508 results about "Infection risks" patented technology

The invention relates to an orthopedic postoperative drainage liquid infection risk identification method. Drainage liquid is regarded as system output jointly driven by postoperative local immune regulation and wound recovery; capturing a nonlinear time sequence curve; first-order derived trend modeling is carried out; abrupt change after the change rate is stable is analyzed; establishing a postoperative recovery normal path framework, and forming a standard recovery trend library by using drainage fluid dynamic parameters of non-infected cases; comparing the Euclidean offset degree and directional change between the drainage parameter behavior vector of the current patient and the standard trajectory; the change is converted into a visual recovery offset map, and infection prediction data is measured from a multi-day trend angle; constructing and identifying local abnormal signal aggregation; forming a framework of infection event transition to obtain clinical infection nodes of qualitative change caused by quantitative change; according to the method, early-stage accurate recognition can be realized, the intervention opportunity can be obviously advanced, single threshold misjudgment is avoided, the recognition accuracy and specificity are improved, the model adaptability is improved, and the recognition interpretability is enhanced.

The invention relates to the technical field of peritoneal drainage, in particular to a peritoneal drainage system based on hemoglobin real-time monitoring and intelligent early warning. According to the technical scheme, the device comprises an abdominal cavity drainage tube, an optical sensing module, a microprocessor module and a wireless communication module, wherein the microprocessor module is configured to perform moving average filtering and dynamic trend modeling on hemoglobin concentration data; and triggering early warning according to a preset multi-level alarm condition. The hemoglobin concentration in the peritoneal drainage liquid is accurately monitored in real time, intelligent early warning and a personalized response mechanism are combined, the limitation of traditional manual observation is broken through, the timeliness and accuracy of bleeding risk identification are remarkably improved, the infection risk is reduced through the closed design, the medical care working process is optimized through the system integration capacity, and the medical care efficiency is improved. Data sharing and remote cooperation are achieved, intervention time windows are shortened, patient prognosis is improved, nursing resources can be released, medical quality is improved, and a comprehensive and efficient solution is provided for postoperative monitoring.

The invention discloses a leak-free core-shell hydrogel microsphere delivery system for non-contact flora transplantation as well as a construction method and application of the leak-free core-shell hydrogel microsphere delivery system. According to the invention, bacteria are encapsulated in a core of a core-shell microsphere through a two-step photo-initiation emulsion polymerization method of methacrylic acid gelatin, and a non-contact microbiota transplantation system (NMTS) is constructed. The NMTS can be used for biological encapsulation of various strains, shows encapsulation efficiency close to 100%, and has little influence on bacterial activity at the same time. NMTS demonstrates: a shielding effect that protects sealed bacteria from low pH values in the gastrointestinal tract and bile acid disruption; sufficient mechanical strength ensures that bacterial leakage is prevented and the infection risk is eliminated in the whole gastrointestinal tract delivery process; and internal and external substance exchange is realized, and the intestinal microorganism structure is remodeled. The invention provides a unique bacterial cell microencapsulation method which is a non-contact, safe and effective micropopulation transplantation method.

The invention discloses an intelligent electronic stethoscope system based on wireless transmission and a data processing method thereof, and belongs to the technical field of electronic stethoscopes, the intelligent electronic stethoscope system comprises a heart sound acquisition module, a signal conditioning module, a power supply module, a wireless transmission module, an upper computer module and a database module; the microprocessor module serves as a core control unit, and the system can collect heart sound signals of a patient in real time and conduct amplification, filtering and spectrum analysis processing on the heart sound signals. The processed heart sound data is transmitted to a mobile device or a computer in real time through a wireless transmission module, so that doctors and users can check heart sound waveforms and related data conveniently; the system also supports the uploading of the data to a cloud database for remote diagnosis and query; the method not only can meet the requirements of modern medical treatment for high efficiency and convenience, but also can play an important role in improving the diagnosis precision and the remote diagnosis capability and reducing the infection risk.

