157 results about "Targeted interventions" patented technology

The invention provides a neurology clinical nursing potential safety hazard analysis method and device, and relates to the technical field of neurology clinical nursing, and the method comprises the steps: inputting a risk feature matrix generated based on multi-source heterogeneous nursing data into a rule engine and graph neural network model, and outputting a preliminary screening risk event set; taking the primary screening risk event set and the risk feature matrix as input, and constructing a causal conduction map through a causal discovery algorithm; performing risk conduction quantitative integration on each risk event in the primarily screened risk event set based on a causal conduction map to generate a quantitative risk list; based on the dynamic risk priority number and the conduction path chain, reversely tracing to a root cause node along a directed conduction edge, and generating a targeted intervention strategy packet bound with the root cause node; the targeted intervention strategy package is pushed to the nursing responsible person terminal, the strategy execution effect and the risk evolution data are recorded, and a closed-loop disposal database is generated, so that the dynamics and the effectiveness of potential safety hazard analysis of clinical nursing of the neurology department are improved.

The invention relates to a psychological counseling interaction method and device based on an autonomous psychological planning architecture. The method comprises the following steps: acquiring initial user data of a target user; constructing a dynamic target map of a target user through a three-layer nested target structure, and pre-loading a matched personalized decision tree; after receiving the real-time interaction data, executing real-time path re-evaluation based on the real-time interaction data to obtain a treatment value function of each intervention path; constructing an intervention response prediction model by adopting a Bayesian network and a Monte Carlo tree search algorithm, adjusting the priority and the execution sequence of the intervention paths in the personalized decision-making tree in combination with the treatment value function of each intervention path, and selecting a target intervention path matched with the real-time interaction data from the adjusted intervention paths; the real-time interaction data is mapped into the multi-dimensional psychological state space to serve as the session trajectory, session trajectory planning is conducted based on the target intervention path, real-time interaction with the target user is achieved, and the accuracy of intervention decision making and the session fluency are improved.

The invention relates to the technical field of medicine and artificial intelligence, and discloses an elderly care-oriented medical and nursing combined knowledge service system construction method, which comprises the following steps of collecting sentiment expression data of the elderly, applying a nonlinear time sequence analysis and deep learning model, extracting sentiment dynamic characteristics, and obtaining sentiment expression data of the elderly; recognizing an early signal with reduced emotion regulation ability; on the basis of the obtained emotion dynamic features, a memory enhanced attention network is combined with a psychological knowledge graph, an individualized emotion cognitive interaction model of the old people is constructed, a dynamic interaction mechanism between an emotion state and a cognitive mode is revealed, and key intervention nodes are recognized; based on an emotion cognition interaction model and a key node recognition algorithm, the system can accurately position key links of mutual influence of emotion and cognition, and targeted intervention is achieved; and a dual-channel collaborative intervention strategy adjusts an emotional state and reconstructs a cognitive mode through multi-agent reinforcement learning, and breaks through an emotional cognitive vicious circle.

The invention discloses an irrigation oasis regulation potential quantification and targeted intervention strategy generation method and system, and the method comprises the steps: dividing a target irrigation oasis region into a plurality of management units, obtaining the multi-source data of all management units, and calculating the coupling coordination degree of each management unit; the management unit with the coupling coordination degree smaller than the regulation lower limit serves as a unit needing to be regulated, and the difference value between the coupling coordination degree of the unit needing to be regulated and the corresponding regulation lower limit or regulation upper limit serves as the regulation potential; constructing and training a Bayesian causal network, and calculating mutual information or belief variance of each driving node of the unit needing regulation and control to a target node by adopting the probability output by the trained Bayesian causal network according to the coupling coordination degree and the index of the unit needing regulation and control; and taking the driving node with the highest mutual information or belief variance as a main control factor of the corresponding unit needing to be regulated and controlled, and searching a targeted intervention strategy of the unit needing to be regulated and controlled in the factor-strategy knowledge base by adopting the main control factor.

