479 results about "Infection risk" patented technology

The invention relates to an infection risk assessment method and system for nursing, and the method comprises the steps: collecting multi-source heterogeneous data of a patient, and fusing the multi-source heterogeneous data into a unified original data set; obtaining a standardized risk feature vector based on the original data set; inputting the risk feature vectors into a multi-modal risk assessment model, and outputting risk probabilities of individual infection and group infection; forming a personalized risk index based on the risk probability; according to the personalized risk indexes, the decision support system outputs hierarchical intervention measures matched with the risk levels, and records and feeds back execution conditions and intervention effect data of the hierarchical intervention measures for dynamically updating parameters of the risk assessment model; and integrating the intervention effect data and the early warning signal into feedback information to form a dynamic infection risk assessment system adapted to specific hospital characteristics. The accuracy of infection risk assessment of nursing can be improved.

The invention discloses an infection risk dynamic assessment method based on deep learning, and relates to the technical field of intelligent monitoring. Multi-source heterogeneous data are integrated by calling a pre-trained deep learning model, a basic regeneration number (R0) value set is calculated based on an SEIR infection model, the basic regeneration number (R0) value set serves as a node initial feature of a space-time diagram network, and a double-layer dynamic network is constructed to generate a regional vulnerability scoring matrix. And calculating a global infection risk index through the linear combination vulnerability score and the R0 numerical set, and generating a prediction infection density matrix and a hierarchical prevention and control strategy when the index exceeds a preset threshold. And further comparing a prediction result with actually measured infection data, dynamically adjusting a symptom keyword weight and a medical resource dependency parameter, and triggering online incremental learning of the model to optimize evaluation precision. Dynamic adaptation of multi-source data fusion modeling and prevention and control strategies is achieved, and the timeliness of infection risk assessment and the scientificity of prevention and control decisions are remarkably improved.

The invention relates to the technical field of burn wound treatment, and discloses an intelligent burn wound dynamic monitoring and evaluation system. The system comprises a data acquisition module for acquiring real-time physiological data of a burn wound by using a multi-source sensor; the multi-modal feature fusion module is used for generating wound comprehensive state features based on a deep belief network; the dynamic evaluation module outputs a wound healing level and a risk early warning signal through a pre-trained collaborative evaluation model; the optimization decision generation module is used for constructing a multi-target dynamic optimization model to adjust a treatment scheme according to risk early warning; and the hierarchical execution control module realizes distributed execution of treatment instructions through a hierarchical control architecture. The system can comprehensively monitor the state of the wound surface, accurately evaluate the healing risk, optimize the treatment scheme and accurately execute the treatment scheme, effectively improve the treatment effect of the burn wound surface, reduce the infection risk and shorten the healing period, and has important clinical application value.

The invention discloses an infection risk assessment method and system for burn nursing, and the system comprises a long-term trend analysis module and a short-term anomaly detection module, the long-term trend analysis module employs an improved Transform-XL model, and captures the chronic cumulative effect of inflammation indexes within 72 hours through a relative position coding and memory multiplexing mechanism; the short-term anomaly module is based on a bidirectional LSTM reconstruction network, combines a dynamic threshold algorithm to identify sudden physiological anomaly in a window of 6 hours in real time, generates a final infection risk index through a confidence-driven adaptive fusion algorithm and dynamic weighted dual-channel output, triggers clinical response in combination with a hierarchical early warning mechanism, and introduces closed-loop feedback optimization, so as to achieve the early warning of the physiological anomaly. The actual intervention effect feedback model is iterated, the infection recognition time is shortened to 3.2 hours, the ROC-AUC reaches 0.94, and the reasonable utilization rate of antibiotics is increased to 89%.

The invention relates to the technical field of health monitoring, in particular to a health monitoring method and device based on the Internet of Things, and the method comprises the steps: obtaining a historical health monitoring data set according to an Internet of Things sensor network; dividing the monitoring area into a multi-scale space-time health state grid; and performing state classification through the historical health monitoring data set according to a density peak clustering algorithm to obtain a health state mode. According to the method, the monitoring area is divided into the multi-scale space-time health state grids, and the mapping relation between the environment parameters and the health indexes is combined, so that the microenvironment-health association which is difficult to find by a traditional monitoring system can be captured, for example, in a ward scene, the monitoring accuracy is improved; the phenomenon that the infection risk of a patient is increased due to poor air circulation in a ward can be accurately identified, so that environmental parameters are optimized in a targeted manner; and through collaborative analysis of a global channel and a local channel, a group trend and individual anomaly can be captured.

