472 results about "Neurologic function" patented technology

The invention discloses a nerve disease detection and analysis method and system, and the method comprises the steps: obtaining a bracelet collection signal, a sphygmomanometer collection signal, a movement behavior image and behavior test data, and extracting tremor intensity features, gait symmetry features and autonomic nerve rhythm features through multi-band decomposition of the bracelet collection signal; analyzing the motion behavior image and the standardized motion test to obtain a motion function score; carrying out heart rate variability analysis to identify a neural function abnormality mode; constructing a neural function state map and calculating a feature weight; predicting a disease progress trend in combination with historical monitoring data; and dynamically adjusting a prediction result through subsequent feedback correction information. Through a mode of combining short-time intensive monitoring and long-term intermittent acquisition, long-term trend prediction and dynamic correction based on initial data are realized, and the reliability and practicability of nerve disease risk assessment in a home scene are remarkably improved.

The invention relates to the technical field of intelligent medical systems, and discloses a cerebral apoplexy onset risk assessment and reminding method and system.The method comprises the steps that continuous medical structured detection data are collected, and the data comprise carotid artery blood flow parameters, brain oxygen saturation, heart rate variability and metabolic indexes; inputting a bidirectional LSTM, a differential convolutional network, a wavelet residual network and a multi-layer perceptron to extract nonlinear features; constructing a neural function coupling structure diagram of four nodes of cerebral blood supply, oxygen supply, autonomous regulation and metabolic steady state; calculating inter-node time sequence offset correlation and a stable factor to obtain a coupling anomaly coefficient; and driving the embedded network by using a graph structure and a node feature input mechanism, and outputting a risk state assessment result. According to the method, the neural function coupling structure diagram is constructed and the mechanism is introduced to drive the embedded network, so that high-precision identification of the multi-system collaborative abnormal state and dynamic evaluation of the stroke risk level are realized.

The invention discloses a neurology patient rehabilitation nursing method based on multi-modal data analysis, and relates to the technical field of medical health, and the method comprises the steps: extracting neural function features through a multi-modal data fusion algorithm, and carrying out the calculation through a weighted fusion and statistical analysis method, and obtaining a neuroplasticity index vector; combining the neuroplasticity index vector with the unified multi-modal feature representation, carrying out multi-modal abnormal mode recognition analysis, obtaining a rehabilitation risk early warning signal and a personalized intervention suggestion, and generating a personalized rehabilitation scheme; performing dynamic optimization and self-adaptive adjustment on the individualized rehabilitation scheme by using a feedback loop mechanism to generate an optimized individualized rehabilitation scheme; physiological signals in individualized rehabilitation training based on the optimized individualized rehabilitation scheme are collected in real time and preprocessed, and a standardized physiological response data sequence is generated. According to the invention, the scientificity, timeliness and individual adaptability of regulation and control are improved, so that nerve function remodeling is accelerated and the rehabilitation risk is reduced.

The invention discloses a cerebral hemorrhage postoperative gastrointestinal hemorrhage prediction method based on an LGBM model. The method comprises the steps of obtaining a multi-dimensional clinical feature sequence of a target patient, screening out a stable feature subset by adopting a Boruta feature selection algorithm, performing nonlinear relation fitting and integrated decision by utilizing a pre-trained LightGBM machine learning model, and generating an individualized ATH risk probability value; and when the risk probability value exceeds a dynamic risk threshold value, triggering a high-risk early warning signal, and based on a Kaplan-Meier survival analysis model, carrying out association mapping on a prognosis track of poor long-term neural function recovery, and finally generating a comprehensive prediction report. According to the invention, accurate quantitative evaluation of ATH risk is realized, clinical intervention timeliness is improved through a dynamic threshold early warning mechanism, short-term complication risk and long-term function prognosis are organically combined, and a comprehensive and reliable prognosis basis is provided for individualized treatment decision.