The invention relates to the technical field of health risk assessment, in particular to an intelligent early warning system for postoperative infection risk of orthopedic trauma. The system comprises a data acquisition module for acquiring physiological feature data and biomarker data; the key monitoring and screening module screens key monitoring patients according to the continuous abnormal representation growth degree of the initial physiological signs; the infection risk assessment module obtains a marker level index by using the initial deviation level and the growth amplitude of the biomarker, and obtains a wound infection risk coefficient in combination with the prediction condition of historical biomarker data; and the early warning report generation module is used for dividing patient early warning levels according to the physiological parameter abnormality and the wound infection risk coefficient to generate a risk report. According to the method, the evaluation accuracy of postoperative infection is improved through the physiological sign abnormity continuity and the biomarker sudden increase and prediction trend, the subsequent early warning level and risk report generation are more reliable, and a more personalized and accurate treatment scheme can be provided for a patient.

The invention discloses riboflavin photodynamic antibacterial hydrogel for a diabetes wound dressing as well as preparation and application of the riboflavin photodynamic antibacterial hydrogel, and belongs to the technical field of biomedical materials. The hydrogel is prepared from carbomer 941, rhizoma bletillae polysaccharide and carboxymethyl chitosan through physical and chemical bi-crosslinking, glutaraldehyde and carboxymethyl chitosan are added to form dynamic imine bonds, and the stability and adaptability of the hydrogel are enhanced. Meanwhile, the photosensitizer riboflavin is introduced, so that the hydrogel is endowed with photodynamic sterilization characteristics, efficient antibiosis is realized, and rapid healing of diabetic wounds is promoted. The hydrogel has excellent wound environment adaptability and adhesion performance, and is suitable for complicated wound surfaces of diabetes mellitus. The successful research and development of the invention provide reference for the development of novel photodynamic wound dressings, have wide application prospects, provide better treatment choices for diabetics, and are helpful for accelerating wound healing, reducing infection risks and improving the life quality of patients.

The invention discloses a filtering device for reinfusion after external drainage of bile in the hepatobiliary surgery department, and belongs to the technical field of medical instruments. The filtering device comprises a drainage mechanism, a stepped filtering mechanism and a reinfusion mechanism. The stepped filtering mechanism is used for filtering bile; the stepped filtering mechanism is detachably connected with the drainage mechanism and the feedback mechanism. The stepped filtering mechanism comprises a filtering carrier, a filtering cavity and a pumping mechanism used for pumping bile to the filtering cavity are arranged in the filtering carrier, a primary screen, a hollow fiber membrane and a hydrophilic gel filtering membrane are sequentially arranged in the filtering cavity from top to bottom, and a cleaning mechanism used for cleaning the primary screen is arranged on one side of the primary screen. An ultrasonic vibration module for cleaning attachments on the hollow fiber membrane is arranged on one side of the hollow fiber membrane. By means of the intelligent design and the multi-stage filtering mechanism, the bile feedback efficiency and safety are remarkably improved, and the infection risk is reduced.

The invention discloses a burn ward infection prevention and control intelligent early warning system based on big data, and relates to the field of big data analysis and monitoring. The system comprises a multi-modal data acquisition module for acquiring multi-modal data; the data preprocessing module is used for preprocessing the collected data; the feature construction module is used for extracting infection risk features according to the preprocessed data; the dynamic infection risk assessment module is used for constructing a patient infection risk assessment model by using a multi-modal feature learning model according to the infection risk features, and taking the infection risk features as input and the patient infection risk indexes as output; and the intelligent early warning module sets a multi-stage early warning mechanism according to the infection risk index. Through multi-modal data fusion, an intelligent early warning mechanism and dynamic infection risk assessment based on multi-modal feature learning, the infection risk is accurately predicted, early warning hierarchical management is optimized, the adaptability of the system to risk changes is improved, and efficient and prospective infection prevention and control decision support is provided for clinic.

The invention discloses a children respiratory tract infection risk prediction method based on multi-source medical data, particularly relates to the field of respiratory tract infection risk prediction, and is used for solving the problems that an existing method cannot identify a cross-regional co-infection mode and cannot prevent an input transmission risk. According to the method, a high-incidence time period baseline is constructed by extracting children respiratory tract infection historical electronic medical records of all regions, a local co-infection mode feature library is established based on a pathogen positive case co-occurrence relation, and a region-time period-pathogen three-dimensional collaborative tensor is constructed to recognize a synchronous high-incidence region group. And capturing real-time pathogen data of the synchronous high-incidence area, matching the real-time pathogen data with a local co-infection mode to generate a real-time risk list, deducing an input co-infection mode in combination with interregional personnel circulation intensity, and calculating the cross-regional risk permeability. And finally, a risk heat map is generated based on the permeability, and regional linkage-oriented children respiratory tract infection risk prediction is realized.