The invention relates to the technical field of intelligent building environment control and energy management, and provides a building ventilation regulation and control method and equipment based on multi-target space-time analysis in order to solve the problems of high energy consumption, uncontrollable infection risk and response lag in the prior art. Original data and the spatial-temporal features are combined into a multi-modal fusion data set, an air quality change rule is learned based on an LSTM model, a future air quality state matrix is output, a multi-target dynamic optimization function is constructed, an optimal regulation and control strategy of a fan, fresh air and purification equipment is generated, and the optimal regulation and control strategy of the fan, the fresh air and the purification equipment is obtained. The response speed is improved while energy consumption is reduced and infection risks are controlled, and the system is particularly suitable for public places such as hospitals, schools and nursing homes with high requirements for indoor gas environments.

An infection control tool for a building HVAC system includes processing circuitry configured to receive one or more inputs defining a HVAC system configuration for each of a baseline scenario and one or more other scenarios. The processing circuitry is also configured to estimate infection risk and at least one of energy consumption or operating cost for each of the one or more other scenarios relative to the baseline scenario. The processing circuitry is also configured to operate a display to provide the infection risk and at least one of the energy consumption or operating cost to a user.

The invention relates to the technical field of medical instruments, in particular to an intelligent wound nursing system which comprises a dressing body, and the dressing body comprises a skin-friendly layer, a functional layer and a protective layer. A monitoring module, a control module, a medicine leading-in module, a flexible circuit layer and an alarm module are integrated in the functional layer. According to the method, the infection misdiagnosis rate is reduced through multi-sensor fusion monitoring and a preset infection risk threshold algorithm; according to the design, the micro-fluidic chip and the biological probe are integrated in the percolate component sensor, so that the infection detection rate is increased; a temperature-sensitive hydrogel micro-valve array and nanofiber membrane slow release technology is adopted, so that medicine waste or poor treatment effect is reduced; through a multi-sensor data fusion algorithm, the detection accuracy is improved; the layout of the micro-valve array and the annularly distributed independent medicine storage cavities is adopted, so that the release error is reduced; through the ultrathin flexible framework, the snakelike wiring circuit and flip chip packaging, circuit breakage is avoided, and the clinical failure rate is reduced.

The invention discloses a postoperative infection monitoring and early warning method and system, and relates to the technical field of clinical monitoring, and the method comprises the steps: collecting a postoperative infection multi-source alignment data set, building an individual reference model, dynamically extracting postoperative change features, building a behavioral physiological coupling model, recognizing abnormal interaction, and quantifying the infection risk. According to the method, multi-source data are fused, an individualized dynamic baseline model and a behavior-physiological coupling model are established, intelligent recognition and grading early warning of postoperative infection risks are achieved, and the method is high in practicability and easy to popularize. Model parameters are automatically corrected by utilizing a self-learning and feedback recharge mechanism, a closed-loop process of monitoring, prediction, intervention and optimization is formed, infection symptoms can be recognized in advance, manual dependence is reduced, the real-time performance and accuracy of postoperative infection prevention and control are improved, and intelligent decision support is provided for clinic.

The invention discloses an ICU sepsis two-stage early prediction method and device and a storage medium, and the method comprises the steps: continuously collecting a clinical data set after a patient enters an ICU, and carrying out the feature extraction, and obtaining a prediction feature vector; based on the predicted feature vector corresponding to the clinical data set at the current observation moment, determining whether the patient is a non-sepsis sample by using a preset classification model; and if the patient is not determined as a non-sepsis sample by the classification model, predicting whether the patient has a sepsis infection risk in a future preset time period or not by using a preset prediction model according to the current observation moment and the prediction feature vector corresponding to the clinical data set in the previous set time. According to the application, a two-stage mode is adopted, patients are subjected to layered screening, and samples which do not obviously belong to sepsis are excluded; and for the samples which are not excluded, more accurate sepsis risk prediction is carried out by using the prediction model in combination with the prediction feature vectors corresponding to the clinical data of the plurality of time periods, so that the prediction accuracy is improved.