The invention relates to the field of medicinal chemistry, and particularly discloses a piperidine derivative as well as a pharmaceutical composition, application and a preparation method thereof. The piperidine derivative has the following general formula. The piperidine derivative can be effectively used for treating or preventing multiple sclerosis, and shows an unexpected synergistic effect in an animal model: the piperidine derivative not only can significantly improve neurological function impairment and promote recovery, but also can deeply reduce the levels of key proinflammatory cytokines IFN-gamma and IL-17 at the same time. The invention provides a novel small molecule candidate drug with central permeability, neuroprotection and comprehensive immune regulation functions for treatment of multiple sclerosis.

The invention relates to the technical field of stereotactic surgery, and discloses a neurosurgery stereotactic surgery positioning system based on multi-modal image fusion, which comprises a multi-modal image acquisition module, an intelligent registration fusion module, a three-dimensional modeling module, a surgery navigation engine, an augmented reality interface and a dynamic calibration module, a cross-modal elastic registration module is arranged, when multi-modal image fusion is carried out, the spatial matching degree of a functional image and a structural image is detected in real time through a nonlinear deformation compensation algorithm, and when registration deviation exists between white matter fiber bundles and tumor boundaries, an elastic deformation compensation field is dynamically generated by a system, so that the positioning accuracy of a neural functional area is improved; and by arranging the dynamic drift correction module, the brain tissue displacement change is perceived in real time based on laser surface scanning during deep target navigation, precise correction of the pose of the surgical instrument is realized, and the positioning reliability of the deep target is ensured.

The invention relates to the technical field of intelligent medical auxiliary diagnosis and neural function automatic evaluation, in particular to an NIHSS score automatic evaluation system for a stroke patient. Comprising a multi-mode induction and perception unit which is used as a front-end data entry and is used for collecting patient response in real time to generate a video stream containing depth and color information and a synchronous audio stream; the dynamic reference calibration unit is used for extracting kinematic characteristics to construct an individualized nerve reference template; the neural motion spectrum decomposition unit is used for generating a spectrum pathological feature vector for distinguishing myasthenia and ataxia; the opposite-side image rejection analysis unit is used for generating compensation and driving confidence for representing a real nerve driving intention; the cross-modal reflection analysis unit is used for generating a sensory pathway integrity index according to the nerve conduction velocity difference; and the collaborative scoring decision engine is used for mapping the multi-modal features into standardized NIHSS scores. According to the method, the interference of age and basic physique on scoring is effectively eliminated, and a high-precision comparison reference can be provided for subsequent abnormal judgment of the affected side.

The invention relates to the technical field of health risk assessment, in particular to a neurosurgery risk prediction method and system based on big data analysis, and the method comprises the steps: obtaining the neural signal intensity of a brain region in preoperative functional image data of a patient, analyzing the balance degree of neural signal transmission, and analyzing the balance of oxygen metabolism distribution according to the nerve conduction rate. And preoperative nerve state information is formed. According to the method, by accurately extracting the preoperative neural activity signals and analyzing the signal transmission delay, the fluctuation amplitude and the oxygen metabolism balance, the accuracy of individual neural function state evaluation is improved. In the postoperative recovery stage, the abnormal region is dynamically recognized in combination with the neural signal change trend, and the metabolism matching capacity is evaluated, so that the recovery mode is more refined. Neural network connection adjustment capability analysis enhances signal transmission stability evaluation, and abnormal region identification accuracy is improved by combining time deviation and oxygen metabolism recovery consistency.

