469 results about "Clinical research" patented technology

The invention discloses a medical whole-course intelligent management system based on a large model, and belongs to the technical field of large models. Comprising a multi-modal data acquisition module, a privacy calculation preprocessing module, a dynamic knowledge enhancement module, a time sequence data analysis module, an intelligent decision engine module, a multidisciplinary collaboration module, a patient interaction platform module, a dynamic intervention feedback module and a system security center module. The cross-mechanism data security sharing is realized, and the compliance of sensitive information processing is also ensured; a two-channel medical knowledge base is constructed, authoritative guidelines can be synchronized, newest clinical research data can be analyzed in real time, the knowledge base is kept in the newest state all the time, and the frontier scientific basis is provided for clinical decisions; dynamic modeling and trend prediction are carried out on long-term monitoring data of a patient by adopting a hybrid neural network model, and potential health risks and development trends can be identified more accurately.

The invention discloses a clinical research data analysis method based on machine learning, and the method comprises the steps: constructing a multi-modal variable structured causal map, and building a direction adjustable mechanism of a causal path; constructing a bidirectional nested structure attention mechanism, and capturing a cross-modal dependency and dynamic evolution relationship between variables; recording each layer of information propagation path and variable participation degree, and realizing reverse reconstruction of a model decision path in a reasoning stage; target-oriented attribution path regularization is introduced to carry out regularization constraint on an attribution path set of the key target variables; and constructing a nested attribution graph visualization system, and realizing interactive presentation of interpretation sub-graphs corresponding to prediction results so as to improve cognitive trust of model output. According to the method, from structure expression, path tracing and causal constraint to visual presentation, the core problems that a deep model is poor in interpretability, clinicians are not trusted, and existing interpretation tools are insufficient in applicability are solved in a full-link mode.

The invention discloses a construction method of a traditional Chinese medicine alert question-answering system based on a large language model. The method comprises the following steps: establishing a traditional Chinese medicine knowledge base; constructing a retrieval enhancement generation model PV-RAG oriented to drug alert, and training and optimizing the PV-RAG model by taking the traditional Chinese medicine knowledge base as a training set; the PV-RAG model comprises a retrieval module, a text extraction module, a query rewriting module and a generation module; and constructing an intelligent question and answer application end, and generating a traditional Chinese medicine alert answer according to a natural language question input by a user. According to the traditional Chinese medicine alert question-answering system based on the large language model and the retrieval enhancement generation technology, deep semantic understanding of traditional Chinese medicine literatures is achieved through the text embedding model, multi-source data such as traditional Chinese medicine specifications, traditional Chinese medicine classics and clinical research literatures are effectively integrated, and the traditional Chinese medicine alert question-answering system is established. And rich knowledge support is provided for traditional Chinese medicine alert questions and answers.

The invention relates to the technical field of medical data management and disease auxiliary decision making, and discloses an auxiliary diagnosis and treatment data management system based on a disease full-path atlas model, and the system comprises a multi-source heterogeneous database which integrates and standardizes medical data; the node coding module carries out diagnosis and treatment node coding; the graph module constructs a disease knowledge graph and identifies path nodes; the diagnosis and treatment auxiliary module generates decision suggestions through path matching; the research auxiliary module is used for screening homogeneous cases to support clinical research; a cross-modal attention mechanism, reinforcement learning optimization coding rules and GNN dynamic path generation are integrated, causal reasoning is combined to eliminate hybrid variables, and multi-center privacy cooperation is realized based on federated learning. According to the method, a multi-modal database is constructed through standardization and path processing, homogeneous cases are screened by utilizing a full-path map, key features are extracted, intelligent decision support is provided for clinical diagnosis and treatment, meanwhile, efficient data analysis service is provided for scientific research, and medical data management and application are optimized.

The invention discloses a lung adenocarcinoma prognosis risk prediction model and a construction method and application thereof, and belongs to the technical field of biomedical detection. The lung adenocarcinoma (LUAD) prognosis model is successfully constructed by systematically analyzing the immune infiltration related gene (CAFRG) of tumor-associated fibroblasts (CAF), and the application value of the lung adenocarcinoma (LUAD) prognosis model in prediction of patient prognosis is verified. The CAFRG risk score is negatively related to the immune microenvironment score and is remarkably related to immune checkpoint gene expression, which suggests that a high-risk patient may have the characteristic of immune escape. Furthermore, based on TIDE tool analysis, the patients in the low-risk group have more active T cell immune response. The risk score is also closely related to the sensitivity of antitumor drugs, especially Doramapimod. Therefore, a new theoretical basis is provided for personalized treatment of lung adenocarcinoma, and a new direction is provided for future clinical research.

