91 results about "Treatment strategy" patented technology

The invention relates to the technical field of medical instruments, in particular to an electromagnetic focusing extracorporeal shock wave pancreatic lithotripsy device and method.The electromagnetic focusing extracorporeal shock wave pancreatic lithotripsy device comprises a device body, a bed body is installed on one side of the device body through a supporting frame, and a lithotripsy notch is formed in the side, close to the device body, of the bed body; a large C-shaped arm and a small C-shaped arm installed on the inner side of the large C-shaped arm are installed at the position of the notch of the device body, an X camera imager is installed at the upper end of the large C-shaped arm, and a shock wave generator and an ultrasonic probe installed on one side of the shock wave generator are installed on the small C-shaped arm. An energy adjusting module used for controlling the shock wave generator and a safety detection module used for detecting the skin temperature are arranged in the device body, and a displayer and a human-computer interaction interface are arranged on one side of the device body. The technical scheme in the prior art has limitations on shock wave generation, positioning precision, energy regulation and control and treatment strategies.

The invention relates to the technical field of medical artificial intelligence, and discloses a non-small cell lung cancer immunotherapy risk assessment method and system and a storage medium, and the method comprises the steps: constructing an optimal strategy tree model capable of dividing a patient into a plurality of subgroups based on a historical patient data set, and determining an initial optimal treatment strategy for each subgroup; determining a subgroup to which a new patient belongs and an initial treatment strategy thereof according to the model; in the treatment process, the deviation degree between the individual response trajectory of the patient and the average response trajectory of the subgroup to which the individual response trajectory belongs is calculated; and when the deviation degree exceeds a preset threshold value of the subgroup, triggering an adaptive adjustment mechanism, and outputting an updated treatment suggestion. By establishing a dynamic monitoring and closed-loop feedback mechanism based on the subgroup benchmark, the technical problem that an existing scheme is difficult to carry out prospective identification and dynamic intervention on individualized risks is solved, so that the accuracy, safety and individualized level of non-small cell lung cancer immunotherapy are improved.

The invention relates to the technical field of medical cosmetology, discloses a laser hair removal method based on multi-parameter feedback, and aims to solve the problems of unstable curative effect and insufficient safety caused by single parameter of traditional laser hair removal. The method comprises the following steps: synchronously acquiring multi-dimensional physiological parameters such as skin type, hair follicle depth and epidermis temperature through multispectral imaging, high-frequency ultrasound and temperature sensing; constructing a personalized treatment parameter model based on a deep neural network, and generating initial energy density, pulse width and cooling parameters; laser output is regulated and controlled in real time by using a fuzzy logic controller in the treatment process, and it is ensured that thermal injury accurately acts on the hair papilla; performing adaptive optimization on the treatment strategy in combination with reinforcement learning, and continuously updating the model through a closed-loop learning mechanism; meanwhile, a treatment history database is established, curative effect prediction and parameter backtracking are supported, precision, individuation and high safety of laser depilation are achieved, depilation efficiency is remarkably improved, and the risk of skin adverse reaction is reduced.

The invention discloses a layering and preference learning-based personalized dynamic treatment strategy generation system for Parkinson's disease, which comprises a dynamic state and preference representation module, a preference-based reward function learning module, a layering treatment strategy generation module and a treatment path simulation and interactive output module, the system learns preferences from doctor-patient interaction and generates layered, dynamic and explainable personalized long-term treatment strategies, so that making of personalized long-term treatment decisions is achieved, and the problems that in an existing Parkinson's disease reinforcement learning scheme, an award function is fixed, and long-term planning ability is lacked are solved.

The invention discloses a case misdiagnosis identification method and device and a storage medium, relates to the technical field of medical technology and machine learning, and discloses the steps that multi-source heterogeneous medical detection data of a to-be-identified case and a disease diagnosis result and a treatment strategy of a doctor on the to-be-identified case are acquired; based on the multi-source heterogeneous medical detection data, the disease diagnosis result and the treatment strategy, diagnosis and treatment path matching is conducted on a pre-constructed typical disease knowledge base, the corresponding diagnosis and treatment path deviation degree is obtained, and the typical disease knowledge base comprises multiple disease entries and reference diagnosis and treatment paths corresponding to the disease entries; and inputting the multi-source heterogeneous medical detection data, the disease diagnosis result, the treatment strategy and the diagnosis and treatment path deviation degree into a misdiagnosis recognition model, and performing misdiagnosis recognition on the to-be-recognized case based on the misdiagnosis recognition model to obtain a corresponding misdiagnosis recognition result, thereby solving the technical problem of low misdiagnosis recognition accuracy of the actual diagnosis and treatment path of the case in the prior art, and improving the accuracy of the misdiagnosis recognition. And the misdiagnosis identification accuracy is improved.