The invention relates to a precise health monitoring method based on multi-source data fusion. The method comprises the following steps of 1, collecting multi-source data; step 2, data preprocessing; step 3, multi-source data fusion; 4, health analysis and decision making; step 5, dynamic weight adjustment; and step 6, feedback optimization. The hierarchical fusion strategy is adopted to process heterogeneous data, a machine learning algorithm is combined to establish an individualized health model, physiological state changes are tracked in real time, a targeted intervention scheme is generated, and in terms of technical implementation, the system supports collaborative decision making of various analysis models, including rule-based behavior reasoning, time sequence feature analysis and environment threshold judgment, and the system has the advantages of being simple in structure and convenient to use. The contribution degrees of information of different sources are balanced through an adaptive weight distribution mechanism, time-frequency analysis and dimension reduction technologies are fused in the feature extraction process, the dynamic mode of the health state is effectively captured, cross validation optimization is adopted in model training, and the reliability of an evaluation result is ensured.

The invention discloses an infantile autism three-early evaluation method and rehabilitation training cloud platform based on child visual size perception, and the method comprises the steps: constructing a multi-core ability dimension question bank based on Delphi expert scoring and an analytic hierarchy process, and dividing the question bank into a plurality of hierarchies according to size perception ability factors, each hierarchy comprises a plurality of test tasks for testing the size perception ability of the user, dynamically matching an initial test hierarchy through ASQ development month age, realizing cross-layer question insertion by utilizing a dynamic dominant layer polling mechanism, recording behavior and eye movement characteristics of the user, and automatically collecting the behavior and eye movement characteristics of the user as evaluation indexes; evaluating the big and small feeling perception ability of the user by comprehensively calculating the evaluation indexes, obtaining an evaluation result, and adaptively executing intervention measures according to the evaluation result. According to the invention, through fusion of a seven-factor dominant layer polling mechanism and eye movement-behavior bimodal data, accurate identification, scientific diagnosis and targeted intervention of visual perception abnormity of autistic children are realized.

The invention relates to the technical field of health monitoring, in particular to a health state alarm response system based on multi-dimensional monitoring, which comprises a dynamic threshold module, a physiological monitoring module, an anomaly positioning module, an inducement output module, an anomaly intervention module and an early warning response module, according to the method, multi-dimensional original data of a user is collected, meanwhile, a timestamp alignment and scene label binding technology is adopted, an exclusive physiological index normal fluctuation interval library is constructed for different large classes of scenes, then the problem of misjudgment of a static threshold value is fundamentally solved, the cause of'abnormity 'is deeply and accurately positioned, and the accuracy of the abnormal condition is improved. The abnormity-scene-behavior-cause full-link association not only enables the user to clearly know the cause of the abnormity, but also provides data support for the medical personnel to formulate a targeted intervention scheme, and reasonably formulates the targeted intervention scheme based on the intervention list, thereby avoiding the ineffectiveness of general suggestions, enabling resources to be inclined to high-risk users, and improving the user experience. The complication occurrence rate is effectively reduced.

The invention provides a pension service supervision method and system based on an image recognition AI model algorithm. The method comprises the following steps: aiming at respiratory arrest, pressure sores and limb stiffness risks in a bedridden old-age care scene, firstly, establishing a physiological abnormality library containing parameters such as a respiratory rate threshold value and a body pressure critical value; a physical sign monitoring device is deployed to collect body pressure hot area distribution data of the bedridden person in real time, breathing interval abnormity, heartbeat attenuation and body pressure exceeding areas are analyzed through an AI model, and a retention risk index is generated. And when the monitoring data exceeds an abnormal library threshold value, triggering multi-modal early warning information, fusing risk area positioning, abnormal duration and temperature gradient change, outputting a multi-modal early warning report combining images and texts, and guiding the nursing personnel to perform targeted intervention. According to the technical scheme provided by the invention, real-time monitoring and multi-mode risk early warning of health hidden dangers in bed are realized, the occurrence rate of complications such as respiratory arrest and pressure sores is reduced, and the precision and response efficiency of nursing for the aged are improved.