The ureter and urine bag comprises a urine bag body, a spiral pipe, a connecting pipe, a threaded connector pipe and a urine guiding pipe, the threaded connector pipe comprises a pipe body and an insertion pipe, internal threads with the thread pitch being 1.8-2.2 mm are machined on the inner wall of the pipe body, external threads matched with the internal threads are machined on the outer wall of the insertion pipe, and the spiral pipe is connected with the connecting pipe. Two groups of wing plates are symmetrically arranged on the outer wall of the cannula to provide rotating acting points, and a collecting assembly is integrated on the side wall of the urine bag and used for aseptically collecting urine samples. Traditional plug-pull type connection is replaced by a precise thread fit structure, a clear rotating force application point is provided for medical staff, operation is labor-saving and convenient, connector pollution is avoided, the urinary tract infection risk is effectively reduced, and the nursing comfort of a patient is improved.

The invention discloses a nursing communication follow-up visit system for the department of burn and plastic surgery based on artificial intelligence, and belongs to the technical field of medical follow-up visit systems. The system comprises a nursing wound acquisition module used for acquiring physiological data of a patient, wound image data, nursing operation records and text record data constructed by subjective feedback of the patient in real time; according to the method, multi-modal data are integrated, and a dynamic patient data framework is constructed; physiological indexes are monitored in real time, and a basis is provided for early infection early warning. A wound area is accurately segmented, and quantitative evaluation of the wound is achieved; the emotion and compliance of the patient are analyzed, the nursing compliance is improved, the infection risk detection rate is increased, and the false alarm rate is reduced; based on a random forest model and a dynamic threshold value, hierarchical risk management is realized, a personalized follow-up visit strategy is constructed, resource configuration is optimized, a feedback driving mechanism is introduced, a closed loop is formed, model dynamic updating is realized, nursing standard upgrading is promoted, and system model prediction precision is improved.

The invention discloses an infection risk grading early warning method and system based on clinical parameter dynamic fusion. The method comprises the following steps: acquiring patient data from a plurality of medical systems to obtain initial data; performing regularization preprocessing on the initial data to obtain a preprocessing result; quantifying the importance of the preprocessing result in combination with clinical expert opinions and a machine learning model, and generating a final risk assessment weight through dynamic weighted fusion; based on the final risk assessment weight and the knowledge graph, factors influencing the risk and weights of the factors are determined, and a dynamic assessment model used for calculating a risk score is established; and performing continuous monitoring by using the dynamic evaluation model, and automatically triggering an alarm when the risk score exceeds a threshold value. By implementing the method provided by the invention, the accuracy and reliability of infection judgment can be effectively improved, false alarms and missing alarms are reduced, and more timely and accurate infection risk early warning is realized.

The invention relates to the technical field of medical instruments, and discloses an interventional instrument delivery rotating device and conveying system.The interventional instrument delivery rotating device comprises a transmission mechanism, a delivery mechanism and a translation driving component, the transmission mechanism comprises a rotation driving component and a translation driving component, and the delivery mechanism is arranged at the top of the transmission mechanism; the delivery mechanism comprises a delivery driving wheel and a delivery driven wheel, the delivery driving wheel is matched with the rotary driving part and drives the delivery driving wheel to rotate through magnetic force so as to achieve synchronous rotation, and the translation driving part is used for driving the delivery driven wheel to move; compared with the prior art, through non-contact transmission of magnetic coupling, the driving side and the execution side are completely isolated, a pollution path is cut off from the physical structure, and the infection risk is greatly reduced.

This invention relates to the field of nasal aspirator technology, and more specifically, to a nasal aspirator and its method, comprising: a nasal plug suction head unit and a negative pressure suction unit. The nasal plug suction head unit includes: a suction head body, which has an suction port for inserting into the nasal cavity to aspirate nasal secretions and an exhaust port for connecting to the negative pressure suction unit. The nasal aspirator and its method of this invention adjust the suction force of the suction head body through the negative pressure suction unit, making it easier to control the speed or force of aspirating nasal secretions, reducing discomfort inside the nasal cavity. Compared to oral nasal aspirators, this invention provides better suction and reduces the risk of infection. The structural design of the nasal plug suction head unit in this invention effectively prevents the backflow of nasal secretions, preventing secondary infection caused by backflow, and reducing discomfort caused by irritation to the nasal cavity or throat.