The invention discloses an emergency treatment resource scheduling method based on a multi-stage dynamic game, and relates to the technical field of medical emergency management, and the method comprises the steps: according to a three-party dynamic game model corresponding to a pre-hospital first-aid team, a hospital department and a transfer unit, and the medical multi-modal data of each patient in a current treatment scene, carrying out the multi-stage dynamic game; determining a pre-hospital first-aid team treatment strategy, an in-hospital department treatment strategy and a transfer unit treatment strategy; according to the three-party treatment strategy, robust scheduling based on meta-learning is carried out on current existing emergency treatment resources, and a robust scheduling strategy is determined; iCU bed scheduling, operating room scheduling and ambulance scheduling are executed according to the robust scheduling strategy. According to the method, emergency treatment resource allocation balance under the dynamic game of multiple participants is realized, meanwhile, sudden disturbance can be quickly adapted through the meta-learning framework, the purpose of effectively allocating emergency treatment resources in response to emergencies is also realized, and the adaptability of a robust scheduling strategy to the emergencies is improved; and the resource scheduling strategy has interpretability and stability.

The invention discloses a construction method and application of a preeclampsia animal model based on an RASA3 target, and belongs to the technical field of biomedicine.The preeclampsia animal model is constructed by injecting Ad-RASA3 into a pregnant mouse and monitoring pathological indexes, related to preeclampsia, of the pregnant mouse. According to the method, the animal model with preeclampsia-like clinical symptoms can be stably induced, the abnormal change of the uterine spiral artery remodeling process can be systematically monitored, the method is high in operation controllability and model stability, and an effective tool can be provided for deeply researching the pathogenesis of preeclampsia and developing a novel diagnosis and treatment strategy.

The invention discloses a rehabilitation evaluation system and method based on data feedback, and the method comprises the steps: obtaining a continuous online rehabilitation video as rehabilitation training video frame data, and constructing a rehabilitation training motion data set; extracting joint angle features and skeleton point distance features from the action data set by adopting a label classification technology, and obtaining distance measurement of each human body joint skeleton point coordinate; matching the time sequence with the action features by adopting a dynamic adjustment algorithm for the action feature combination, and constructing a classification evaluation model of rehabilitation training actions; a data feedback mechanism is introduced into the classification evaluation model of the rehabilitation training actions, the relation between rehabilitation requirements and rehabilitation evaluation is mapped, the whole system achieves detailed analysis and dynamic adaptation of the rehabilitation training actions, accurate rehabilitation suggestions can be provided according to individual differences, the effectiveness of a treatment strategy is ensured through real-time monitoring and adjustment, and the rehabilitation training effect is improved. And the rehabilitation effect and efficiency are greatly improved.

The application discloses a sensitized ferroptosis lipid nano regulator and a preparation method and application thereof, and belongs to the technical field of new adjuvants and new dosage forms of drug preparation combined treatment. The lipid nano regulator is co-assembled by a GPX4 inhibitor and a FASN inhibitor through intermolecular forces, and is modified with an oxidation-reduction sensitive PEG modifier, a molar ratio of the GPX4 inhibitor and the FASN inhibitor is 10:1-1:10, a mass ratio of the sum of the GPX4 inhibitor and the FASN inhibitor to the PEG modifier is 10:90-90:10, and the intermolecular forces include pi-pi stacking force, hydrophobic force and hydrogen bond. The co-assembled nano preparation provides a new strategy and more choices for the development of drug delivery, and meets the urgent needs of high-efficiency and diverse ferroptosis treatment strategies in preparations in the clinic.

The invention provides a chest pain type determination system, a program product, an electronic device and a storage medium, the program product comprises a computer program or instruction, and when the computer program or instruction is executed by a processor, the following method steps are executed: determining a chest pain risk level according to multivariate medical information of a patient; if the level is the first level, analyzing multivariate medical information according to first guide information for any preset type of high-risk chest pain disease to obtain a preliminary result; according to the preliminary results corresponding to the various types of high-risk chest pain diseases, determining a target high-risk chest pain type; if the first level is the first level, analyzing the multivariate medical information by referring to second guide information for any preset type of low-risk chest pain disease to obtain a preliminary result; and determining a target low-risk chest pain type according to the preliminary results corresponding to the various types of low-risk chest pain diseases. And determining a corresponding diagnosis and treatment strategy for each target chest pain type. Therefore, the target chest pain type can be quickly and accurately determined, and a diagnosis and treatment strategy can be given, so that a doctor can be assisted to quickly and accurately diagnose and treat.