The invention belongs to the technical field of medical puncture equipment, and particularly relates to a cardiology department clinical puncture device which comprises a supporting plate and further comprises an automatic puncture mechanism, a hanging and placing mechanism, a positioning and locking mechanism, a puncture resistance real-time monitoring and feedback mechanism, a hydrops extraction power supply mechanism and a PLC control panel. A stable positioning position can be provided according to the puncture requirement, the smoothness in the puncture process is ensured, the puncture angle can be rapidly adjusted according to the requirement, the puncture speed can be automatically adjusted based on different resistances in the puncture process, the larger the puncture resistance is, the slower the puncture speed is, the effusion extraction efficiency is effectively improved, and the puncture cost is reduced. More medical labor is released, continuous and stable operation of pericardial effusion extraction work is ensured, time for puncture effusion extraction is shortened, and the problem that pain and infection risk of a patient are increased due to overlong-time operation is solved.

The invention discloses a wound healing state evaluation method and system based on artificial intelligence, and belongs to the field of wound healing evaluation. The method comprises the following steps: integrating medical record data and wound physiological parameters, and extracting relevance between a medication history and an infection type to form a multi-dimensional pathological factor; hemoglobin oxygenation, blood flow and metabolic heat are subjected to cross-period correlation analysis to construct dynamic physiological time-space information, pathological factors and the physiological time-space information are fused into a heterogeneous graph, nodes comprise drug intensity quantized values, infection risk levels and microcirculation fluctuation values, and edge weights are determined by the time sequence matching degree of drug doses and blood flow changes; based on the node weight and the edge association relationship, the treatment time and the physiological parameter acquisition period are aligned to generate a spatio-temporal evolution matrix, the spatial distribution of the infection risk level and the metabolic heat value characteristics are combined, the dynamic association of the drug action intensity and the microcirculation fluctuation is analyzed, and wound healing evaluation information is generated. The accuracy of wound healing state evaluation can be improved.

The invention relates to the technical field of medical data mining, in particular to a postoperative pulmonary infection prediction method and system.The postoperative pulmonary infection prediction method comprises the following steps that a continuous data set is formed by collecting breathing parameters and conducting alignment completion, tidal volume and blood oxygen response delay characteristics are extracted through sliding analysis, and a functional abnormal pulmonary segment is located through local anomaly recognition; and fusing physiological and anatomical features to establish a spatial probability map, extracting a respiratory variation coefficient and a risk feature regression analysis confidence index, and outputting an infection risk early warning list with anatomical positioning. According to the method, data faults are eliminated through timestamp alignment to improve the reliability of time sequence association, the breathing compensation capability is quantified through multi-scale window analysis dynamic coupling, lesion avoidance feature masking is accurately positioned through local anomaly detection, and the result interpretability is enhanced through combination of multi-modal feature fusion and space mapping. The three-stage progressive mechanism improves the prediction precision and timeliness, and provides a decision basis with both time sensitivity and anatomical orientation for clinic.

The invention relates to the technical field of artificial intelligence, in particular to a machine learning-based double-J tube indwelling membranous fungus infection risk medication decision support method, and aims to solve the problems of inaccurate double-J tube indwelling membranous fungus infection risk assessment and medication decision experience. According to the method, the machine learning model for predicting infection risks, pathogenic bacteria and drug curative effects is constructed by collecting multi-dimensional data and performing feature engineering, and personalized medication suggestions and visual decision support are provided in combination with a knowledge base and a rule engine. By adopting the scheme, accurate risk prediction can be realized, drug curative effect evaluation can be optimized, drug use reasonability and safety can be ensured, and clinical decision-making efficiency can be improved.