The invention relates to the technical field of nervous system dysfunction, in particular to a nerve regulation and control system for degenerative disease treatment based on multi-modal physiological feedback, which comprises a central processing unit, an optical radiation applicator, a mechanical vibration applicator, an integrated biological signal sensing array and a man-machine interaction module, cooperative stimulation is applied by using a multispectral light source and a broadband vibrator, and multi-dimensional physiological signals such as heart rate variability, myoelectricity, galvanic skin and the like are monitored in real time through a sensor array. A multi-parameter adaptive control algorithm built in the central processing unit can dynamically and intelligently adjust stimulation parameters based on the feedback signals to form an accurate personalized treatment closed loop. Meanwhile, the safety monitoring module based on the biological thermal model ensures the safety boundary of the treatment process. According to the invention, intelligent, self-adaptive and non-invasive treatment of nerve dysfunction is realized.

The invention provides a patient consultation intelligent reply method and system based on an RAG knowledge base, and is applied to the technical field of data processing. The method comprises the following steps: preprocessing multi-modal data of a patient to generate text semantic features, voice features, intestinal barrier function features, intestinal immune function features, intestinal nerve function features and image features; performing feature extraction processing on the historical dialogue data of the patient to generate past consultation features and medication feedback features; processing the previous consultation features and the medication feedback features to generate patient portrait information; preprocessing the medical knowledge base data, extracting preset semantic features and storing the preset semantic features to a mixed index structure; the intestinal barrier function features, the intestinal immune function features and the intestinal nerve function features are processed, and intestinal influence factors are generated; and processing the text semantic features, the image features, the patient portrait information and the intestinal tract influence factors based on the dynamically updated medical knowledge base data and an RAG technology to generate target reply information.

The invention provides a brain-computer interface-based TMS and VR collaborative rehabilitation training system, which is characterized in that a multi-mode collaborative positioning module is used for collecting VR interaction data and electroencephalogram data and determining the optimal stimulation state of a subject; the motion intention analysis module is used for matching a rehabilitation mode according to the collected data and in combination with the type of the subject; and the closed-loop rehabilitation interaction module is used for adjusting parameters of the TMS equipment according to the rehabilitation mode and stimulating the final stimulation area under the optimal stimulation state of the subject. For a mild stroke patient, the system dynamically monitors the plastic change of the autonomic nerve and adaptively adjusts the treatment parameters according to the plastic change of the autonomic nerve; for a severe stroke patient, the virtual reality situation is combined to effectively induce motor imagery and synchronously collect and analyze electroencephalogram signals, closed-loop nerve regulation is achieved, synchronous accurate intervention and curative effect optimization of the severe stroke patient are achieved, and an intelligent solution is provided for rehabilitation treatment of the nerve function of the severe stroke patient.

The invention discloses a pathology adaptive prediction control method for a lower limb rehabilitation exoskeleton robot, and belongs to the technical field of rehabilitation robot control. The method comprises the steps that the joint angle, the angular speed and the man-machine interaction torque of the lower limb rehabilitation exoskeleton robot are collected in real time, and a kinetic equation of the lower limb rehabilitation exoskeleton robot is constructed; on the basis of the kinetic equation of the lower limb rehabilitation exoskeleton robot, parameter vectors representing the current pathological features of the patient are estimated online, so that a prediction model in the lower limb rehabilitation exoskeleton robot is updated, and the optimal auxiliary torque is solved. The intelligent brain of the exoskeleton robot can be deeply fused with the real-time state of the body of the patient, and rehabilitation training which is really personalized and self-adaptive and can effectively promote neural function recovery is provided for the patient.

The invention discloses a nerve postoperative pain monitoring and feedback method and system, and relates to the technical field of medical information, and the method comprises the following components: a data acquisition step, a digital twin model construction step, a pain simulation step, a visualization and interaction step and a feedback and scheme making step. By constructing the digital twinborn model of the postoperative body of the patient, the postoperative physiological structure, the nerve function state and the pain-related physiological mechanism of the patient can be accurately simulated, and based on the model, a doctor can simulate different treatment schemes and pain responses under external stimulation, so that a more personalized pain management scheme is formulated, and the pain management efficiency is improved. According to the personalized management mode, the accuracy of pain management is remarkably improved, postoperative pain of the patient can be relieved more effectively, and the treatment experience and satisfaction degree of the patient are improved.