The invention discloses a colorectal cancer metabolism-related prognosis model construction method based on multiple omics. By integrating multiple omics data, the defect is overcome, a new view angle and method are provided, the accuracy and practicability of the prognosis model are effectively improved, and the blank in the prior art is filled. Meanwhile, the method provided by the invention is not only suitable for prognosis prediction of colorectal cancer patients, but also can be popularized and applied to other types of cancers. As the metabolism-related gene plays an important role in various cancers, the technical scheme provided by the invention has relatively high universality and popularization value, and can provide reference for prognosis prediction and personalized treatment of other cancers. Finally, the prognosis model provided by the invention can be used as a clinical decision support tool to help doctors to make more scientific and accurate decisions in diagnosis and treatment processes. Through early recognition of high-risk patients and implementation of targeted intervention measures, prognosis of the patients can be significantly improved, and the risk of relapse and metastasis can be reduced.

The invention relates to the technical field of intelligent monitoring, and particularly discloses an intelligent monitoring method and system for hemodialysis patient complications, and the method comprises the following steps: S1, carrying out the fusion to form a multi-modal feature set, S2, constructing an individualized risk feature map, S3, generating complication risk probability distribution, S4, calculating an individualized risk threshold value, and S5, generating an intervention suggestion sequence. The method comprises the following steps: acquiring physiological parameters of a hemodialysis patient and operation parameters of dialysis equipment, identifying a coupling relationship between the parameters, constructing an individualized risk characteristic spectrum, predicting a characteristic change trend, matching the characteristic change trend with a historical complication mode, calculating an individualized risk threshold to trigger early warning, generating targeted intervention suggestions, and monitoring an effect. According to the system, the accuracy and timeliness of hemodialysis complication monitoring are effectively improved, the complication occurrence rate is reduced, the workload of medical staff is relieved, and the safety and effectiveness of hemodialysis treatment are improved.

The invention relates to the technical field of medical instruments, in particular to a constipation adjuvant therapy appliance and a using method thereof.The constipation adjuvant therapy appliance comprises an insertion tube, a vibration sleeve is arranged at the inner end of the insertion tube, and a vibration motor is arranged in the vibration sleeve; the outer end of the insertion pipe is connected with a medium pipeline used for inputting or outputting a medium into or out of a pipe cavity of the insertion pipe. A plurality of protruding blocks are arranged on the pipe wall of the outer side of the insertion pipe. Through mechanical pressure generated by expansion of the insertion tube and the adjusting cavity of the insertion tube and local stimulation of the outer side protruding block on the rectum wall, low-frequency vibration of the vibration motor in the vibration sleeve is combined, a rectum wall mechanical receptor and a nerve conduction path are cooperatively activated in a multi-mode mode, defecation reflex is triggered, and therefore targeted intervention on defecation reflex disorder of a constipation patient is achieved. The defect that a traditional therapy does not touch a neural mechanism is overcome, and a comprehensive solution from physiological reflex activation to mechanical power enhancement is provided for constipation treatment.

The invention discloses a classroom psychological state recognition system based on multi-modal data, particularly relates to the field of image recognition, and is used for solving the problem that an existing classroom monitoring mode cannot effectively capture group emotions and lacks targeted intervention. The method comprises the following steps: detecting and positioning a multi-view video sequence through a target tracking module, extracting a student face image and establishing an identity frame sequence relationship; the emotion recognition module performs expression recognition on the image to generate an emotion intensity time sequence; the emotion analysis module performs time-frequency analysis on the sequence, extracts rhythm frequency and phase parameters and generates a region-level emotion curve according to seat layout aggregation; the drift calculation module calculates the phase difference and the frequency difference between the regions, and constructs a rhythm drift matrix; the propagation visualization module maps the matrix into a space vector field, and generates an emotion propagation path visualization model; and the intervention prompt module completes source positioning and intervention strategy generation based on the model, and realizes classroom psychological state identification and regulation.