The invention relates to a medical image generation method and device based on a migration model, computer equipment and a storage medium, and aims to ensure data quality and consistency and lay a foundation for model training by acquiring and preprocessing a medical image report data set and generating an initial medical image and corresponding initial pathological text data. And constructing a text-to-image generation model based on a diffusion model, and preliminarily realizing text-to-image conversion. The generation model is finely adjusted by using initial data, and the generation precision and adaptability are improved. And analyzing the multiple pieces of target pathological text data, generating a target medical image by using the optimization model, and verifying the validity of the model in practical application. According to the technical scheme, transfer learning and a diffusion model are combined, the problems of medical data finiteness and distribution inconsistency are solved, the medical image generation effect and application value are improved, and important technical support is provided for clinical research and medical diagnosis.

The invention discloses a three-dimensional clinical research method of deciduous tooth anchorage on maxilla hypoplasia under the guidance of an HPC line. According to the invention, the deciduous tooth anchorage technology guided by the HPC line breaks through the limitation of the traditional tooth support type and bone support type correction, and creates a third anchorage selection mode for osteomalocclusion. By accurately positioning the central axis of the deciduous tooth crown as a supporting point, the technology not only retains the effectiveness of the traditional method on the transverse expansion of the maxilla, but also remarkably reduces the side effects of mesial inclination, vertical lifting and the like of the permanent tooth, and realizes the dual purposes of bony reconstruction and dentition stabilization. The innovativeness is that the physiological characteristics of deciduous teeth are combined with the biomechanical principle, the technical scheme is provided for the first time in China, the blank of correction of complex malocclusion in mixed dentition is filled, and a safer and more efficient treatment path is provided for clinic.

In some implementations, a system dynamically adjusts an electronic form of an application based on user data and form data specified for the electronic form. Form data that specifies characteristics of the electronic form is initially received by a computing device. The form data specifies one or more rules configured to vary the content of the electronic form that is presented for different users. User data indicating characteristics of a user is then obtained by the computing device. An interactive element is then selected from among a set of multiple interactive elements based on the received user data and the rules in the received form data. A view of the electronic form is customized for the user by including, in the customized view, the interactive element. The view of the customized electronic form is then displayed by the computing device.

The present invention relates to a method for producing a canine atopic dermatitis animal model, a canine atopic dermatitis animal model produced thereby, and a use thereof. According to the present invention, a canine atopic dermatitis animal model is produced by skin stimulation on a dog through epicutaneous sensitization with ovalbumin at a concentration of 1 to 5 mg / ml once daily for 1 to 2 weeks and then with ovalbumin at a concentration of 1 to 5 mg / ml once daily for 2 to 8 weeks. The resulting animal model exhibits clinical symptoms of atopic dermatitis, changes in relevant factors such as increased expression levels of IgE and CCL17, and elevated expression levels of Th2-related cytokines IL-4, IL-31, and IL-13. Therefore, this invention enables the establishment of a standardized animal model for symptoms and Th2 immune responses appearing upon the onset of atopic dermatitis, and the model can be used in clinical studies for screening candidate agents for the prevention, alleviation, or treatment of atopic dermatitis.

The invention provides a method for enhancing Treg cell functions and application, and belongs to the technical field of cell engineering. According to the method, hUC-MSCs are irradiated by gamma rays to form feeder layer cells, and then the feeder layer cells and Treg cells are co-cultured to obtain the Treg cells with enhanced cell functions. Through the co-culture of the feeder layer cells and the Treg cells, the inhibition ability of the Treg cells on activation and proliferation of immune cells can be enhanced, and the feeder layer cells and the Treg cells can be used as universal cells in clinical researches of autoimmune diseases, graft versus host diseases and the like.

The invention provides application of TRMT61A and its inhibitor tetramethylthiuram disulfide in tumor immunotherapy, and relates to the technical field of biological medicine, clinical research proves that RNA m1A methyltransferase TRMT61A is highly expressed in tumor tissues and is related to poor prognosis of tumor patients, and can be used as one of tumor therapy targets. Meanwhile, high expression of the TRMT61A is related to poor prognosis of a tumor patient receiving anti-PD-1 immunotherapy, and after anti-PD-1 antibody immunotherapy is carried out on the patient with low TRMT61A expression level in the tumor of the patient, pathological complete relief is easier. Tetramethylthiuram disulfide inhibits TRMT61A, inhibits m1A modification regulation of TRMT61A on PD-L1 mRNA, increases PD-L1 protein expression, and is combined with a PD-1 antibody drug to significantly enhance the immunotherapy effect of the anti-PD-1 immune checkpoint drug in treating malignant tumors.

