve the safety and stability of drug use.

The invention relates to the field of medicine informatization management, and discloses an informatization medicine accurate regulation and control method and system for hemodialysis anemia patients, and the method comprises the steps: randomly dividing the collected patient information into a research group and a control group, comparing and analyzing the treatment effect difference caused by the anemia index change of the two groups of patients, and determining the accuracy of the treatment effect. The anemia improvement effect is evaluated by analyzing the relationship between the anemia index level change before and after the adjustment of the drug dose and injection frequency of a research group patient, whether the drug regulation direction is correct or not is judged, and the drug dose and injection frequency are adjusted according to the anemia index level change in the body of the patient. According to the method, the drug dosage and the injection frequency are dynamically optimized, and the difference of patients in a research group and patients in a control group in the aspect of anemia index level improvement is analyzed based on a model prediction result, so that drug regulation is further tracked and monitored, the drug use process is accurately regulated, the treatment quality is improved, and the treatment cost is reduced. And the workload of medical staff is reduced.

To provide an automatic drug intake record identification cap having the function of quickly and automatically identifying drug usage records. [Solution] The cap comprises a cap main body shell 101, a partition plate, and an identification component 103. The partition plate is provided in the center of the cap main body shell, and a transparent view window 104 is provided on the top surface of the cap main body shell, and the identification component is disposed inside the cap main body shell. The identification component includes a pressing base, an identification turntable, an interlocking drive component, and a support component. The pressing base is disposed below the partition plate, and the identification turntable is disposed above the partition plate. The support component is provided between the pressing base and the identification turntable, and the identification turntable is actively engaged with the interlocking drive component.

1. Name of the product of this design: Graphical user interface for maintaining an intelligent prescription usage and dosage database for electronic devices. 2. Purpose of this design product: for use in an electronic device. 3. The key design point of this design product lies in the graphical user interface. 4. The picture or photo that best illustrates the key points of the design: main view. 5. Purpose of the graphical user interface: used for intelligent prescription review and maintenance of the database on drug usage and dosage. 6. Human-computer interaction method of the graphical user interface: In the main view, pull down the drop-down bar in the interface to enter the interface change state diagram 1, continue to pull the drop-down bar to enter the interface change state diagram 2, continue to pull the drop-down bar to enter the interface change state diagram 3, continue to pull the drop-down bar to enter the interface change state diagram 4, continue to pull the drop-down bar to enter the interface change state diagram 5, continue to pull the drop-down bar to enter the interface change state diagram 6, and continue to pull the drop-down bar to enter the interface change state diagram 7.

The invention discloses an intelligent medical record classification method and system, and relates to the technical field of text classification, medical record data in unit time is collected from a hospital database, the medical record data is stored in a standardized mode, and the medical record data comprises basic information of patients, medical record details and medicine use records; performing feature entity analysis on the medical record data by using a RoBERTa-Med model to generate first data; performing feature matrix calculation on the first data based on multi-method feature selection to generate emergency priority, and performing priority ranking on the medical record data according to the emergency priority; a medical record quality control algorithm is used for matching similarity retrieval of current medical record data and historical medical record data, similar medical record data is obtained, historical similar medical records are rapidly matched for current high-risk medical records, and diagnosis and treatment scheme reference and historical result analogy are provided for doctors.

The utility model relates to the technical field of tweezers, and provides a pair of tweezers used for clamping medicine, which comprises a first tweezers arm and a second tweezers arm which are rotatably connected, a first clamping piece is arranged on the inner side of the top of the first tweezers arm, a second clamping piece is arranged on the inner side of the top of the second tweezers arm, grooves are arranged on the first clamping piece and the second clamping piece, and the first tweezers arm and the second tweezers arm are connected through the grooves. When the first clamping piece abuts against the second clamping piece, the two grooves can form a containing cavity used for containing medicine, flexible strips are arranged at the opening ends of the first clamping piece and the second clamping piece, and supporting pieces are rotatably connected to the outer sides of the first tweezers arm and the second tweezers arm through rotating shafts. The tweezers head ends of the first tweezers arm and the second tweezers arm can be far away from the table top by rotating the supporting piece. According to the tweezers, medicine can be prevented from being pinched, the medicine falls into the containing cavity formed by the two grooves during use, the medicine is prevented from falling off, the medicine is prevented from being damaged, and the technical problems that existing tweezers are prone to pinching the medicine, and tweezers heads are prone to being polluted are solved.