This invention relates to diselenylene-bridged mesoporous silica nanoparticles loaded with baicalin and their applications. The invention constructs a ROS-responsive, microglia-inspired Ba@Se-MSN&BV2 nanoplatform targeting the secondary phase of spinal cord injury. The BV2 cell membrane-mediated enrichment at the injury site, combined with the diselenylene-triggered, on-demand release of baicalin, enables targeted intervention in a highly oxidative and pro-inflammatory microenvironment. In vitro and in vivo studies show that Ba@Se-MSN&BV2 can alleviate oxidative stress and mitochondrial dysfunction, inhibit apoptosis, promote axonal and neuronal survival, and improve motor circuit function. This invention provides a new therapeutic target and research direction for neuroinflammatory injuries driven by redox homeostasis disruption, with significant clinical application prospects and social value.

The invention discloses a student portrait analysis and intervention measure design method and system based on generative artificial intelligence, and belongs to the crossing field of artificial intelligence and education technologies. The method comprises the following steps: obtaining a prediction result and feature contribution analysis of an interpretable machine learning model; constructing a hierarchical knowledge base system; the LoRA fine tuning technology is adopted to carry out domain adaptation on the large language model, and output consistency and professionality are ensured; establishing a student evaluation standard system of dynamic weights, and adaptively adjusting the evaluation weight of each dimension according to the grade of the student; designing a structured prompt template, and generating a special prompt for different analysis tasks; personalized student portraits are generated based on knowledge base retrieval and large model reasoning, and qualitative description and quantitative scoring are included; and generating targeted intervention measures in combination with the private experience knowledge base. According to the method, organic combination of quantitative analysis and qualitative description is realized, the generated student portrait is more comprehensive and accurate, and intervention suggestions are more professional and operable.

The invention relates to the technical field of intelligent monitoring of mental health, and discloses a social function prediction system for teenager patients with depression. The system comprises a multi-source data acquisition module, a psychological feature fusion module and a prediction engine module. The multi-source data acquisition module is used for acquiring social interaction records of patients, constructing behavior dynamic characteristics, performing mode recognition and generating behavior mode data. And the psychological feature fusion module performs difference comparison on the behavior data and a healthy group benchmark, screens key behavior indexes, and calculates correlation degree values of the key behavior indexes and psychological assessment parameters in real time. The prediction engine module evaluates the social function degradation type based on the correlation degree, locates vulnerable nodes in the development process, and identifies specific dysfunction points. According to the system, continuous dynamic monitoring of social function states is realized, early warning of degradation risks and accurate positioning of weak links are realized through behavior-psychological correlation analysis, and technical support is provided for targeted intervention.

The invention belongs to the technical field of reproductive medicine and clinical metabolism intervention, and particularly relates to a group of markers for diagnosing unexplained recurrent abortion and application thereof. Aiming at the clinical pain point that unexplained recurrent abortion (URSA) lacks accurate metabolic typing diagnosis indexes and targeted treatment means, based on detection of a large number of clinical samples and verification of cell experiments, direct association between down-regulation of levels of choline related metabolites and trimethylamine oxide (TMAO) of decidua tissues and the RSA is disclosed for the first time; the core effect of TMAO in-situ synthesis of decidua stromal cells (DSC) in regulation and control of the decidualization process is determined; meanwhile, an RSA indication screening system of joint detection of serum creatinine and decidua choline metabolism is constructed, a targeted TMAO targeted intervention scheme is formed in a matched mode, a diagnosis and treatment closed loop of RSA from precise typing to targeted treatment is achieved, and a brand new technical path is provided for clinically solving the URSA diagnosis and treatment problem.