The invention relates to the technical field of electric digital data processing, and discloses an intelligent data processing method for clinical research. The method comprises the following steps: constructing a basic clinical knowledge graph fused with an international medical ontology; the method comprises the following steps: performing deep learning driven entity recognition and knowledge graph linking on original data from heterogeneous sources such as an electronic medical record and an inspection system; executing cross-source entity alignment and knowledge fusion based on the graph attention network; performing automatic data quality verification and restoration according to clinical logic rules embedded in the atlas; and finally, extracting and generating a standardized analysis ready data set from the enhanced atlas according to research requirements. According to the technical scheme, high-quality, automatic and semantic integration and flexible delivery of clinical research data are realized, and the data processing efficiency and research reliability are improved.

The invention relates to the technical field of information processing, in particular to a traditional Chinese medicine informatization processing system and method for acute lung injury. The system comprises a traditional Chinese medicine information slice storage module, a traditional Chinese medicine knowledge graph construction module, a dialectical auxiliary reasoning module and a prescription sorting recommendation module. An acute lung injury traditional Chinese medicine information database can be generated by collecting and integrating ancient traditional Chinese medicine poeia information corresponding to acute lung injury, domestic and overseas clinical research information and acute lung injury patient record data extracted from electronic medical record systems corresponding to various hospitals and performing slice coding storage; performing entity and relation extraction and knowledge graph construction according to the acute lung injury traditional Chinese medicine information database, and generating an acute lung injury traditional Chinese medicine knowledge graph; dialectical auxiliary reasoning and traditional Chinese medicine prescription sorting recommendation are carried out based on the acute lung injury traditional Chinese medicine knowledge map, and a traditional Chinese medicine prescription suggestion scheme sequence corresponding to the acute lung injury syndrome type is generated. The information processing efficiency of acute lung injury traditional Chinese medicine prescription recommendation can be improved.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for managing and adapting monitoring programs. In some implementations, a system communicates with a set of remote devices involved in a monitoring program that involves collection of data from the remote devices over a communication network. The system determines a set of attributes associated with an outcome or condition that has occurred for multiple of the remote devices. The system generates parameters to adapt the monitoring program, and the system selects a second group of remote devices to involve in the adapted monitoring program based on profiles or sets of attributes of users associated with the remote devices. The system configures the remote devices in the selected second group to perform monitoring for the adapted monitoring program, including acquiring data for the adapted monitoring program and providing the acquired data to a server over the communication network.

The invention relates to an intelligent inquiry and risk evaluation method for gynecological tumors. The method comprises the following steps: acquiring symptom information of a consultant and tumor medical history information of relatives in a plurality of generations of families of the consultant; constructing a tumor genetic family diagram by using the tumor medical history information, and then evaluating genetic risks of consultants to generate genetic consultation suggestions; constructing a symptom semantic network based on a medical ontology, and converting the symptom information into standard symptom data; calling a corresponding hierarchical inquiry protocol according to the standard symptom data to generate an intelligent diagnosis result; and integrating the genetic risk assessment result and the intelligent diagnosis result and outputting a diagnosis suggestion. Gynecological tumor inquiry consultation and risk evaluation can be automatically completed, and meanwhile a clinical research form is generated and inserted into a hospital electronic medical record system. The whole process does not need manual operation of doctors, the workload of information collection and input of the doctors is greatly reduced, and the doctors can concentrate on the core diagnosis and treatment process.

To provide an examinee candidate extraction system for promptly and efficiently extracting an examinee candidate of a clinical research by utilizing information collected on the basis of the will of a patient, an examinee candidate extraction device, an examinee candidate extraction method and a program.SOLUTION: An examinee candidate extraction system 1 includes an integrated repository 11 and an examinee candidate extraction device 17. The integrated repository 11 stores in an associated manner, medical information of a patient which is inputted or generated by a medical institution and previously permitted by the patient, the physical information of the patient inputted or generated by the patient and previously permitted by the patient, and information relating to the will of the patient to be an examinee candidate. The examinee candidate extraction device 17 extracts from the integrated repository 11 the patient having the predetermined medical information and the physical information from among the patients having the wills to be the examinee candidate in accordance with a selection condition or algorithm.SELECTED DRAWING: Figure 1