The invention relates to the technical field of software security governance, in particular to an open source component governance method and system based on multi-dimensional measurement and feedback optimization, and the method comprises the steps: collecting multi-source heterogeneous data of an open source component, carrying out the feature extraction, and constructing a basic measurement matrix containing security, compliance, efficiency and collaborative dimensions; respectively calculating a security dimension index and a compliance dimension index which represent a risk defense boundary, and an efficiency dimension index and a cooperation dimension index which represent business delivery kinetic energy, and generating a multi-dimensional efficiency state vector; mapping to a governance efficiency evaluation space, and generating an efficiency deviation characteristic value by calculating the coupling collaboration degree and restriction loss among the dimension indexes; and reversely deducing the adjustment gradient of the control strategy parameter to generate a dynamic correction instruction for the strategy execution component, issuing the dynamic correction instruction to the strategy execution component to update the control rule in real time, and executing a treatment operation on the open source component. According to the method, the treatment effect of the software can be effectively quantified, and the treatment strategy is guided to carry out targeted adjustment and continuous optimization.

The invention belongs to the technical field of biological medicine, and particularly relates to a new Spp1 + Carmil1 + and Spp1 + Cav1 + macrophage subgroup, a screening method and application in diagnosis and treatment of rheumatoid arthritis (RA). Aiming at the function limitation of a traditional M1 / M2 classification model, the invention proves the following new subgroup pathological interaction mechanism: osteoclast (ACP5 +) specifically releases TNFSF11 (RANKL), and is co-localized with Spp1 + Carmil1 + and Spp1 + Cav1 + subgroup space; the Spp1 + Carmil1 + subgroup secretes IL-18, and space interaction exists between the Spp1 + Carmil1 + subgroup and Treg (Foxp3 +) and Th17 (Il17a +) cells. The invention provides a novel cell marker and a targeted treatment strategy for accurate diagnosis and treatment of RA.

The application relates to the technical field of medical health data processing, and discloses a blood potassium management and monitoring method and system based on multivariate input, which comprises the following steps: firstly, obtaining demographic data, medical history data, test data, medication data and medication adjustment event data of a patient, and performing pretreatment; then, based on the pretreated data, determining whether to enter a potassium supplement path or a potassium reduction path, and performing risk stratification on the blood potassium state of the patient, and outputting a risk stratification result and a treatment strategy; then, according to the determined path and the risk stratification result, performing corresponding medication decision to generate a medication adjustment scheme, and based on the medication adjustment scheme, generating a review suggestion for the patient; finally, showing the analysis result containing the risk stratification result, the treatment strategy, the medication adjustment scheme and the review suggestion to a user end, and recording an operation log. The application meets the clinical demand for fine, individualized and whole-process management of blood potassium.

The invention provides application of kestose in preparation of a medicine for treating heart failure related diseases, and belongs to the technical field of biological medicine. The prominent application value of the natural compound kestose in prevention and treatment of heart failure related diseases is disclosed for the first time. The traditional Chinese medicine composition has the direct effects of remarkably improving cardiac insufficiency and relieving myocardial injury; in the aspect of product application, a brand-new choice of a heart failure treatment medicine derived from a natural product is provided for clinic, the medicine has a good myocardial protection effect, a solid foundation is laid for developing a targeted treatment strategy aiming at a specific pathological link of chronic cross-induction, and the application has a wide application prospect. Important theoretical significance and wide clinical application prospects are realized.

The application discloses a 7T magnetic resonance head and neck tumor radiotherapy response evaluation system, belongs to the field of medical imaging and tumor radiotherapy, and comprises an ultrahigh-field multi-modal image acquisition module, a multi-phase accurate registration and radiomics feature extraction module, an early response biomarker identification module and an adaptive treatment decision support module. The high resolution, high signal-to-noise ratio and multi-nuclide imaging capability of the 7T ultrahigh-field magnetic resonance are utilized to acquire multi-modal images before and during treatment, more than 200 features are extracted through accurate registration and radiomics analysis, the treatment response is predicted based on the Delta feature and the deep learning model 2 to 3 weeks after the start of radiotherapy, the prediction accuracy reaches 87.5%, the prediction is 3 to 4 weeks earlier than the conventional evaluation, decision support is provided for timely adjustment of the treatment strategy, a closed-loop feedback mechanism is established, the clinical verification results are used to optimize the parameters of each module reversely, and continuous improvement is realized.

