121 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 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 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 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 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 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 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 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.

An apparatus for generating personalized risk assessments for neurodegenerative diseases includes a computing device that receives user data containing genetic and medical information. It processes the data to create genotype identification and gene detection modules, identifying user genotypes and relevant genetic markers. The user's mitochondrial haplogroup is examined to refine the assessment. A risk calculation module employs machine learning to weigh genetic variants against population-based data, calculating a polygenic risk score (PRS). The PRS forms a personalized risk profile, displayed through a visual interface. The disclosed systems offer a comprehensive approach to accurate risk assessment, enabling targeted interventions and informed decision-making in neurodegenerative disease management.

The invention discloses a multi-organ system biological age assessment method, and relates to the technical field of health assessment, and the method comprises the steps: S1, obtaining data; step S2, preprocessing the data; s3, screening biological age construction indexes of the multi-organ system; and S4, estimating the biological age of the multi-organ system. According to the method, the defects of an existing biological age model in the aspects of crowd applicability and prediction accuracy are overcome, accurate evaluation of the biological age of a multi-organ system is achieved, early recognition and accurate prevention and control of senescence-related diseases can be achieved, systematicness and heterogeneity of the senescence process are revealed, and the method is suitable for popularization and application. And more evidences are provided for pertinently intervening the senescence process.

The invention belongs to the technical field of biological medicines, and particularly relates to application of an HS2ST1 inhibitor in preparation of a medicine for treating KRAS inhibitor drug-resistant tumors. At present, more than 50% of KRAS inhibitor drug-resistant patients have unclear mechanisms and lack of effective intervention targets, and HS2ST1 is identified as a key regulation target of KRAS inhibitor drug resistance for the first time. Researches find that the expression of HS2ST1 in KRAS inhibitor drug-resistant cells is significantly up-regulated; functional experiments prove that targeted intervention of the HS2ST1 can effectively enhance the curative effect of the KRAS inhibitor and reverse the drug resistance phenotype of the KRAS inhibitor, and a new strategy and a potential treatment direction are provided for overcoming KRAS targeted treatment drug resistance.

The application relates to the technical field of artificial intelligence, and discloses an emotional conversation generation method and device, electronic equipment and a storage medium, the method comprising the following steps: constructing an emotional conversation dataset and constructing a plurality of intelligent agents based on a pre-trained large language model, which respectively play the roles of a seeker and a consultant; obtaining current conversation text received by a first intelligent agent corresponding to the seeker, mapping a target cognitive distortion classification system of the current conversation text based on the emotional conversation dataset; determining the cognitive bias of the current user based on the target cognitive distortion classification system; determining a target intervention strategy of the current conversation text based on the cognitive bias by using a second intelligent agent corresponding to the consultant, a preset hybrid reward mechanism and a cognitive strategy reinforcement learning algorithm; and optimizing reply text in the target intervention strategy to generate a target reply text, so that the cognitive diagnosis and cognitive intervention strategy accuracy for the seeker are improved, and accurate identification and professional intervention of cognitive distortion of the seeker are realized.

The invention belongs to the technical field of medical artificial intelligence, and relates to an acute kidney injury early intelligent prediction method fusing multi-modal data, which comprises the following steps: generating a two-dimensional clinical feature flow containing slow variable trend features and instantaneous impact event vectors; generating a parallel risk path trajectory set containing the independent risk evolution trajectory of each path; extracting the current state value of each independent risk evolution trajectory, and generating a pathway state snapshot representing the current risk level of each pathogenic pathway; performing dynamic correction on each independent risk evolution trajectory in the parallel risk path trajectory set, and generating a collaborative enhancement risk trajectory set fusing cross-path influence; identifying and locking the trajectory with the most significant deterioration trend, and determining the trajectory as the current dominant risk pathway; and matching and generating a structured early warning instruction containing a risk type qualitative conclusion and a targeted intervention suggestion. The problem that risk fluctuation caused by treatment intervention or disease change cannot be reflected in real time is solved.

The application discloses application of UFSP2 as a target point in preparation of a prostate cancer treatment product. The application relates to the field of biological medicine, and research finds that UFM1 specific protease 2 (UFSP2) is highly expressed in prostate cancer tissues, and the protein level is higher than that of paracancerous tissues, and is positively correlated with the expression of proliferation related molecules c-Myc and CyclinD1. Function experiments further show that inhibition of UFSP2 expression can significantly inhibit the proliferation, clone formation and migration of prostate cancer cells, and inhibit the growth and metastasis of prostate cancer in vivo; on the contrary, overexpression of UFSP2 can promote the proliferation of prostate cancer cells, indicating that UFSP2 can be used as a prostate cancer treatment target and can be used for screening of anti-prostate cancer drugs. The application provides application of an UFSP2 expression inhibitor and / or a function inhibitor in preparation of a prostate cancer treatment product, and provides a new drug development direction and a targeted intervention strategy for prostate cancer treatment.