The invention discloses an intelligent adverse drug reaction acquisition system and method based on clinical practice, and the method comprises the steps: obtaining a medication record, a disease course text and a nursing record of a patient, and an inspection index; s2, performing identification and relation extraction on the data acquired in the S1, and constructing a time-sequenced knowledge graph of medicine-indications-test abnormality-clinical bad symptoms; training a Transform prediction model through a time sequence knowledge graph, complementing a knowledge graph relationship, and predicting a missing relationship and an entity; s3, monitoring the change of physiological indexes of the patient after medication in real time, performing dual-channel early warning, adding the detected adverse reaction into the prediction model in S3, and performing update training on the prediction model; a time sequence knowledge graph is constructed, the correlation between the medicine and the adverse reaction is comprehensively and systematically presented, powerful support is provided for clinical research and supervision, and the medicine safety monitoring level is improved.

Systems and methods provide efficient access to electronic data capture (EDC) and electronic medical record (EMR) data for monitoring clinical research. A multi-tenant clinical research platform is configured to support remote management of clinical research sites based on EDC and EMR data. The platform is configured to access EDC data from an EDC data store, access related EMR data from an EMR data store that is separate from the EDC data store, and use mappings between the EDC data and the EMR data to contextually integrate the EMR data into a clinical research review workflow provided by the platform. In some embodiments, the platform is configured to prevent persistence of the EDC data and / or EMR data within the platform. The platform provides remote, on-demand controlled access to the EDC data and the EMR data to facilitate offsite reviews of clinical research sites based on EDC and EMR data.

The present invention provides a data management method for clinical research projects, the method comprising: in response to a node event initiated by a workflow management center, triggering a call request, the workflow management center communicating with multiple clinical research tools; in response to the call request, calling a specific research tool among the multiple clinical research tools, and collecting at least one target parameter provided by the specific research tool; creating a customized format copy of the target parameter and storing it in an underlying database. In addition, the present invention also provides corresponding computer equipment and readable media, as well as a data management system for clinical research projects. Implementation of the various embodiments of the present invention helps to improve the efficiency of team collaboration and clinical research.

The invention provides an application of a spleen T lymphocyte exosome in construction of a depression animal model, a stress rat spleen T lymphocyte exosome is injected into a mouse body to construct the depression animal model, and the depression animal model can be used for depression drug screening, drug efficacy evaluation or diagnosis, and can be used for treating depression. And the method can also be used for researching and revealing pathogenesis of depression. The invention also proves that the IL4 / IL4R alpha signal channel and the BDNF signal channel play an important role in depression through experiments. The invention has important significance for clinical research of depression.

The metabolic marker can be used for early diagnosis of heart failure, has the advantages of high sensitivity, rapidness, convenience and accurate and reliable result, provides a basis for clinical decision, provides a certain basis for subsequent fundamental research and clinical research, and has potential application and research values. The metabolic marker comprises one or more of 1-(4-nitrophenyl) piperidine, sphingolipid d19: 3 / 23: 0, phosphatidyl ethanolamine 16: 1e / 22: 5, phosphatidyl ethanolamine 16: 1e / 22: 6, sphingolipid d14: 0 / 22: 1, 3-phosphoglyceric acid, phosphatidylcholine 15: 0 / 20: 4, phosphatidylcholine o-16: 1 / 18: 0, phosphatidylcholine 14: 0e / 20: 1, phosphatidylcholine 17: 0 / 18: 5, betaine, phosphatidylcholine 15: 0 / 18: 2 and phosphatidylcholine 18: 5e / 20: 4.

The invention discloses a traditional Chinese medicine compound oral preparation for treating male oligoasthenospermia, and belongs to the technical field of traditional Chinese medicine preparations. The rhizoma polygonati processed with wine, the prepared rehmannia root and the like are used for nourishing the liver and kidney to consolidate congenital, the codonopsis pilosula, the astragalus membranaceus and the like are used for invigorating spleen and replenishing qi to complement postnatal, the fried cowherb seed is used for activating blood circulation, and the salted semen plantaginis is used for promoting diuresis, so that the problems of insufficient spermatogenesis and low vitality caused by deficiency of the spleen and the kidney are fundamentally solved. Experiments and clinical researches show that the preparation can significantly improve the sperm quantity, activity and activity rate of oligoasthenospermia model mice and patients, the clinical total effective rate reaches 90%, the pregnancy rate reaches 53.3%, and the curative effect is superior to that of Wuzi Yanzong pills in a control group. The action mechanism covers regulation of blood lipid metabolism, improvement of hypothalamus-pituitary-gonad axis functions, repair of testicular seminiferous tubule structural damage and reduction of lipid deposition, and meanwhile, oxidative stress and inflammatory injury are relieved and spermatogenic cell functions are protected by regulating and controlling a PPAR signal channel and inhibiting molecular pathways such as Cga / Sting mediated cell apoptosis.