The invention discloses a cerebral apoplexy patient postoperative neural function real-time monitoring method. The method comprises the steps that brain MRI image data and clinical information of a to-be-monitored patient and post-operation electroencephalogram data collected in real time are collected and preprocessed; respectively extracting neurophysiological features and radiomics features of the patient to be monitored based on the preprocessed data; performing significant feature screening on the clinical information, the neurophysiological features and the radiomics features, performing preprocessing on the screened data, and combining minimum absolute contraction and selection operator regression analysis to obtain quantitative electroencephalogram data feature indexes and radiomics scores; inputting the screened clinical information, the quantitative electroencephalogram data characteristic index and the radiomics score of the to-be-monitored patient into a trained prediction model, and predicting a risk index of early neurological deterioration of the to-be-monitored patient; the problem that the evaluation result is inaccurate due to the fact that a single clinical feature is adopted to evaluate the neural function in a traditional method is solved.

The invention provides a nerve regulation and control system and method for a spinal cord ventral epidural region, and the system employs a microprocessor to generate multiple paths of pulse width modulation signals, and drives a voltage-controlled current source after amplitude adjustment. Stimulation current with adjustable frequency, pulse width and amplitude is output to act on a spinal cord ventral nerve structure. Real-time monitoring of stimulation current of each channel is realized through combination of voltage sampling and a single-pole multi-throw analog switch, feedback information of a body position, myoelectricity, pressure and other multi-mode sensors is fused, a closed-loop control mechanism is constructed, and dynamic adjustment and individualized optimization of electrical stimulation parameters are realized. The system has the advantages of being more accurate in electrical stimulation positioning, more sensitive in response, more intelligent in control and the like, and is suitable for intelligent rehabilitation intervention in scenes of spinal cord injury, cerebral palsy, neurological dysfunction and the like.

The invention provides an epinephrine automatic injection patch and method for cardiovascular first aid, and the injection patch comprises a flexible biosensing layer which obtains the subcutaneous impedance value and vital sign parameters of a patient; the microneedle array is used for adjusting the penetration depth based on the subcutaneous impedance value and controlling the deformation quantity through a piezoelectric actuator; the micro-fluidic pulse drug delivery module is connected with the micro-needle array and is used for executing pulse type drug injection according to the penetration depth; and the control module is used for judging an autonomous circulation recovery state based on the vital sign parameters and triggering the microfluidic pulse administration module to stop injection. According to the application, by constructing a first-aid closed loop of'multi-mode physical sign dynamic monitoring-self-adaptive microneedle administration-ROSC intelligent termination ', the response speed of epinephrine injection is increased, the bioavailability is improved, the risk of excessive medication is reduced, and the gold rescue efficiency and the neurological function prognosis rate of pre-hospital cardiac arrest patients are remarkably improved.

The invention discloses a functional hydrogel microsphere and a preparation method and application thereof, and relates to the technical field of medicines.The preparation method comprises the steps that a hyaluronic acid methacrylic acid precursor solution and an IL-1beta shRNA adenovirus stock solution are mixed to obtain an Ad-atHAMA precursor solution; preparing the Ad (at) HAMA precursor solution through an oil-in-water micro-fluidic technology to obtain an Ad (at) HAMA microsphere; and sequentially adding the Ad (at) HAMA microspheres, 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide and N-hydroxysuccinimide into a 2-morpholinoethanesulfonic acid buffer solution, carrying out activating treatment, adding E selectin, and incubating to obtain the functionalized hydrogel microspheres. The functionalized hydrogel microspheres can inhibit a related mechanism of acute spinal cord injury pathological progress and promote neural function repair by targeting adsorption of neutrophil to regulate Nets-triggered innate immune inflammation cascade.