The invention discloses a deep learning-based lung cancer adjuvant chemotherapy benefited patient identification method and system, and relates to the technical field of lung cancer precise treatment and artificial intelligence crossing, and the method comprises the steps: analyzing and preprocessing preoperative and postoperative registration logs of a patient to obtain basic information of the patient, a pathological image of the patient and a treatment strategy of the patient; the method comprises the following steps: performing segmentation processing on a patient pathological image by adopting nnformer to obtain a focus region segmented image, performing feature extraction and enhancement on the focus region segmented image to obtain image omics features, and constructing an improved 3D survival analysis model; and analyzing the basic information of the patient, the radiomics characteristics and the treatment strategy of the patient by adopting an improved 3D survival analysis model to obtain an identification result of the lung cancer adjuvant chemotherapy benefited patient. According to the method, the quantitative survival risk score and the adjuvant chemotherapy sensitivity conclusion are output, and an interpretable reference basis is provided for clinical decision making.

The invention belongs to the technical field of medicine, and discloses an application method of tumor-killing effect B cells in colorectal cancer liver metastasis, Meta-CBL is used for transforming the B cells into tumor-killing effect cells for the first time, and the anti-tumor immune effect is remarkably enhanced. In a tumor microenvironment, the meta-CBL can directly kill tumor cells and activate other effector immune cells, so that synergistic anti-tumor is realized. By combining liquid biopsy and single cell sequencing, tumor load and microenvironment immune state can be tracked in real time. The evaluation precision is higher than that of traditional iconography, invalid treatment patients can be recognized in the early stage, and the treatment strategy is adjusted in time. Precise treatment and dynamic prognosis evaluation of colorectal cancer liver metastasis are realized by innovatively utilizing meta-CBL, and the defects of limited treatment effect and lagging evaluation means in the prior art are overcome. The comprehensive system structure and the precise treatment strategy of the system bring brand new treatment choices and remarkable survival benefits for patients with colorectal cancer liver metastasis, and the system has extremely high industrialization and clinical popularization value.

The application provides a magnetic response composite hydrogel for integrated repair of bone defects and a preparation method thereof, and belongs to the technical field of medical materials. The composite hydrogel can efficiently inhibit tumor cell activity under the time sequence regulation of an external alternating magnetic field, and then provide a suitable microenvironment and key components for bone tissue regeneration, so that signal conversion and function connection from tumor killing to bone repair are realized. The material has good injectability and self-healing ability, can minimally invasively fill irregular defects, and has significant advantages in simplifying the clinical treatment procedure, shortening the treatment course, reducing the risk of tumor recurrence and improving the repair quality, and provides a new and integrated treatment strategy for tumor-related bone defects.

The invention relates to a mouse spinal cord injury bionic compression modeling system and a method thereof.The system comprises a mechanical arm, a magneto-rheological-pneumatic loading compression module, a multi-mode optical fiber sensing probe and a control module, the magneto-rheological-pneumatic loading compression module comprises a shell, an air bag, a magneto-rheological elastomer and an air supply part, the shell is installed at the driving end of the mechanical arm, and the air bag is installed at the driving end of the mechanical arm; the air bag is installed in an inner cavity of the shell, the electromagnetic part is fixedly installed at the bottom of the inner cavity of the shell, the air supply part supplies air to the air bag, and the magnetorheological elastomer is fixedly installed at the end, away from the bottom of the shell, of the air bag. The multi-mode optical fiber sensing probe is installed at the end, away from the air bag, of the magnetorheological elastomer and used for detecting the microenvironment of the deep spinal cord tissue of the mouse. The injured spinal cord chronic compression animal model constructed by the scheme is high in fidelity, the clinical correlation of the model can be remarkably improved, and the experimental variability is reduced, so that a more reliable and more comprehensive research platform is provided for mechanism research and treatment strategy evaluation of degenerative spinal cord diseases.