The invention relates to a multi-modal data fusion-based infection dynamic visualization evaluation method, which comprises the following steps of: acquiring multi-modal data which comprises a medical image modal, a microbiological modal, a spatio-temporal behavior modal and a physiological and biochemical modal; the multi-modal data is quickly searched through quantum parallel computing, and an optimal feature combination is obtained; carrying out fusion association on the optimal feature combination to obtain fusion features, and constructing a space-time coupling infection risk model at the same time; the space-time coupling infection risk model performs risk field construction based on the fusion features, and generates infection dynamic visualization content; compared with traditional single-mode data, the infection direction can be evaluated more accurately, after quantum calculation is introduced, the operand can be reduced, the calculation efficiency and the accuracy of optimal feature combination obtaining can be improved at the same time, the pathogen propagation path can be visually checked through the infection dynamic visualization content generated through the space-time coupling infection risk model, and the infection risk can be effectively improved. Therefore, blocking can be timely cut off, and disease prevention and control are achieved.

The utility model belongs to the technical field of Tibetan pig disease prevention and treatment, particularly relates to a vaccine injector for Tibetan pig disease prevention and treatment, and aims to solve the problems that when vaccine injection is carried out on Tibetan pigs in the same batch of growth stage, workers often hold injectors with hands to go to pigsties to inject the Tibetan pigs one by one, piglets missing vaccine injection are prone to occurring, and potential risks exist. According to the scheme, the device comprises an electric conveying belt, the electric conveying belt is arranged on a channel between two adjacent pigsties, and two guardrails for preventing piglets from falling off are symmetrically arranged above the electric conveying belt. When the piglet vaccine injection device is used, through the design of the electric conveying belt and the guardrails, a worker can conveniently inject vaccines to piglets one by one, and therefore the situation that the piglets are missed to be vaccinated is avoided; through the design of the adjusting assembly, the distance between the guardrails can be adjusted according to the body types of piglets of different growth batches; through the design of the needle-free injection assembly, stress reaction and cross infection risks caused by traditional needle puncture are avoided.

The invention discloses a monitoring and prevention method for comprehensive prevention and control of tobacco viruses. The monitoring and prevention method comprises the following steps: S1, collecting tobacco virus monitoring data; s2, analyzing a virus infection risk index through the monitoring data; s3, preparing a comprehensive virus control agent; s4, collecting leaf states of the tobacco plants; s5, judging an infection propagation direction by combining multi-dimensional data; according to the method, concentration data of root system metabolites and leaf VOCs are collected at the same time, and multi-parameter conjoint analysis of virus invasion is achieved; through joint analysis of VOCs concentration data in the orientation, root system metabolites and leaf apparent parameters, the numerical value change trend in the virus propagation direction is quantified, and accurate positioning of a propagation path is achieved; through multi-dimensional data fusion, dynamic model quantitative analysis and physical blocking and medicament cooperative prevention and control, early warning, accurate judgment, propagation direction quantification and efficient prevention and control of tobacco virus infringement are realized, and a complete closed loop from monitoring to intervention is formed.

The invention discloses a fruit and vegetable grafting wound healing nutrient solution containing polysaccharide complex enzyme and a preparation method, belongs to the technical field of agricultural biochemical preparations, and aims to solve the technical problems of low removal efficiency of necrotic tissues at grafting wounds and high risk of microbial infection. According to the technical scheme, the nutrient solution is characterized by being prepared from the following raw material components in parts by weight: 0.3 to 0.8 part of polysaccharide, 1 to 5 parts of cellulase, 0.5 to 2.5 parts of pectinase, 1 to 5 parts of glycerol and 90 to 100 parts of water. Wherein the pH value of the nutrient solution is adjusted to 5.0-6.5 by using a phosphate buffer agent, the polysaccharide is composed of chitosan and sodium alginate, the mass ratio of the chitosan to the sodium alginate is 1: 0.5-1: 2, the activity of cellulase in the nutrient solution is 100-500 U / mL, and the activity of pectinase in the nutrient solution is 50-250 U / mL. The nutrient solution is mainly used for promoting fruit and vegetable grafting wound healing, and application verifies that the nutrient solution can effectively improve wound healing quality and reduce infection risk in the grafting process of fruits and vegetables such as cucumbers, eggplants, peppers, tomatoes, litchis and oranges, and has a good application effect.