The invention relates to a stroke prognosis prediction model training method based on quantum computing and artificial intelligence, and relates to the technical field of prognosis effect prediction. According to the method, leukocyte community parameters are introduced into an acute ischemic stroke prognosis model for the first time, morphological function characteristics of leukocytes are detected through a flow cytometry, and compared with traditional inflammation indexes, the leukocyte prognosis model has higher sensitivity and objectivity and becomes an important index for predicting neurological function impairment; the indexes closely related to cerebral apoplexy prognosis are screened out through quantum calculation for the first time, and a new thought is provided for high-dimensional data feature screening; meanwhile, by comparing 14 traditional machine learning, integrated learning and deep learning models, it is judged that the LightGBM model is an acute ischemic stroke prognosis prediction model, and compared with the prior art, the LightGBM model is remarkably improved.

The invention relates to the technical field of medical instruments, in particular to a multi-mode biological feedback ear vagus nerve self-adaptive stimulation device and method.The device comprises a host, a stimulation electrode, a signal collection bracelet and an electroencephalogram collection module, and the host comprises core hardware configuration and a power management system; the signal acquisition bracelet comprises an ECG module, a PPG module, a GSR module, a six-axis acceleration sensor and the like. The ear vagus nerve stimulation parameter can be dynamically adjusted through real-time analysis of multi-mode data such as electrocardio, electroencephalogram, heart rate variability, respiration-heart rate synchronism and emotional state, personalized precise treatment is achieved, meanwhile, the wearing comfort and the durability of the device are improved, and the application range is wide. The traditional Chinese medicine composition can be used for auxiliary treatment of various diseases such as inflammatory bowel disease, epilepsy, chronic insomnia, depression, chronic pain, anxiety disorder, post-traumatic stress disorder and autonomic nerve dysfunction, and the functions of a nervous system are adjusted and the symptoms of a patient are improved by accurately stimulating the vagus nerve in the auricular concha area.

The invention provides a brain disease drug curative effect analysis and prediction system and method, and relates to the technical field of drug analysis. Multi-source heterogeneous data such as genetic variation spectrum, neural image topological characteristics, metabolic trajectory vectors and microbiome dynamic distribution matrix are integrated, and cross-modal dynamic fusion is realized through decomposition. The system constructs a drug prediction coupling network based on dynamic causal inference, analyzes overlapped potential intervention nodes of multiple disease mechanisms, and generates a disease-drug-phenotype multi-dimensional mapping library. A short-term drug response toxicity threshold is predicted through a metabolic entropy change model, a long-term neurological function degeneration trajectory is evaluated in combination with epigenetic drift, and an anti-fact strategy gradient is utilized to dynamically optimize a drug administration scheme. According to the invention, accurate fusion and dynamic analysis of multi-modal data are realized, a balance mechanism of curative effect and risk is established, and accurate drug combination sequence and administration strategy support can be provided for individualized treatment of complex brain diseases.

The invention discloses a nervous system function evaluation method and device, computer equipment and a medium, and relates to the technical field of intelligent medical treatment. The specific implementation mode comprises the following steps: acquiring sensor data of a plurality of body parts of daily activities of a user, wherein the sensor data is acquired through a sensor arranged in a home environment; obtaining a plurality of motion function evaluation parameters according to the sensor data; obtaining a nervous system function evaluation result based on the whole-age group normal population data model according to the multiple motion function evaluation parameters; and outputting a neurological function risk index and a risk index of the user according to a nervous system function evaluation result. According to the scheme, the nervous system function is evaluated by obtaining multiple evaluation parameters in daily life, and the accuracy and reliability of the evaluation result and the use flexibility of the evaluation method are improved.