The invention relates to application of a targeted intervention strategy based on a TRIM25-SNRK regulatory axis in treatment of non-small cell lung cancer. The nucleotide sequences of the mRNA of the TRIM25 gene and the mRNA of the SNRK gene are respectively as shown in SEQ ID NO.1 to SEQ ID NO.2. According to the invention, it is found for the first time that the combined targeting TRIM25-SNRK regulatory axis has a more significant cancer inhibition effect in the cell proliferation and migration process of the non-small cell lung cancer compared with single interference of TRIM25 expression level or transfection of exogenous SNRK mRNA expression plasmids. The siTRIM25 and SNRK-OE combination strategy designed by the invention can specifically knock down the level of TRIM25 mRNA and up-regulate the level of SNRK mRNA at the same time, and compared with the condition of singly transfecting siTRIM25 or SNRK-OE, a cell function experiment shows that the combination strategy has a more effective anti-tumor effect. Therefore, the TRIM25-SNRK regulation axis can be used as an intervention target to be applied to research, development and preparation of non-small cell lung cancer antitumor drugs.

The invention discloses a composition for improving immunity and delaying senescence and a preparation method thereof. Belongs to the technical field of functional health. The composition comprises the following components in parts by mass: 5-50 parts of collagen, 10-80 parts of paeonia ostii tea, 1-20 parts of an antioxidant, 3-10 parts of an intestinal microecology regulator and 1-3 parts of an energy metabolism and nerve regulator. According to the invention, through multi-system cooperation and multi-target intervention, dual effects of immune enhancement and senescence delay are realized. Through scientific compounding and a special process, the product has the advantages of stable components, uniform activity and good solubility. Animal experiments and theoretical models show that immune organs can be effectively protected, accumulation of aging markers is reduced, and a solution is provided for development of comprehensive anti-aging health products.

This invention confirms that ventral hippocampal ignition leads to functional reorganization of the ventral hippocampal excitatory circuits. Most notably, this results in increased connectivity with the medial prefrontal cortex, increased activation on fMRI, and increased electrophysiological activation amplitude. Evidence suggests increased anxiety after ignition. This invention provides a method for imaging a single epileptic seizure using simultaneous LFP-fMRI. Imaging the spatiotemporal dynamics of an individual epileptic seizure can characterize the propagation patterns of focal and secondary generalized seizures, thereby providing targeted interventions.

The application provides an antisense oligonucleotide Jag-i9 ASO and application thereof, relates to the technical field of biological medicine, and the antisense oligonucleotide Jag-i9 ASO has the sequence of 5'-ACTGGGCCCTGCACCTGA-3'. By providing the antisense oligonucleotide of a specific sequence, the binding site of target heterogeneous ribonucleoprotein K and the Jag2 gene is targeted, the expression of the pro-inflammatory Jag2 subtype is inhibited, the Jag2 gene splicing site can be accurately targeted, the heterogeneous ribonucleoprotein K binding function is specifically blocked, a targeted intervention means is provided for the treatment of myocardial ischemia-reperfusion injury, the generation of the pro-inflammatory subtype is inhibited by efficiently and accurately regulating the alternative splicing of a specific gene, myocardial cell apoptosis and inflammatory response are reduced, myocardial function is improved, and a new approach is provided for the prevention and treatment of myocardial ischemia-reperfusion injury, the treatment effect is improved, and the advantages of reducing side effects are achieved.

The invention belongs to the technical field of biological medicines, and particularly relates to application of CDK9 as a target spot in preparation of a medicine for preventing and treating oral leukoplakia canceration. The invention proves that the phenomenon of transcriptional activity increase and the characteristic of transcription addiction exist in the oral leukoplakia canceration process, and a driving factor cyclin-dependent kinase 9 (CDK9) closely related to oral leukoplakia transcriptional disorder is screened out. Moreover, a molecular mechanism of CDK9 driving oral leukoplakia transcription addiction is further clarified, an important role of CDK9 in an oral leukoplakia canceration process is clarified, and transcription addiction of oral leukoplakia cells can be effectively inhibited through targeted intervention of activity or expression level of CDK9, so that canceration potential of oral leukoplakia can be effectively prevented and treated.