The invention discloses a recurrent abortion risk analysis knowledge graph construction method. A data acquisition unit, an evidence-based medicine evidence evaluation unit, a knowledge reasoning unit, a knowledge fusion unit, a classification attribute layer construction unit, a risk factor layer construction unit and an evaluation index layer construction unit are included. The method has the advantages that the description model of the factors causing the recurrent spontaneous abortion and the onset risk of the recurrent spontaneous abortion is constructed based on the knowledge graph, auxiliary guidance opinions are provided for clinical risk screening and diagnosis and treatment thoughts of the recurrent spontaneous abortion, risk factors of the recurrent spontaneous abortion can be comprehensively checked, and decision data basis is provided for doctors and patients.

The invention provides a lipidosome preparation capable of performing brain-targeted drug delivery in a depression model, a preparation method of the lipidosome preparation and application of the lipidosome preparation in improving the anti-depression effect of fluoxetine, and belongs to the technical field of pharmaceutical preparations. The composition disclosed by the invention consists of DOPG, DSPE-PEG2000-PGP, DSPE-PEG2000, cholesterol, fluoxetine and celecoxib, and can be used for improving the anti-depression effect of fluoxetine. The double-drug-loading liposome with high entrapment efficiency and uniform particle size is prepared through a film hydration-film extrusion method, has good stability and biocompatibility, has an obvious targeting drug delivery effect in a chronic social contusion stress model, is suitable for a combined treatment strategy of depression, and has a good clinical application prospect.

The application relates to the technical field of medicines, in particular to application of N-acetylneuraminic acid in preparation of medicines for preventing and / or treating ulcerative colitis. The application finds that N-acetylneuraminic acid can effectively prevent or treat ulcerative colitis and promote tissue repair by regulating macrophage metabolism, inhibiting glycolysis pathways and M1 type polarization, and simultaneously repairing intestinal mucosal barrier, thereby providing a safe, simple and clear mechanism of action new treatment strategy for clinic.

The present application relates to the technical field of medicine. Disclosed for the first time is a chemogenetic gene therapy technology for treating autism spectrum disorder. Specifically, provided in the present technology is a combined drug treatment strategy, which comprises a neuron-targeted intracranial injection and a small-molecule agonist (the latter serving as a second drug administered after surgery). According to this strategy, the injection is precisely delivered to the posterior substantia innominata brain region by means of stereotactic intracranial injection, and then the second drug is administered after surgery, so as to intervene in the social behavioral abnormalities associated with autism spectrum disorder. The therapy can prolong the attack latency, shorten the duration of aggressive behaviors, and reduce the frequency of aggressive episodes in model animals, while not interfering with basic vital activities and emotional states such as normal social interaction, fear and anxiety. This strategy pioneers a novel approach for treating autism spectrum disorder, which is expected to improve the quality of life of patients and alleviate the burdens on the families thereof and society, and thus has broad prospects for clinical application.

The present application relates to the technical field of nano-preparation, in particular to an extracellular vesicle-liposome hybrid nanoparticle and a preparation method and application thereof. The extracellular vesicle-liposome hybrid nanoparticle provided by the present application significantly improves the ability of drugs to cross the blood-brain barrier and the target enrichment efficiency of ischemic lesions in the brain through active targeting modification; the specific response release of drugs is realized by using the high active oxygen microenvironment of the lesion, non-specific distribution of drugs is reduced, and the systemic toxic side effects are reduced; ultimately, a multi-target point synergistic treatment system capable of synchronously regulating neural cell apoptosis, glial cell inflammatory activation, brain microvascular endothelial cell ferroptosis and the structural integrity of the blood-brain barrier is constructed, the problem that the effect of traditional single target point intervention is limited is broken through from the root, and a more efficient, safe and precise new treatment strategy is provided for cerebral ischemia-reperfusion injury.

The invention belongs to the technical field of antioxidant drugs, and particularly relates to application of a glutathione dry powder inhaler in preparation of drugs for treating radiation acute lung injury, the glutathione dry powder inhaler comprises the following active ingredients by mass percentage: 50%-60% of reduced glutathione, 10%-20% of a carrier and 20%-30% of a dispersant, totaling 100%, the carrier is mannitol, and the dispersing agent is L-leucine. According to the invention, the glutathione dry powder inhalant accurately delivers high-concentration GSH to an alveolar injury area through a lung targeting delivery system, synchronously activates endogenous antioxidant enzymes, inhibits lipid peroxidation and an inflammation source, and blocks release of proinflammatory factors, so that radiation-induced oxidation-inflammation cascade reaction is directly inhibited, alveolar structure damage is relieved, and the anti-inflammatory effect is achieved. And an efficient new treatment strategy is provided for RILI.