This invention discloses a method and application for regulating fatty liver syndrome based on osteocalcin-adiponectin receptor, relating to the field of livestock and poultry metabolic disease prevention and control technology. The method includes the following steps: clarifying the clinical symptoms and pathological changes of fatty liver syndrome in laying hens; constructing a complementary validation system for fatty liver syndrome models, including an in vivo FLS model in laying hens and an in vitro LMH model of chicken liver cancer cells; using osteocalcin OCN and the adiponectin receptor agonist AdipoRon to target and intervene in the in vivo FLS model and the in vitro LMH model of chicken liver cancer cells, and conducting multi-dimensional detection and evaluation of the regulatory effect; by specifically silencing the expression of AdipoR1 or AdipoR2, comparing changes in lipid deposition and signaling pathways in cells treated with osteocalcin, and identifying the functional hierarchy of AdipoR1 and AdipoR2 in the osteocalcin regulatory pathway; this invention achieves precise prevention and treatment of fatty liver syndrome in laying hens through complementary validation models, targeted intervention with osteocalcin and AdipoRon, and identification of adiponectin receptor function.

The invention relates to an ICU bedside pressure sore risk image identification and early warning method. The method comprises the following steps: continuously acquiring images at a preset frame rate before and after the same skin area of a patient is pressed and decompressed to obtain a sequence; extracting color, brightness or texture features of the region from the sequence, comparing the color, brightness or texture features with baseline features before decompression, if a recovery threshold is met, judging that the region is reversible, otherwise, judging that the region is limited in recovery when continuous deviation exceeds a first time length; calculating regional displacement and deformation within a second duration under the condition that the limited state is recovered, and judging that the compression is hidden and continuous when the displacement is smaller than a threshold value; and comparing the characteristics of the region before and after body position adjustment or nursing intervention, and if the characteristics are not improved or deteriorated, outputting a pressure sore high-risk early warning. The method does not need an additional contact type sensor, is suitable for continuous and non-invasive monitoring beside an ICU bedside, can provide early warning in the early stage of formation of pressure sores and even before macroscopic injuries occur, and helps nurses to take targeted intervention measures in time, so that the occurrence rate of the pressure sores is reduced, and the nursing quality and the working efficiency of the ICU are improved.

The invention relates to the technical field of wisdom education, and discloses a wisdom teaching interaction method and system based on multi-modal perception, and the method comprises the steps: collecting multi-modal teaching data, and carrying out the preprocessing and quality evaluation; extracting a multi-modal feature vector, and carrying out standardization and dimension projection; carrying out dynamic weighted fusion; constructing a multi-dimensional evaluation model and identifying a multi-dimensional state of the student; learning difficulty point diagnosis is carried out, a strategy optimization model is constructed to generate targeted intervention content, and the optimal triggering opportunity is determined; intervention is executed through multi-mode cooperation, student reactions are monitored in real time, and the intervention effect is quantitatively evaluated; the strategy optimization model is optimized, and personalized evaluation is carried out based on learning progress track data of students; according to the invention, accurate perception and intelligent personalized support of the programming learning process are realized, and the teaching quality and learning experience are effectively improved.

The application relates to a psychological counseling interaction method and device based on an autonomous psychological planning architecture. In the method, initial user data of a target user is acquired; a dynamic target graph of the target user is constructed through a three-layer nested target structure, and a matched personalized decision tree is preloaded; after real-time interaction data is received, real-time path reevaluation is performed based on the real-time interaction data to obtain a treatment value function of each intervention path; a Bayesian network and a Monte Carlo tree search algorithm are used to construct an intervention response prediction model, the priority and execution sequence of the intervention paths in the personalized decision tree are adjusted in combination with the treatment value function of each intervention path, a target intervention path matched with the real-time interaction data is selected from the adjusted intervention paths; the real-time interaction data is mapped into a multidimensional psychological state space as a conversation trajectory, conversation trajectory planning is performed based on the target intervention path, real-time interaction with the target user is realized, and the accuracy of intervention decision and the fluency of the conversation are improved.