The invention discloses a cerebral hemorrhage heterogeneity quantitative evaluation system based on cyclic cross-attention clustering, and relates to the field of cerebral hemorrhage evaluation, and the system comprises an image segmentation module which is used for carrying out the three-dimensional segmentation of a brain plain-scan CT image through an nnU-NetV2 model, and outputting the binary masks of a hematoma region and an edema region; the feature extraction module is used for extracting high-dimensional pixel features from the mask region and generating an initial feature embedding matrix; the cyclic cross-attention clustering module is used for dynamically updating a clustering center through a multi-scale cyclic EM cross-attention mechanism and executing clustering analysis on the feature embedding matrix; the heterogeneity scoring module is used for calculating information entropy and generating hematoma and edema heterogeneity scores; and the prognosis prediction module is used for predicting the hematoma expansion risk and the neural function outcome through a machine learning model. According to the scheme, objective quantification of cerebral hemorrhage heterogeneity can be realized, and the prediction accuracy of the hematoma expansion risk and the neural function outcome is improved.

The invention provides multifunctional bionic hydrogel as well as preparation and application thereof in traumatic brain injury treatment, and belongs to the field of biomedical materials. The preparation method comprises the following steps: combining polydopamine modified hemoglobin nanoparticles with curcumin-based carbon quantum dots with anti-inflammatory activity, and embedding into bionic hyaluronic acid-collagen double-network hydrogel, so as to prepare the multifunctional bionic hydrogel. The hydrogel can effectively relieve neuron hypoxia, reduce apoptosis, promote the polarity of microglial cells to be converted into anti-inflammatory phenotype, and significantly down-regulate the expression of S100A8, thereby inhibiting pathological neural immune crosstalk. In a traumatic brain injury model, hydrogel implantation improves the pathological microenvironment, enhances endogenous nerve regeneration, and ultimately results in significant neurological function and cognitive recovery. The multifunctional bionic hydrogel prepared by the invention has a good application prospect in preparation of materials for preventing and / or treating traumatic brain injury.

The invention discloses a medical image-based spinal cord injury analysis method and system, and belongs to the technical field of image analysis, and the method comprises the steps: obtaining MRI images of a target object at a plurality of time points, carrying out the registration and normalization processing, and constructing a time sequence image set; extracting a spinal cord and an injury area by adopting a dynamic segmentation network guided by a spinal cord structure; constructing a time sequence deformation path of the damaged area based on a form tracking algorithm; extracting high-order morphological characteristics including a curvature change rate, an edge contour jump value and a spinal cord compression rate; performing double-domain modeling on the features and neural function scores, and training a structure-function coupling model; the model is used for performing functional state prediction, risk area identification and rehabilitation suggestion output on a new patient, and the method has the advantages of being high in predictability, high in accuracy, remarkable in clinical auxiliary value and the like.

The invention relates to a bionic nano CO generator as well as preparation and application thereof, belongs to the technical field of medicines, and solves the problem that a CO delivery system which can synergistically promote neuroprotection and neurogenesis and has brain targeting and controlled release capabilities is urgently required to be developed at present. According to the technical scheme, the bionic nano CO generator comprises a drug-loaded particle inner core and a covering film, the drug-loaded particle inner core comprises hollow mesoporous CeO2 nano particles and MnCO loaded on the hollow mesoporous CeO2 nano particles, and the covering film is a macrophage membrane and wraps the drug-loaded particle inner core. The compound is used for apoplexy treatment administration by integrating neuroprotection and enhancing innovative dual channels of endogenous nerve growth, and is expected to significantly reduce brain injury after cerebral apoplexy and restore neurological functions so as to relieve the worry about high death rate and long-term disability after cerebral ischemia-reperfusion injury.

The invention belongs to the technical field of nutritional compositions, and particularly relates to a composition, a preparation method thereof and application of the composition in protecting brain health. The composition provided by the invention is prepared from docosahexaenoic acid, 3-sialic acid lactose and phosphatidylserine. The composition is clear in sleep improvement effect, can effectively solve the problem of sleep maintenance caused by sleep deprivation, has the effects of protecting neural functions, improving memory and relieving anxiety from multiple dimensions, and can repair brain tissue damage and protect brain health. Based on the composition, products for assisting in improving memory, preventing and treating insomnia and anxiety, regulating neurodevelopmental disorders, protecting brain health and improving concentration can be developed, the health requirements of different people are comprehensively met, and the application value is high.

