67 results about "Drug usage" patented technology

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 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 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.

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 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.

This invention provides an automatic early warning system for abnormal drug sales, comprising: a data management module for periodically collecting and processing patient business data to obtain an underlying data pool; a manual control module for selecting control objects, configuring drug sales early warning rules, determining whether the control objects meet the early warning conditions, and automatically sending early warning information if the determination result is yes; a sales anomaly judgment module for extracting abnormal data from the underlying data pool, constructing a sales anomaly prediction model, and performing real-time drug sales monitoring to obtain sales anomaly trends; and a sales prediction module for extracting sales influencing factors from the underlying data pool, constructing a sales prediction model, and performing real-time drug sales prediction to obtain predicted purchase volume and predicted purchase timing. This invention can effectively identify abnormal drug sales trends, predict drug sales trends, achieve personalized automatic early warning for abnormal drug sales, monitor drug usage and consumption, and promptly detect and respond to drugs with abnormal sales.

The application discloses application of methylphenidate in preparation of a post-traumatic stress disorder (PTSD) psychotherapy enhancer. The methylphenidate is used in the introduction period of PTSD psychotherapy, and can improve the treatment effect of core symptoms of PTSD, including intrusive symptoms, avoidance symptoms, high vigilance symptoms, negative thinking and emotion. The application uses single methylphenidate to disturb patients into an unstable state, adjusts a time window for reconsolidation of trauma memory, and strengthens the decline of trauma memory and the update of healing memory in the time window. Furthermore, compared with daily medication, single medication has clinical significance of reducing the psychological burden and economic burden of patients on drug use. Therefore, the application uses single methylphenidate in the introduction period of PTSD psychotherapy.

The invention discloses an individualized infection control decision-making system based on wound surface microecology and a data processing method, the system collects a local sample of a wound surface, obtains a 16SrDNA or metagenome sequencing result, conventional etiology, inflammation indexes and patient conditions, and records plant defensin BKX-1 and antibacterial drug administration information; the micro-ecological and clinical features are subjected to fusion modeling based on machine learning, a wound infection severity score and a drug resistance risk score are output, an individualized infection control scheme is generated in combination with a preset antibacterial drug use rule, BKX-1 local drug use is preferentially recommended when the risk is low, broad-spectrum antibacterial drugs are reduced, and the risk is reduced. When the risk is high, etiology inspection and medication upgrading are prompted; and data of multiple patients can be counted to form quality indexes such as etiology inspection rate and the like. The method is beneficial to improving the etiology inspection rate, optimizing the use of antibacterial drugs and promoting wound infection control.

The invention discloses an intelligent medicament regulation and control system based on model predictive control. The problem that in the prior art, the medicament usage amount cannot be automatically regulated and controlled along with the change of the water quality condition is solved. The device comprises a chemical mixing barrel arranged on a chemical adding barrel bracket, a chemical stirring mechanism arranged in the chemical mixing barrel, chemical concentration detection equipment arranged in the chemical mixing barrel, a chemical discharging mechanism arranged on the chemical adding barrel bracket and communicated with the chemical mixing barrel, and a sewage detection mechanism arranged in a sewage treatment tank, and the control mechanism is arranged on the dosing barrel bracket and is respectively connected with the medicament stirring mechanism, the medicament concentration detection equipment, the medicament discharging mechanism and the sewage detection mechanism. The control mechanism adjusts the adding amount of the medicament according to the detection result of the sewage detection mechanism, so that the regulation of the put medicament is realized, the waste amount of the medicament is reduced, the use cost of the medicament is saved, and the hysteresis of the medicament during sewage treatment can also be reduced.

The invention provides a transdermal analgesic patch as well as a preparation method and application thereof. The transdermal analgesic patch consists of a polyethylene glycol terephthalate backing layer, a drug-containing gel layer and a silicified polyester anti-sticking layer. The medicine-containing gel layer takes diclofenac sodium, menthol and capsaicin as analgesic active ingredients according to a specific proportion, and raw materials such as a laurocapram and L-menthol compound penetration enhancer, a blending pressure-sensitive adhesive matrix and a compound antioxidant are matched. The preparation method comprises the steps of dissolving, mixing, coating, drying, compounding and the like, and the process is mild and controllable. The patch is excellent in transdermal performance, the steady-state transdermal rate reaches up to 38.3 micrograms / cm < 2 > h, the 24-hour analgesic total effective rate is 93.3%, and the patch is good in stability and free of layering and curling problems. The traditional Chinese medicine composition can be used for preparing medicines for treating postoperative acute pain or chronic neuropathic pain, and is convenient to use and stable in effect.

The invention discloses a drug sensitivity test drug recommendation system, method and device based on an AI large model and a medium, relates to the technical field of drug sensitivity tests, is applied to a computer device, and comprises a medical object information collection module used for collecting medical feature information from initial medical information of a medical object by using a feature information extraction AI large model; the medical feature information comprises basic information of a medical object, current and past drug allergy information and disease information; the drug recommendation module is used for determining a preliminary drug recommendation result according to a drug sensitive test result of the medical object and a preset expert database constructed based on a drug use industry standard; the medication recommendation module is used for inputting the medical feature information, the preliminary medication recommendation result and a medication database into a medication recommendation AI large model and outputting a target medication recommendation conclusion; the target drug use recommendation conclusion at least comprises recommended drugs, drug use risk information of the recommended drugs and drug use details. And more accurate and practical drug recommendation is realized.

The invention relates generally to medication therapy and more particularly to a system and methods for medication therapy management to support improved adherence and alert clinicians of changes in behavior or symptoms. The system may facilitate interactions between various data sources (e.g., medical health records, genomics databases, and other connected third-party devices) to manage workflow, execute rules, interface with knowledge bases, codify information, schedule events, provide notification, and more. In addition, the system may include a conversational or actionable artificial intelligence persona tailored to each user and configured to, for example, converse, instruct, and / or coach a user according to one or more features of the system. Advantageously, the system may improve adherence and facilitate patient engagement, care transition, and disease management, resulting in, for example, reduced healthcare costs for providers and payers, and enhanced drug use for pharmaceutical manufacturers, pharmacies, and specialty pharmacies.

The invention provides a soluble microneedle loaded with triptolide and salvianolic acid A as well as a preparation method and application of the soluble microneedle, and relates to the technical field of pharmaceutical preparations. According to the invention, the soluble microneedle is utilized to load the triptolide nanocrystal and the salvianolic acid A, and the medicine which can directly act on the diseased joint of a patient with rheumatoid arthritis through local transdermal administration is prepared. By using the soluble microneedle loaded with the triptolide and the salvianolic acid A, the skin delivery capacity can be improved, accumulation of diseased regions is increased, meanwhile, side effects caused by systemic drug absorption are reduced, the curative effect is improved by using the two drugs together, and the soluble microneedle loaded with the triptolide and the salvianolic acid A has a better treatment effect on rheumatoid arthritis.