This invention belongs to the field of biomedical inorganic nanomaterials technology, and discloses a copper-doped bioglass and its application in the treatment of chronic liver injury and hepatic osteodystrophy. The bioglass is prepared by a sol-gel method, with copper as a dopant (Cu). 2+ It is doped in a form with a doping amount of 0.1-5 wt%, has a mesoporous structure, a particle size of approximately 163 nm, and can slowly release Cu in environments with pH 7.4 or 5.5. 2+ The treatment duration is 48-96 hours. This invention is the first to use the aforementioned material for the simultaneous treatment of chronic liver injury (such as metabolic-associated steatohepatitis) and its secondary hepatic osteopathy, achieving liver-targeted therapy via intravenous injection. Its mechanism of action includes: regulating glucose and lipid metabolism in the liver, enhancing mitochondrial function, and inhibiting inflammation and fibrosis; simultaneously upregulating the liver-derived factor LCAT, promoting osteogenic differentiation via the liver-bone axis, thereby synergistically improving liver injury and bone loss. This invention overcomes the limitations of separate liver and bone treatment, providing a safe and effective integrated treatment strategy.

This invention discloses a method and system for generating auxiliary diagnostic results and reference prescriptions. First, a medical record database and a treatment strategy database are constructed and stored in a vector database and a text retrieval database, respectively. For a target medical record, vectorization and textualization are performed. Then, candidate medical records and treatment strategies are retrieved from the medical record vector database, medical record text database, treatment strategy vector database, and treatment strategy text database via four channels. Subsequently, the RRF algorithm is used to fuse and sort the vector and text channels, and the candidate results are further refined based on a pre-trained semantic ranking model to obtain a small number of reference medical records and treatment strategies highly relevant to the current condition. Finally, prompt words are constructed by combining the target medical record, reference medical records, and treatment strategies to generate candidate results such as TCM diagnosis, TCM syndrome type, Western medicine diagnosis, and TCM prescriptions, serving as auxiliary references for doctors' clinical decision-making. This significantly improves the accuracy, interpretability, and efficiency of intelligent assisted diagnosis and treatment.

The invention provides an application of an expression inhibitor of Gadd45a in preparation of a medicine for preventing or reducing the ototoxicity of cis-platinum. In-vivo and in-vitro experiments prove that by locally applying the Gadd45a inhibitor, cochlea hair cells and auditory functions can be effectively protected by activating autophagy, inhibiting an NF-kappaB1 inflammation pathway and regulating JNK-mediated apoptosis, so that hearing loss caused by cis-platinum is relieved. The invention provides a brand-new effective medicine product and a treatment strategy for clinically preventing and treating the ototoxicity of cis-platinum, and has important clinical application value for preventing or relieving the ototoxicity of a patient receiving cis-platinum chemotherapy.

The application provides a coronary artery maximum pressure gradient calculation method and device based on an X-ray contrast image, and applies to the technical field of data processing. The application performs automatic screening on functional contrast frames based on preprocessed contrast images, obtains a difference image by subtracting a first frame of background frames from each preprocessed image, calculates a gray scale variance of the difference image, and selects a frame with the maximum variance as a target contrast image of each projection angle. The target contrast image is subjected to three-dimensional blood vessel model reconstruction and coordinate conversion to construct a coronary artery three-dimensional network model. Hemodynamic parameters are calculated based on the coronary artery three-dimensional network model. A PPG index is constructed based on the hemodynamic parameters, and lesions are classified. A PPG index formula is derived by integrating a 20mm maximum pressure gradient and a diffuse lesion ratio, a single PPG index value is made to correspond to a treatment strategy through an inverse proportional weighting algorithm, and classification information of coronary artery lesions is generated.

The invention discloses a risk sensitive causal strategy optimization method oriented to continuous time decision. The method comprises the following steps: 1) constructing a continuous time process of each patient based on a discrete time sequence observed for medical diagnosis and treatment processes of different patients in a medical scene; 2) constructing a Fokker-Planck equation residual error based on a continuous time dynamic model of an SDE modeling treatment effect process, and alternately training a treatment effect regression network and a discriminator through a minimum-maximum residual error optimization framework; 3) simulating and generating treatment effect anti-fact trajectories under different continuous time treatment strategies by using the treatment effect regression network, and estimating corresponding anti-fact distribution; and under the budget constraint and the quantile type security constraint, searching to obtain an optimal continuous time treatment strategy meeting the risk constraint. According to the method, the average effect and the tail risk can be simultaneously described in a continuous time environment, and safe and steady optimization of a medical intervention strategy is realized.