The invention provides a method for establishing a mouse postoperative delirium model under a simulated high altitude urgent entry environment, and relates to the technical field of animal model establishment. According to the method for establishing the model for simulating postoperative delirium of the mouse in the sudden entering plateau environment, a control group (group C), a plateau group (group H), a POD model group (group P) and a plateau POD model group (group HP) are included, behavior changes of the mouse are evaluated through a Y maze experiment, then the mouse is killed, brain tissue is taken, and the mouse is subjected to postoperation delirium simulation in the sudden entering plateau environment. The mouse hippocampus tissue structure damage change is observed through morphological methods such as Nissl staining and a transmission electron microscope, meanwhile, blood is taken through mouse eye sockets, the concentration of inflammatory related indexes IL-6 and TNF-alpha in serum is measured through an ELISA method, and the stability and repeatability of model establishment are known. The plateau postoperative delirium mouse model prepared by the invention can generate obvious damage to brain tissues and neurological functions, and is high in operability and good in repeatability.

The invention relates to the technical field of exosome preparations, and particularly discloses an exosome nasal delivery preparation as well as a preparation method and application thereof. The preparation comprises the following components: 1 * 10 < 9 >-5 * 10 < 11 > particle number / ml of exosome, 1%-4% w / v of a saccharide protective agent, 0.5%-4.5% w / v of an alcohol protective agent, 0.05%-1% w / v of an absorption enhancer and a solvent. The exosome nasal delivery preparation can break through the blood brain barrier and quickly take effect, and the intracerebral delivery efficiency of the exosome nasal delivery preparation can be improved by 2-5 times compared with intravenous injection. The nasal administration preparation can be used for treating central nervous system diseases such as cerebral apoplexy and the like, and can remarkably improve the neurological function, reduce the cerebral infarction area and promote functional recovery.

The invention discloses a construction method and application of a neurological function prognosis prediction model after cardio-pulmonary resuscitation, and the method comprises the steps: obtaining clinical data of a patient reaching spontaneous circulation recovery after cardio-pulmonary resuscitation, and screening a clinical patient meeting a discharge standard; taking brain function classification as dependent variables, respectively adopting an LASSO regression analysis method and a Boruta feature screening method to screen feature variables, and selecting common feature variables; constructing a plurality of machine learning models based on the common feature variables, and drawing an ROC curve and a decision curve corresponding to each machine learning model; carrying out discrimination evaluation on the machine learning model by adopting AUC, evaluating clinical benefits of the machine learning model by adopting a decision curve, and screening an optimal prediction model; and explaining the optimal prediction model and the common feature variables by adopting an SHAP tool. The prediction model constructed by the invention can conveniently and quickly predict the prognosis condition of the neurological function within 24 hours after sudden cardiac arrest and resuscitation.

The invention discloses a bionic nano system for treating acute ischemic stroke and application of the bionic nano system. According to the preparation method disclosed by the invention, the TNK-DNaseI (at) ZIF-8 nano-particles are prepared by loading the ZIF-8 with the TNK-DNaseI (at) ZIF-8 and then the TNK-DNaseI (at) ZIF-8 nano-particles are coated with the natural platelet membrane, so that the TNK-DNaseI (at) ZPM bionic nano-system is prepared. The bionic nano system can achieve efficient thrombolysis, obviously reduce the infarct area, improve neurological impairment and reduce bleeding complications. The invention provides a new drug choice for treating the acute ischemic stroke, and has a wide application prospect in the aspects of clinically treating the acute ischemic stroke and improving the prognosis of a patient with the acute ischemic stroke.