The thoracocentesis tube capable of monitoring the chest pressure in real time comprises a main body assembly, and the main body assembly comprises a chest drainage tube, a medicine conveying hole, a medicine conveying tube, a three-way connector and an anti-blocking hole. The medicine conveying tube, the chest pressure detection connector, the medicine feeding connector and the like are integrated on the chest drainage tube, so that medical staff can monitor the pressure and the blood oxygen concentration in the chest in real time while conducting closed drainage treatment on the chest, medicine is directly and accurately fed into the chest through the medicine feeding connector when necessary, extra operation and equipment are not needed, and the operation is convenient. Convenience and efficiency of clinical treatment are greatly improved, pain and infection risks of patients are reduced, and rapid recovery of the patients is facilitated; the pressure change and the blood oxygen concentration change in the thoracic cavity are sensed in real time through the detection equipment, continuous and dynamic monitoring of the pressure and the blood oxygen concentration in the thoracic cavity in the whole drainage process is achieved, instant and accurate pressure data are provided for medical staff, and the medical staff can find the abnormal change of the pressure in the thoracic cavity in time.

The embodiment of the invention provides a multi-dimensional data processing method and system for intelligent scoring of emergency patients. The method comprises the following steps: acquiring dynamic temperature data and humidity fluctuation data of a burn wound surface through a flexible wearable monitoring device; inputting the time sequence change of the dynamic temperature data into a temperature-drug release model to generate drug concentration distribution; constructing an infection diffusion map taking the anatomical structure as a topological reference, wherein the infection diffusion map comprises an edge attribute representing the flow direction of tissue fluid and a node attribute representing a necrotic region; combining the metabolic rate parameter in the node attribute and the fluid resistance parameter in the edge attribute, iteratively updating the infection propagation intensity, and generating a weight distribution diagram; matching burn depth grading standards according to geometric deformation characteristics and gradient attenuation trends of the weight distribution map, and generating infection risk dynamic scores integrated with drug concentration distribution feedback. According to the technical scheme provided by the embodiment of the invention, the multi-dimensional data processing efficiency and precision can be improved.

The invention discloses lactobacillus crispatus for improving female genital tract microenvironment and immune aging and application of the lactobacillus crispatus, and belongs to the field of probiotics. The probiotic lactobacillus crispatus ProSci-38 disclosed by the invention can be used for effectively improving the symptoms such as pruritus vulvae, causalgia of vagina, abnormal vaginal secretion and the like of patients with vaginitis; mainly through the effect of intestinal tract-vaginal axis, the proportion of lactobacillus is increased, the proportion of harmful bacteria is reduced, the balance of vaginal flora is recovered, and the acidic environment of vagina is maintained; meanwhile, the inflammatory factor level can be reduced, the immune function of the vagina of a patient can be improved, so that the vagina environment is improved, the infection risk is reduced, and the preparation method has a great prospect in preparation of products for relieving and / or treating vaginitis.

The invention provides a dynamic prediction algorithm for monitoring late-onset infection of a premature infant and an upgrading system. The dynamic prediction algorithm for monitoring late-onset infection of the premature infant and the upgrading system comprise the following steps: a, collecting clinical data of the premature infant, including birth weight, gestational age, 1-minute and 5-minute Apgar scores, right hand perfusion index, lower limb perfusion index and other related clinical information, and b, determining the early-onset infection of the premature infant through medical history collection and physical sign analysis. The method comprises the following steps: collecting data of 11 classification independent variables: prenatal antibiotic use conditions (existence and absence); according to the dynamic prediction algorithm for monitoring late-onset infection of the premature infant and the upgrading system, the infection risk index is effectively calculated through high-risk factors analyzed by the Lasso regression model in combination with clinical basic data of the premature infant, early warning of infection of the premature infant is provided for medical staff, and the accuracy and timeliness of infection prediction are remarkably improved. Besides, the system can automatically remind medical staff to intervene the high-risk child patient through red warning, so that the death rate caused by delayed discovery and delayed treatment is reduced, and the clinical intervention effect is improved.