Systems, methods, and computer-readable media are disclosed for predicting heart disease events using multimodal biometric and clinical data processed by a temporally-aware machine learning model. Biometric data, such as sensor measurements and additional wearable-derived activity and physiological signals, are collected from a user over a multi-day collection time period (e.g., 10–30 days). Biometric features generated from the collected data are supplemented with clinical features such as demographic and drug-use information. The combined feature set is provided to a machine learning model comprising a sequence of transformer blocks configured to generate progressively lower-resolution temporal representations through pooling and to enforce temporal causality via causal self-attention. The model produces an output predictive of a heart disease event, which may include a metric of VO2 regression or other indicators of cardiopulmonary decline.

A drug prescription support system is provided. In one embodiment, the drug prescription support system for dialysis treatment based on blood tests comprises: a data collection unit that collects basic data about a patient and medical data of a dialysis patient receiving a drug manufactured to treat a first disease, on a server; a Database Management System (DBMS) that maps disease-drug association data and establishes a systematic drug usage information system through data preprocessing; and an artificial intelligence model that includes the patient's blood test data, diagnoses the patient's condition based on the blood test data, and generates at least one drug recommendation information.

The present invention belongs to the technical field of drug preparation, and discloses a pyritinol hydrochloride dry suspension and a preparation method thereof. The pyritinol hydrochloride dry suspension comprises the following components: pyritinol hydrochloride, cross-linked carboxymethyl cellulose salt, adhesive, filler and suspending agent; the filler is lactose and mannitol; the suspending agent is xanthan gum and / or gum arabic; the adhesive is hydroxypropyl methylcellulose E5. The pyritinol hydrochloride dry suspension provided by the present invention uses cross-linked carboxymethyl cellulose salt as a disintegrant, and through the selection of adhesive, filler and suspending agent, the pyritinol hydrochloride dry suspension has good particle properties and appearance, excellent sedimentation ratio, accurate dosage, high solubility, and can reach the blood drug concentration required for treatment faster and facilitate the treatment of young patients. The pyritinol hydrochloride dry suspension provided by the present invention has good taste and strong compliance through the adjustment of the prescription.

The present application provides a method and system for monitoring adverse drug reactions based on big data, which generates more comprehensive clinical drug feedback features by accurately extracting drug action characteristic data and patient response characteristic data from clinical feedback big data, and innovatively blending these characteristic data, laying a solid foundation for subsequent adverse drug reaction analysis. Furthermore, it is possible to intelligently search and identify feature combinations that meet the application conditions of drug combinations in the huge clinical feedback features, and realize accurate prediction and evaluation of adverse reactions under combined drug use. Finally, based on these feature groupings, it is possible to automatically generate adverse drug reaction labels corresponding to target drugs, provide data support for drug development, clinical application and supervision, effectively reduce the risk of adverse reactions during drug use, and ensure the safety of patients' medication.

The invention provides an artificial intelligence anesthesia auxiliary method and system applied to a closed environment. The method comprises the following steps: S1, carrying out data acquisition; s2, setting an automatic anesthesia problem; and S3, carrying out constraint improvement on the automatic anesthesia algorithm. According to the intelligent anesthesia assisting method based on extended Actor-Critic and fusing environmental perception, stable and automatic control over the anesthesia depth can be achieved under the closed and large environmental fluctuation conditions, and compared with a conventional reinforcement learning strategy and a traditional rule control strategy which do not consider environmental factors, the intelligent anesthesia assisting method based on extended Actor-Critic and fusing environmental perception has the advantages that the intelligent anesthesia assisting method is simple and convenient to operate. The method has obvious advantages in the aspects of MAP control precision, environment disturbance adaptive capacity and drug use efficiency.