The invention belongs to the technical field of intelligent medical management, and particularly relates to a hospital infection AI intelligent early warning and data management method and system based on deep learning, and the method comprises the steps: collecting the multi-source medical data of a patient, constructing a structured input feature, and training an infection risk prediction model. Real-time reasoning, space comparison and risk path analysis are carried out on the infection risk of the patient; the system comprises a data acquisition module, a model training module, a model reasoning module, a risk comparison module, a multi-level evaluation module and an infection prevention and control business management module, all the modules operate cooperatively, and prediction and identification of infection risks and spread path mapping management are achieved. The intelligent and visual level of hospital infection early warning is improved, and the system has the advantages of being high in real-time performance, clear in data structure and good in traceability.

The invention relates to the technical field of temperature mapping, in particular to a burn wound infection early warning method and system based on infrared thermal imaging monitoring, and the method comprises the following steps: extracting an image temperature recombination thermal matrix, recognizing a contour, screening edge fluctuation, trimming a thermal difference to track a heat flow path, calculating a drift trajectory, and analyzing heat value mutation. And a wound infection early warning scheme is obtained. According to the invention, through temperature reconstruction and thermal difference distribution analysis of an infrared image, a wound surface hot area range and a thermal energy gathering trend are accurately identified, dynamic tracking of edge thermal drift is realized in combination with a heat flow path and a heat value change direction, and a multi-layer heat map structure is constructed by using heat value increasing and climbing mutation characteristics. According to the method, the identification precision and infection risk early warning capability of a thermal abnormal region are improved, the sequential expression and spatial structure definition of temperature change are enhanced, the fuzzy problem of a static heat map is improved, and continuous monitoring of the thermal evolution process of a wound surface and directional positioning of a high-risk region are realized.

The invention discloses a thoracic surgery pulmonary infection effusion drainage device and belongs to the technical field of medical instruments, the thoracic surgery pulmonary infection effusion drainage device comprises a drainage catheter structure, a filtering structure and a connecting assembly, the drainage catheter structure comprises an insertion tube, the two ends of the insertion tube are connected with a fixing tube and a hemispherical end respectively, and a partition plate is arranged in the insertion tube and the fixing tube; a plurality of drainage holes are formed in the end, close to the hemispherical end, of the insertion tube in the circumferential direction, and a medicine feeding hole is formed in the portion, above the drainage holes, of the insertion tube and communicated with the monitoring cavity. By means of the semispherical end and the drainage hole of the drainage catheter structure, lung tissue is prevented from being scratched when thoracic wall puncture is conducted, the lung tissue damage rate can be reduced to be smaller than or equal to 0.5%, drainage, pressure monitoring and drug administration are achieved through the double-cavity structure, one-time puncture is completed, and the pain of a patient is relieved; by arranging the partition plate, the drainage cavity and the monitoring cavity are isolated, liquid medicine is prevented from polluting an effusion sample, and the infection risk is reduced.

The invention relates to a hospital infection risk dynamic assessment method based on environmental monitoring data, and belongs to the technical field of infection risk assessment, and the method comprises the following steps: S1, collecting environmental parameters of a hospital key area in real time through a distributed Internet of Things sensor network, and synchronously integrating a personnel flow thermodynamic diagram of a UWB positioning system and HIS clinical operation data; s2, constructing a rule base containing 12-dimensional coupling rules; s3, performing risk assessment based on an environment-driven infection propagation tree model EITT, firstly calculating a pathogen exposure dose, then dynamically allocating propagation path weights according to a real-time environment state, and finally generating a risk thermodynamic diagram fused with a space-time dimension; and S4, setting a three-level risk value threshold value, starting corresponding prevention and control measures when the risk value reaches the corresponding threshold value, realizing linkage with the environment regulation and control equipment through an OPC-UA protocol, and performing feedback evaluation on an execution effect. According to the invention, the infection risk can be dynamically monitored, response levels can be automatically divided according to infection conditions, and a coping strategy is given.