The invention relates to the technical field of postoperative monitoring, in particular to an enterostomy postoperative infection monitoring and early warning method and system, and the method comprises the following steps: obtaining an enterostomy result based on the state of skin around an enterostomy and enterostomy excrement feature data collected after the enterostomy of a patient; performing time sequence decomposition on the red and swollen area, the wound humidity, the seepage amount and the pH value of excrement, extracting the trend of the red and swollen area and the fluctuation component of the humidity, and combining the pH value change of the seepage and the pH value change of the excrement. According to the method, through time sequence decomposition and sliding time window analysis, dynamic changes of red and swollen area, humidity, seepage amount and pH value are accurately captured, characteristic trend and offset difference are generated in real time, dynamic parameter adjustment and weight updating enable risk assessment to be more sensitive, infection risk changes are effectively predicted, early diagnosis delay of infection is avoided, and the risk assessment accuracy is improved. Through data grouping and distribution analysis, the monitoring precision and the risk grading accuracy are improved, accurate early warning and intervention are achieved, and all-around support is provided for postoperative management of patients.

The invention discloses a method for predicting periprosthetic infection of an artificial joint after a rheumatoid arthritis operation, and belongs to the technical field of medical treatment, the method can be applied to risk prediction of periprosthetic infection (PJI) of the artificial joint after the rheumatoid arthritis operation, and the method comprises the following steps: carrying out feature selection through a Boruta algorithm; an integrated machine learning algorithm is developed based on a genetic algorithm and an SMOTEENN algorithm in combination with machine learning for risk prediction, so that the accuracy and practicability of PJI risk prediction after joint replacement of a rheumatoid arthritis patient are improved. According to the rheumatoid arthritis artificial joint postoperative periprosthetic infection risk prediction method, a more accurate prediction and personalized treatment scheme can be provided for a doctor, and preoperative management of joint replacement of a rheumatoid arthritis patient is optimized, so that PJI is prevented to the greatest extent, and the joint function and life quality of the patient are improved.

The invention relates to a mesenchymal stem cell exosome ovary injection device which comprises a puncture needle, an elastic tube and an injector, a plurality of liquid outlet holes are formed in the side wall of the puncture needle, the needle tip of the puncture needle is a sharp solid needle tip, one end of the elastic tube is communicated with the puncture needle through a hollow connecting part, the other end of the elastic tube is provided with a silica gel plug, and the injector is connected with the puncture needle through a connecting part. One end, far away from the elastic tube, of the silica gel plug is provided with a guide hole which is sunken inwards, and the guide hole is used for guiding a needle head of the injector to pierce the silica gel plug. The needle tip is solid, sharp and high in rigidity, and can smoothly pierce into the ovarian tissue; a plurality of liquid outlet holes are formed in the side surface of the puncture needle, so that exosomes can be more uniformly distributed in the ovary during puncture and injection, the puncture frequency is reduced, and the physical damage to the ovary of a patient is reduced; a silica gel plug is designed at one end of the elastic tube for plugging, so that liquid backflow in the process of switching different injection liquid medicine can be prevented, and the infection risk is reduced.

The invention discloses an enterostomy postoperative infection monitoring and early warning method, and belongs to the technical field of monitoring and early warning. The method comprises the following steps: acquiring multi-modal monitoring data which comprises visual data and non-visual data; processing the visual data, and extracting and quantifying visual features of the enterostomy and the surrounding area of the enterostomy; and according to the quantized visual features and the non-visual data, calculating an evaluation value indicating an infection risk, and determining a risk level. Judging and sending out an early warning signal according to whether the risk level or the quantitative visual feature exceeds a preset key early warning threshold value; when the early warning signal is received, a manual medical examination and verification process is started; and feedback and suggestions are provided for the user. According to the method, by carrying out objective quantitative analysis on multi-modal data, early-stage and accurate evaluation and graded early warning on the infection risk after the enterostomy operation are realized, so that the timeliness and accuracy of monitoring and intervention are effectively improved, and the prognosis of a patient is improved.

The invention discloses a multi-drug-resistant bacterium infection risk assessment method, system and device and a storage medium, and belongs to the technical field of medical data analysis, and the method comprises the steps: collecting a clinical related data set of an ICU patient, and carrying out the preprocessing of the clinical related data set to obtain a to-be-assessed data set; performing feature extraction on the to-be-evaluated data set in combination with a long short-term memory network and a time sequence attention mechanism to obtain a high-risk feature set; inputting the high-risk feature set into a pre-constructed dynamic scoring model, and calculating a corresponding risk score through the dynamic scoring model; and grading the risk score based on a preset grading rule to obtain a current risk level, and outputting a corresponding intervention strategy through a preset intervention decision mechanism based on the current risk level. According to the scheme, the high-risk feature set is extracted by combining the long-short-term memory network with the time sequence attention mechanism, then the risk score is calculated through the dynamic scoring model, the risk level is determined according to the preset grading rule, the intervention strategy is output, and the accuracy of MDRO infection assessment is improved.

