427 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 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 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 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 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 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 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 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 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.

The invention discloses a brain glioma classification method and device based on multi-mode MRI, and relates to the technical field of image processing. According to the method, multiple tumor sub-regions of the brain glioma are acquired based on a to-be-processed multi-modal MR image, multiple local ROIs are extracted based on the multiple tumor sub-regions, and then the sub-type of the brain glioma is determined based on the multiple local ROIs and a global ROI. The subtype can be determined through the multi-modal MR image, so that on one hand, non-invasive identification of the subtype is realized, and bleeding and infection risks caused by identification of the subtype are avoided; and on the other hand, the classification accuracy can be improved by utilizing complementary information between different modal images and a boundary form between different tumor sub-regions. Besides, through the fine structure features of each tumor sub-region reserved from a plurality of visual angles by the plurality of local ROIs, and in combination with the spatial distribution context information of the whole brain glioma provided by the global ROI, a better balance between the processing precision and the calculation efficiency can be realized.

The invention relates to the technical field of medical instruments, and discloses a disinfection device for a reproductive medicine examination room, which comprises a flowing gas heating mechanism and a rotary reciprocating shaking mechanism, a lower movable disc which is positioned in the vertical disinfection barrel and can rotate, an upper movable disc which is positioned right above the lower movable disc and can generate a longitudinal reciprocating motion effect, and a storage movable plate which longitudinally moves along with the upper movable disc and can support an instrument are arranged in the vertical disinfection barrel. According to the disinfection device for the reproductive medicine examination room, an instrument is effectively disinfected through disinfection gas, the disinfection gas is gas and has the rapid movement and permeation functions, in addition, the instrument can shake in the disinfection process through the device, the instrument can generate a movement gap through shaking, and therefore the instrument can be disinfected conveniently. And the disinfection gas can generate a flowing disinfection effect along the whole surface of the instrument, so that the disinfection range of the instrument is expanded, and the infection risk of the instrument in the subsequent use process is reduced.

The invention belongs to the technical field of emergency management, and particularly discloses a medical waste classification recovery vehicle path optimization method and system. Comprising the steps that according to infection risk characteristics of different types of medical wastes, an infection risk calculation model for implementing differentiation in the temporary storage, collection and transportation processes of the medical wastes in a medical institution is constructed; constructing a time dependence function under the time-varying road network, and depicting the dynamic change of the driving speed of the recovery vehicle in different time periods; considering exposed groups in road dynamic vehicles, and establishing an infection risk dynamic calculation model in and around the road; constructing a multi-objective optimization model with the total cost and the total infection risk minimized by taking the vehicle load, the road network, the time and the variables as constraints; and carrying out iterative optimization on the multi-objective optimization model to obtain optimal recovery paths and starting time in different time periods. According to the invention, through reasonable risk grading, time-varying road network modeling, risk calculation and path optimization, efficient and safe recovery of medical wastes is realized.

The invention discloses a coating deposition process for an implant, and relates to the technical field of implant coating preparation, and the deposition process comprises the following steps: S1, base material pretreatment: placing a base material in a deionized water mixed solution for ultrasonic cleaning, adopting low-temperature plasma purification treatment, utilizing high-energy particles of plasma to bombard the base material, and using the high-energy particles of the plasma to bombard the base material; the preparation method comprises the following steps: removing surface and internal impurities, introducing active groups, forming a nanoscale rough interface with the surface roughness Ra of 50-200nm on the surface of a base material through a chemical etching process and femtosecond laser etching synergistic process, and carrying out vacuum drying on the base material; s2, metal gasification: placing a metal tantalum raw material in an upstream heating zone of the reaction chamber; the chemical vapor deposition (CVD) technology is adopted, osseointegration can be promoted, the infection risk can be reduced, the method is suitable for porous implantation instruments of the orthopedics department, the dental department and the like, the obtained coating technology is compatible with a complex base material structure, the clinical curative effect and the life quality of a patient are improved, large-scale production is supported, and development of a new material industry chain is promoted.

