13 results about "Treatment strategy" patented technology

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 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 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 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.

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 application provides an AI treatment decision system for liver cirrhosis acute variceal hemorrhage, relates to the technical field of treatment decision, extracts a transient characteristic indicator of blood flow pressure from a pressure fluctuation signal, predicts a transient pressure peak of the portal vein blood flow during acute variceal hemorrhage through the transient characteristic indicator and a blood flow dynamic model, predicts a quasi-steady pressure field of the portal vein blood flow during acute variceal hemorrhage according to the gradient distribution of the portal vein blood flow pressure and an initial treatment strategy of acute variceal hemorrhage, performs multi-scale coupling on the transient pressure peak and the quasi-steady pressure field to obtain a coupling characteristic of the portal vein blood flow, and then uses the coupling characteristic of the blood flow pressure to perform hierarchical coupling adjustment on the treatment strategy of liver cirrhosis acute variceal hemorrhage. Based on the above scheme, hierarchical coupling of the treatment strategy of liver cirrhosis acute variceal hemorrhage can be realized, so that the prediction accuracy of the portal vein blood flow pressure during acute variceal hemorrhage can be improved.

This invention relates to a disease evolution prediction system based on cross-modal contrastive learning and counterfactual graph reasoning, belonging to the field of medical information processing technology. It includes: a multimodal heterogeneous data alignment module for aligning multimodal heterogeneous clinical data using cross-modal contrastive learning; a dynamic evolutionary time-series graph construction module for abstracting the complex evolutionary process of chronic diseases into a dynamic graph structure that changes over time; and a counterfactual intervention effect evaluation module that uses a conditional diffusion model as a counterfactual sample generator to construct multiple parallel potential evolutionary paths to evaluate prognostic differences under different treatment strategies. This invention significantly improves the representation accuracy of heterogeneous medical data through cross-modal contrastive learning, effectively compensating for the limitations of missing information in single modalities. This invention not only enhances the robustness of the prediction system in dynamic intervention environments but also endows the model with deep clinical interpretability.

The application relates to a kind of traditional Chinese medicine moxa point adaptive control method, system, equipment and medium based on agent, the method comprises: obtaining patient multimodal synchronous perception data, and obtaining multimodal perception data stream by spatiotemporal joint calibration and asynchronous data flow alignment;Reconstruct the three-dimensional skeletal model of patient based on multimodal perception data stream, and solve the initial coordinates of the moxa point to be moxa by bone degree minute method;Combine syndrome observation information and pre-constructed traditional Chinese medicine syndrome differentiation knowledge graph to construct dynamic state space;The dynamic state space is input into the pre-trained fast adaptive reinforcement learning model, and the matched treatment strategy is obtained;Generate multi-point collaborative control sequence based on treatment strategy and initial coordinates of point. By using the method, dynamic syndrome differentiation moxa can be realized, and the accuracy, clinical adaptability and treatment effectiveness of intelligent moxa control can be improved.

The application discloses an antibody targeting B7H3 and application thereof. The application provides a brand-new antibody targeting B7H3 for the field, and the antibody can specifically bind to B7H3, has good affinity and specificity. The application lays a foundation for developing B7H3 related detection and / or auxiliary detection products for the field, and is expected to provide more diagnostic tools and treatment strategies for diagnosis and / or treatment of B7H3 related diseases, and has good application prospect.

The application relates to the medical technical field, in particular to application of sulfasalazine in preparation of a medicine for treating primary biliary cholangitis (PBC) which is poorly responsive to ursodeoxycholic acid (UDCA), aiming at the clinical problem that about 40% of PBC patients are poorly responsive to the first-line drug UDCA, have high disease progression risk and limited second-line treatment options, and providing a new treatment use of the mature drug sulfasalazine. Through prospective clinical research, it is confirmed that, on the basis of UDCA standard treatment, combined use of sulfasalazine (1.5g / day, a treatment course of 48 weeks) can significantly improve liver biochemical indexes of UDCA non-responders, including alkaline phosphatase and gamma-glutamyltransferase, and 62.5% of the patients reach composite biochemical response. The application provides a new, effective, safe and highly accessible second-line treatment strategy for PBC patients who are poorly responsive to UDCA, and has a good clinical application prospect.

The application provides a computer-implemented method and device for tumor treatment strategy prediction, and belongs to the technical field of biological medicine. The method comprises the following steps: obtaining the proportion of target antigen-positive immune cells in total immune cells in a target sample; based on the difference between the proportion and a predetermined threshold, dividing the antigen expression level of the target sample to obtain a grouping result; wherein the grouping result is any one of N preset level groupings, and N is an integer not less than 1; based on the grouping result, matching a corresponding treatment strategy, wherein the treatment strategy comprises: administering an effective dose of an antibody corresponding to the target antigen and / or an immune checkpoint inhibitor antibody. By constructing a multi-level hierarchical mechanism based on the expression proportion of immune-related antigens and establishing a mapping relationship between the hierarchical result and the treatment strategy, fine immunotyping of tumor patients and individualized treatment strategy prediction are realized, so that the accuracy, safety and medical resource utilization rate of immunotherapy are improved.

The application discloses a kind of long-term treatment strategy making methods for cervical cancer prevention and treatment of HPV, belong to medical information processing technical field.The method includes: obtaining the digital HPV health record containing multiple HPV typing detection results, cervical cytology history record and individual physiological characteristic parameters;Three-dimensional treatment situation cube is constructed by virus infection state subspace, cervical tissue state subspace and treatment intervention state subspace;In the cube, state backtracking and forward-looking deduction algorithm based on time axis are used, virus clearance probability field and lesion outcome probability field are calculated;High-risk persistent infection space-time region and low-risk self-healing tendency space-time region are demarcated;Current patient state is projected to the cube, if fall into high-risk region, then trigger long-term treatment strategy generation process including multiple treatment stages, output intervention opportunity, intensity and state transition condition of each stage.