The invention provides a porous magnetic hyaluronic acid microneedle for treating knee osteoarthritis and a preparation method, and relates to the technical field of biological materials. The porous magnetic hyaluronic acid microneedle for treating knee osteoarthritis comprises a needle body and a matrix layer, the needle body is a porous drug-loading autolysis hyaluronic acid microneedle body, and the matrix layer is a magnetic hyaluronic acid matrix. The invention has the following beneficial effects: 1, a soluble biocompatible microneedle structure is adopted, so that the injury caused by the breakage of a metal microneedle is avoided, and the medicine can directly reach the subcutaneous part; 2, a porous structure is constructed through ice crystal recrystallization, and the drug loading content is increased through a secondary drying technology; 3, the drug carrier is added through the nano magnetic particles, so that diffusion and absorption of drug components are promoted; 4, the operation is simple, tedious steps such as injection in the articular cavity are not needed, and the infection risk in the articular cavity is reduced; 5, batch mold production can be realized, and the production cost is reduced; 6, the administration amount is increased through microneedle perforation administration and matrix layer permeation micropore administration.

The invention relates to the technical field of medical instruments, in particular to anti-leakage drainage equipment for general surgery clinical operations, which comprises a drainage tube, a fixing ring is sleeved on the drainage tube, a positioning component is fixedly connected between the fixing ring and the peripheral skin of a drainage part of a patient, a fixing component is coaxially arranged in the fixing ring, and a first partition plate is fixedly connected in the fixing ring. A second partition plate is further slidably connected into the fixing ring, the interior of the fixing ring is divided into a gel cavity and a triggering cavity by the first partition plate and the second partition plate, pH gel used for triggering a locking mechanism of the fixing assembly through expansion after seepage according to the pH value of seepage is arranged in the gel cavity, and the bottom of the pH gel penetrates through the fixing ring and is fixedly connected with the positioning assembly. By combining the automatic response of the pH gel, the dual induction mechanism of the memory metal and the pressure sensor and the dynamic self-locking function of the cam assembly, the drainage tube is stably clamped and fixed, the drainage tube is effectively prevented from falling off, the infection risk is reduced, and the operation safety is improved.

The embodiment of the invention discloses a hospital infection aggregation risk early warning method and system based on patient medication intensity. The method comprises the following steps: acquiring basic information, medication records and inspection results of a patient; cleaning and standardizing data; based on the medication conditions in the short-term and long-term windows in the processing result, calculating medication intensity, and marking high-risk patients to obtain target patient data; performing rolling accumulation statistics on the target patient data, and determining a risk level through quartile anomaly detection or an inter-day mutation threshold method according to a statistical result; different early warning channels are automatically triggered according to the risk levels, and differential intervention measures are implemented. By implementing the method provided by the embodiment of the invention, the accuracy and the response speed of hospital infection prevention and control can be effectively improved, so that the infection risk and the medical cost of a patient are remarkably reduced, and the problem that the prior art lacks an effective means for performing real-time monitoring and individualized evaluation on the hospital infection risk is solved; and the technical problems of delayed prevention and control measures and low resource utilization efficiency are solved.

The invention relates to a postoperative gastrointestinal function monitoring method integrating flexible sensing and AI, and the method comprises the steps: placing a flexible electronic skin sensor in the abdominal regions of a plurality of patients, carrying out the collection of abdominal acoustic signals, obtaining a plurality of abdominal acoustic signals, and constructing a data set; preprocessing a plurality of samples in the data set, and dividing the preprocessed data set into a training set and a test set; constructing a gastrointestinal function monitoring model, and inputting the training set into the gastrointestinal function monitoring model for training; inputting the test set into the gastrointestinal function monitoring model obtained after training to judge the gastrointestinal peristalsis state; the method is used for assisting a doctor to know the gastrointestinal function state of a patient in real time, a flexible electronic skin sensor is adopted to be attached to the abdomen to collect signals, intubation or radiation examination is avoided, and the pain and infection risk of the patient are reduced; by means of artificial intelligence, the gastrointestinal function monitoring model is adopted to efficiently monitor the gastrointestinal peristalsis state in real time, and doctors are assisted in formulating a treatment scheme.