The invention discloses a wart excision device which combines wart excision and medicine spraying functions, can immediately perform medicine treatment after wart excision, effectively promotes wound healing, reduces infection risk, reduces the possibility of wart recurrence, and improves thoroughness and durability of treatment. And secondly, the operation design of the device is extremely humanized, and the patient can operate the device at home without going to a hospital or a professional medical institution, so that the time and economic cost are greatly saved, and meanwhile, the psychological burden and anxiety mood of the patient caused by seeing a doctor are also relieved. The design of the adjustable blade assembly and the straight blade is adopted by the device, the cutting mode can be flexibly adjusted according to the shape and size of warts, accurate excision is achieved, damage to surrounding normal skin is reduced to the maximum extent, and therefore the pain feeling is reduced, and the size of wounds is reduced. In addition, the medicine applying assembly of the device can accurately spray medicine to the wound surface, pain is further relieved, and rapid healing of the wound is promoted.

The utility model provides an exhaust type infusion apparatus which comprises an infusion tube, an injection needle, a flow speed regulator, a drip cup and a bottle stopper puncture needle, the injection needle, the flow speed regulator, the drip cup and the bottle stopper puncture needle are sequentially arranged on the infusion tube, a precise liquid medicine filter is arranged on the infusion tube close to one side of the drip cup, and an air hole is formed in the side face of the drip cup. A connecting pipe is arranged at the air hole, one end of the catheter is connected with the connecting pipe, the other end of the catheter is used for being connected with an air storage cavity or an exhaust end of the precise liquid medicine filter, and the liquid stopping clamp is arranged on the catheter. In actual use, the liquid medicine filter can solve the technical problems that in the prior art, a liquid medicine filter is prone to causing air gathering, the later filtering effect is poor, and infection risks exist due to the fact that tiny filtering holes existing in the breathable film are directly connected with the outside.

The application belongs to the field of digital medicine, and particularly relates to a chronic obstructive pulmonary disease (COPD) differential system based on digital lung sound, a construction method and application thereof. The system comprises a data acquisition module, a preprocessing module, a conversion module, a data module, a data processing module, a data enhancement training module, a deep learning module, a differential module, a grading module and a display module. Digital lung sound records of candidates are collected, converted into mel spectrograms, and diagnosed by using a deep neural network. The candidates are COPD patients, healthy people, or people suffering from other lung diseases, and the disease grade of the COPD patients is given by a device carrying the differential system. The examination only needs to collect lung sounds in clinical or other places, reduces radiation damage and possible infection risk in the conventional diagnosis process, and provides a scheme for early diagnosis of COPD, and improves the diagnosis efficiency of the respiratory department, especially the COPD disease.

Devices, systems, and methods for stabilizing medical tubing protruding from a patient. In various embodiments of the present disclosure, a medical tubing stabilization device is provided that may include a tube stabilization patch and a complementary medical garment. The tube stabilization patch may be applied to a patient who has medical tubing or a catheter protruding from their body to reduce or dampen movement on the body from the medical tubing in relation to the patient. The medical garment may be worn by the patient and placed in combination with the tube stabilization patch to further reduce the relative movement of the medical tubing. The present disclosure may be directed to reducing the level of medical tubing movement, both externally and internally, that a patient may experience, which decreases the risk of infection caused by catheterization of patients.

The invention relates to the field of medical pipe fitting materials, in particular to an antibacterial and anti-adhesion plastic material for medical pipe fittings and a preparation method of the plastic material, and aims to solve the problems that an existing medical pipe fitting material is poor in antibacterial performance and anti-adhesion performance and cannot meet the use requirements of the medical pipe fittings. According to the preparation method, by compounding the double-ion powder and polyvinyl chloride, the double-ion powder can be stably dispersed in the plastic material, excellent antibacterial performance can be achieved, growth and reproduction of various bacteria can be effectively inhibited, accordingly, the infection risk in the use process of the medical pipe fitting is reduced, the plastic material is endowed with excellent anti-sticking performance, and the service life of the medical pipe fitting is prolonged. The material can reach a bioinert surface, can prevent adhesion of other biomolecules or toxic substances, avoids pollution, also can resist adhesion of tissues, and can be safely applied to medical pipe fittings; meanwhile, the preparation method is simple in process and easy to realize industrial production, the production cost is reduced, and the preparation method has a wide application prospect.