The invention relates to the technical field of data processing, and discloses a risk assessment method and system based on multi-modal data, a terminal and a storage medium, and the method comprises the steps: obtaining the multi-modal data of a patient, carrying out the matching and calculation based on a preset VTE risk assessment rule according to the multi-modal data, and obtaining a basic risk level and a basic prevention strategy; obtaining dynamic time sequence data of a patient, adjusting the basic risk level according to the dynamic time sequence data, generating a plurality of dynamic risk weights, and performing fusion calculation on all the dynamic risk weights to obtain a scoring result; and obtaining an early warning trigger condition, determining a target intervention strategy in the basic prevention strategies according to the early warning trigger condition and the scoring result, and executing the target intervention strategy. According to the method, the VTE risk of the patient is iteratively optimized through a dynamic weight fusion mechanism, and the accuracy of risk assessment and intervention strategies is greatly improved.

The invention discloses an ADHD child food addiction neural mechanism evaluation method based on fMRI, and the evaluation method mainly comprises the following steps: obtaining the test results of the attention, execution function, intelligence quotient and food addiction of to-be-evaluated children, and dividing the to-be-evaluated children into an ADHD with food addiction group, an ADHD without food addiction group and a health control group according to the results; performing fMRI stimulation normal form execution after grouping, and performing brain function data acquisition; and finally, constructing a mathematical model of neural image data analysis, so that a specific neural circuit of ADHD children food addiction and a mechanism modulated by an emotional state can be revealed non-invasively and objectively, and an important scientific basis and tool are provided for early recognition, pathological mechanism research and targeted intervention strategy development of ADHD co-disease food addiction.

The invention provides an oligopeptide targeting SUV39H1 and application of the oligopeptide in tumor treatment. The amino acid sequence of the oligopeptide is shown as SEQ ID NO: 1. According to the oligopeptide, a PRMT1 and SUV39H1 binding region is precisely targeted, so that the interaction between the PRMT1 and the SUV39H1 is effectively blocked, meanwhile, the methylation level and the protein level of the SUV39H1 are reduced, and precise targeted intervention on the SUV39H1 is realized. The invention provides a novel SUV39H1 intervention means which is accurate in targeting, high in safety and wide in application range, and the technical bottleneck of current tumor treatment is broken through.

The application discloses an irrigation oasis regulation and control potential power and targeted intervention strategy generation method and system, the method comprises the following steps: dividing a target irrigation oasis region into a plurality of management units, obtaining multi-source data of all the management units, and calculating the coupling coordination degree of each management unit; taking the management unit with a coupling coordination degree less than the regulation lower limit as a regulation unit, and taking the difference between the coupling coordination degree of the regulation unit and the regulation lower limit or the regulation upper limit as the regulation potential; constructing and training a Bayesian causal network, and according to the coupling coordination degree and the index of the regulation unit, using the probability output by the trained Bayesian causal network, calculating the mutual information or belief variance of each driving node of the regulation unit to the target node; taking the driving node with the highest mutual information or belief variance as the main control factor of the corresponding regulation unit, and searching for the targeted intervention strategy of the regulation unit in the factor-strategy knowledge base by using the main control factor.

The invention provides a nervous and mental health risk assessment and grading system based on intestinal microorganisms, and belongs to the technical field of nervous and mental health risk assessment. The invention provides a nervous and mental health risk assessment system. The nervous and mental health risk assessment system comprises a data acquisition and processing module, a microbial species abundance analysis module, a model calculation module and a nervous and mental health risk assessment result output module, the invention further provides a nervous and mental health risk grading system, and a risk grading module is added on the basis of the nervous and mental health risk evaluation system. According to the method, the multi-dimensional microbiome data is integrated and analyzed, the microbiological abundance data is converted into objective, quantifiable and graded output neurological and mental health results, early recognition of high-risk individuals and targeted intervention are facilitated, a reliable basis is provided for clinical decision making, and the method has good universality and expandability.