The invention belongs to the technical field of intelligent logistics, and particularly relates to a medical waste transportation scheme solving method and system based on a double-layer optimization model. The method comprises the following steps that 1, a double-layer optimization model used for solving the medical waste transportation problem is constructed, and the double-layer optimization model comprises the following three stages that in the first stage, the optimal position of a transfer center is determined; in the second stage, a collection route from the collection center to the transfer center is planned; in the third stage, the transportation route from the transfer center to the processing center is optimized; 2, solving the problems of the first stage and the second stage by adopting a Gurobi optimizer; and solving the problem of the third stage by adopting a self-adaptive neighborhood search algorithm. According to the model, the site selection cost and the infection risk are comprehensively considered, and the complexity of the algorithm and the limiting conditions of the real world are effectively dealt with. Therefore, the method has a good application prospect in solving the medical waste transportation problem.

The present invention relates to a composition comprising a Bifidobacterium longum transitional microorganism and a mixture of human milk oligosaccharides (HMOs) consisting of 2'-fucosyllactose (2'-FL), difucosyllactose (DFL), lacto-N-tetraose (LNT), 6'-sialyllactose (6SL), and 3'-sialyllactose (3SL), and optionally lacto-N-fucopentaose I (LNFP-I), 3- fucosyllactose (3-FL) and / or lacto-N-neotetraose (LNnT), wherein the Bifidobacterium longum transitional microorganism has an Average Nucleotide Identity (ANI) of at least 98% with CNCM I-5942. The invention also relates to the use of the composition for preventing, reducing the risk of and / or treating an infection in a subject. The invention also provides the composition for use in promoting a long-term immune benefit in a subject, preventing and / or reducing the risk of allergen sensitisation, preventing and / or reducing the risk of developing a respiratory condition in a subject, and / or preventing and / or reducing the risk of developing asthma in a subject.

The invention discloses a method and system for predicting early infection of a child burn wound, and the method comprises the steps: S1, obtaining the information of the child burn wound, and monitoring the local temperature, pH value, specific inflammatory marker level and original data of pathogen nucleic acid of the burn wound; s2, generating a trend change comprehensive model by using a time sequence analysis algorithm; s3, key features are extracted through an adaptive feature selection technology trend change comprehensive model, and data dimensions are reduced; s4, adopting a transfer learning method to perform pre-training in the burn case as a risk assessment model, and utilizing the risk assessment model to generate an infection risk score; and S5, setting a risk threshold value, and when the infection risk score exceeds a preset threshold value, performing early warning, marking child wound infection, generating a detailed infection report, and performing targeted treatment. According to the method, the problem that a high-performance prediction model is difficult to directly construct due to relatively small child medical data volume and complexity is solved, and the ability of early infection recognition of children is improved.

The invention provides a negative pressure suction device for a neonatal umbilical sinus tract, and belongs to the technical field of medical instruments. The device comprises an adhesive tape, the adhesive tape is arranged in a disc shape, and the bottom of the adhesive tape is fixedly connected with a hydrocolloid adhesive ring. During nursing, an adjusting valve is opened, cleaning liquid is added from a feeding hopper and flows into a tank body through guiding, a driving motor is started, a rotating shaft rotates reversely, a stirring plate is driven to stir medicine and liquid medicine, meanwhile, the liquid medicine is turned over through an auger rotating reversely, the mixing effect is enhanced, after stirring is completed, a flow valve is opened, the driving motor drives the auger to rotate forwards, and the medicine and the liquid medicine are mixed. Liquid medicine enters the sinus tract through the drainage pipe, the cleaning catheter and the injection cleaning cavity in sequence to be flushed and applied, the flow speed can be adjusted and controlled during flushing, a child patient is prevented from being stimulated, the independent cavity is adopted, liquid medicine pollution is prevented, frequent pipe replacement is not needed, thorough cleaning and suction are achieved, the sinus tract is effectively nursed, and the infection risk is reduced.