The invention provides an efficient negative pressure flushing drainage system which is specially designed for a medical scene, combines a negative pressure drainage technology and a flushing technology, and aims at efficiently and safely treating a wound. The system adopts an integrated design, a central tube cavity and an edge interlayer structure are arranged in the negative pressure flushing drainage tube, and a multi-channel flushing hole is formed, so that flushing and drainage are synchronously carried out. The system has an intelligent control function, the flushing strategy can be automatically adjusted according to the flushing fluid amount, the drainage fluid amount and properties, and the treatment effect and safety are improved. Meanwhile, alternate or simultaneous suction of a plurality of drainage tubes is supported, and the risk of cross infection is reduced. In addition, the system integrates data synchronization and information display alarm functions, and the informatization level of medical services is improved. According to the system, the operation process is simplified, and an efficient and convenient wound treatment solution is provided for medical staff.

The invention discloses an animal serum vaccine detection data processing method and system based on big data, and the method comprises the steps: obtaining a multi-source data set, and sequentially carrying out the data cleaning and time-space alignment of the multi-source data set; key features in the initial multi-source data are extracted, a multi-dimensional feature vector is constructed, and potential association between vaccine effects and environmental factors is mined by using an FP-Growth association mining algorithm; the vaccine effect is predicted based on an XGBoost algorithm, an LSTM neural network model is introduced to analyze the time sequence change trend of antibody titer, and the probability of infection risk is quantified in combination with a Bayesian network; inputting the associated multi-source data into the dynamic prediction model for identification, and outputting a vaccine effect evaluation index; and on the basis of the vaccine effect evaluation index, detecting and judging whether the vaccine batch has recessive infection or not by utilizing an isolated forest. And real-time monitoring and risk early warning of vaccine quality are realized.

The invention relates to the field of medical apparatus and instruments in rectum surgery, and particularly provides a novel multifunctional intestinal bypass device for rectum surgery, which comprises a hollow sleeve, a film sleeve, a decompression air bag sleeved outside the hollow sleeve, and an inflation channel, wherein after being inflated, the decompression air bag protrudes in a corrugated or threaded mode in the axial direction of the hollow sleeve, the protruding part makes contact with the intestinal wall to provide friction force, and a decompression gap is formed between the sunken part and the intestinal wall; according to the invention, intestinal contents are discharged from the hollow sleeve and the film sleeve, so that excrement or intestinal juice is prevented from being in contact with an anastomotic stoma, the infection risk of the anastomotic stoma is reduced, and the healing rate of the anastomotic stoma is accelerated; the thin film sleeve is soft and deformable, so that discomfort such as anus falling expansion, pain and tenesmus of a patient can be effectively reduced, and the comfort of the patient is improved; the decompression air bag is expanded through the inflation channel, the hollow sleeve is positioned, meanwhile, blood supply of the intestinal wall is protected, and the reliable effect of replacing preventive fistulization is achieved.

The utility model discloses an anti-infection sputum swab double-sample collecting device. The collection device comprises an anti-pollution sputum collector, a double-sample collection tube and a collection tube cover, the anti-pollution sputum collector comprises a collector tube body, and a silica gel ring is arranged at an end opening of the upper end of the collector tube body. The double-sample collecting tube is a double-cavity collecting tube and comprises a sputum cavity and a swab cavity which are separated by a partition plate; the collector tube body is connected with the sputum cavity in a clamping manner; the silica gel ring can be attached to the periphery of the mouth of the human body to form sealing. The double-sample collection device disclosed by the utility model is suitable for simultaneously collecting two sample types, namely sputum and swab, in hospitals, communities or personal sites, a plurality of parts are matched differently to realize simultaneous collection of the two samples, and repeated uncovering and one-time covering are not needed, so that aerosol pollution and personnel infection are avoided; in addition, the cotton fracture is designed at the inlet of the swab cavity, so that the infection risk caused by manual sample touching and sample splashing is reduced.