The invention belongs to the field of biological medicine, particularly discloses pharmaceutical application of a Dio3 inhibitor screened based on a thyroid hormone disorder algorithm in sepsis cardiomyopathy, and discloses that the core pathological mechanism of SIC is thyroid hormone signal axis disorder caused by Dio3 abnormal up-regulation, further mitochondrial autophagy key protein is inhibited, and the application of the Dio3 inhibitor in sepsis cardiomyopathy is developed for the first time. And myocardial mitochondrial homeostasis imbalance and functional cardiac dysfunction are caused. Through single intraperitoneal injection (25mg / kg) of a compound PBENZ-DBRMD (specific Dio3 inhibitor) within 12 hours after sepsis occurs, heart function indexes (EF% / FS%) can be remarkably recovered, and mitochondrial autophagy disorder can be reversed. Meanwhile, serum transT3 (rT3) is provided as an SIC early diagnosis marker (rT3 is strongly negatively correlated with EF%). The scheme provides a new targeted intervention strategy for SIC, and has the characteristics of simplicity and convenience in operation and definite curative effect.

The invention relates to application of S-adenosylmethionine or salt thereof in preparation of a medicine for preventing and treating ATO cardiotoxicity, and belongs to the field of biological medicine. In order to solve the problem that a general ferroptosis inhibitor cannot prevent and treat ATO cardiotoxicity from the source, the invention provides application of S-adenosylmethionine or salt thereof in preparation of drugs for preventing and treating ATO cardiotoxicity. The invention discloses a key molecular pathway of cardiac toxicity caused by ATO: ATO methylation metabolism exhausts endogenous methyl donors of myocardial cells, causes methylation imbalance of histone H3K9me3, and causes abnormal high expression of ferroptosis key protein HO-1 and mitochondrial iron overload. On the basis, the invention creatively provides a targeted intervention strategy of exogenous supplementation of S-adenosylmethionine, methylation imbalance and ferroptosis pathway activation are blocked from the upstream, root prevention and treatment of ATO cardiotoxicity are realized, and cardiac insufficiency is improved. The targeted intervention strategy is good in safety and has the advantages of clinical transformation and long-term application.

The invention discloses a diagnosis marker for diabetes complicated with atrial fibrillation and application of the diagnosis marker, and relates to the technical field of biological medicine. The diagnostic marker is hematopoietic cell kinase (HCK). The invention finds that HCK can effectively predict the occurrence risk of diabetes mellitus combined with atrial fibrillation and provide an effective treatment target for diabetes mellitus combined with atrial fibrillation. The invention verifies that the knock-down HCK can effectively inhibit AGEs-induced HL-1 cell CaMKII phosphorylation, myocardial fibrosis, mitochondrial membrane potential damage and ROS generation, and alleviates the inhibition effect on AMPK / mTOR signal channel activation, thereby reducing the atrial fibrillation susceptibility. The invention also proves that the risk (AUC is 0.853) of the diabetic with atrial fibrillation can be accurately identified by detecting the HCK level in the plasma. The invention provides a new medical approach for early risk assessment and targeted intervention of diabetes mellitus combined with atrial fibrillation.

The invention provides a coal mine support member risk intelligent detection method based on multi-mode inversion reasoning. Comprising the following steps of state data collection and data set construction of a multi-modal supporting component, defect detection and deformation recognition model design of the supporting component, failure path chain construction based on model inversion and risk assessment and early warning output based on failure path chain driving. According to the method, surface defects, three-dimensional deformation and attitude information can be synchronously obtained and fused, the real state of the component can still be stably recognized in severe environments such as low illumination and dust, and the missing detection and misjudgment rate is remarkably reduced; a failure path chain can be generated based on causal inference, the propagation and influence sequence between defects is disclosed, and a direct basis is provided for fault root positioning and preventive maintenance; and in combination with the defect category, the deformation quantity and the link risk aggregation result, a risk level judgment close to an actual operation safety condition is given, and operation and maintenance personnel are guided to formulate targeted intervention measures.