The invention discloses a clinical research report automatic writing system and method based on artificial intelligence, and relates to the technical field of data processing, and the system comprises a data collection module, a relation mapping module and a training fine tuning module; the technical key points are as follows: extracting report elements from equipment portrait data and clinical research data, pre-training a preset large language model based on a report element mapping relationship, constructing a corresponding fine tuning instruction based on the mapping relationship, and performing fine tuning of corresponding parameters to obtain an optimized large language model; in the process, the knowledge integrity of the large language model is protected, the focus area is strengthened, the adverse reaction type is forcibly constrained, the internal structure of the equipment and the over-limit threshold value of the equipment are considered, and semantic understanding of automatic writing of a clinical research report is strengthened; automatic mapping from the text to the structured dimension is achieved, the matching precision can be continuously improved through dynamic learning and multi-modal fusion, and the accuracy and efficiency of automatic writing are improved.

The present invention belongs to the field of drug research and development, and specifically discloses a method, storage chip and device for efficiently evaluating the efficacy of in vitro combined drug therapy. The present invention directly solves the problems of complexity and high cost of experiments and data processing in the existing drug development process by adopting an AI model and a simplified experimental mode. The AI ​​model optimizes concentration selection based on historical drug data, thereby reducing redundant concentrations and unnecessary number of experiments in the experiment, and improving the sensitivity and reliability of the evaluation. By simplifying the experimental design to single drug concentration point testing and a 3x3 combined drug matrix, the complexity and cost of the experiment are significantly reduced, while the speed of data processing and analysis is accelerated. The method disclosed in the present invention avoids excessive combined drug pre-testing by directly conducting single drug and 3x3 matrix combined drug testing, which can not only more effectively identify potential synergies between drugs, but also provide more accurate and practical data to support future clinical research.

The invention discloses a sample size calculation method and system for quantitative consistency evaluation. The method comprises the following steps: firstly, determining MDL and a clinical consistency boundary value, then collecting pre-test data, and determining a required sample size through iterative calculation. Then, verification samples are extracted from the overall data for consistency analysis, and the robustness of a calculation result of the verification sample size is simulated through Bootstrap; according to the method, MDL and least square regression are fused for the first time, a sample size formula for quantitative consistency evaluation is constructed, the reliability and effectiveness of clinical test data are ensured by providing a new sample size calculation method, more accurate sample size estimation is provided for clinical research, and therefore the quality of clinical decisions is improved.

The present invention provides radiolabeled 2, 3, 4, 5 -tetrahydro-1H-[1,4]diazepino[1,7-a]indol-9-yl]pyridin-2(1H)-one derivatives of general formula (I) or salts thereof and precursors of formulae (II) and (III) to said radioligands, to processes for the preparation thereof, and to intermediates of said processes. The radiolabeled compounds enable visualization and quantification of melanin concentrating hormone receptor 1 (MCHR1) receptors in various target tissues, including monitoring the MCHR1 in such target tissue. The compounds exhibit high binding affinity towards MCHR1 and can pass the blood-brain barrier, thereby facilitate the diagnosis of a range of disease states in human clinical research.

The invention discloses a targeted screening method and application of a xanthine oxidase inhibitor in radix puerariae, and belongs to the technical field of medicinal chemistry. A surface chemical exchange method is carried out on xanthine oxidase through a ligand fishing technology, ligands of active groups of xanthine oxidase are modified to the surfaces of magnetic metal nanoparticles, the magnetic metal nanoparticles and a to-be-separated solution are incubated together, and then specific components with the xanthine oxidase inhibiting effect are successfully screened out through a UPLC-Q-TOF-MS / MS technology. The combination of the active component and the XOD active site is verified through molecular docking simulation to confirm that the active component is an effective inhibitor. The invention provides a reliable basis for further clinical research and development of drugs for treating hyperuricemia, and has a wide application prospect.

The invention relates to a data analysis method and system for multiple PCR multi-target parallel amplification, and relates to the field of biological detection.User features and respiratory tract features of a target user are collected and analyzed to obtain feature confidence, the features are utilized to predict multiple PCR detection results, error calculation is carried out on the results and an actual detection spectrum, and the accuracy of the results is improved. According to the multi-PCR multi-target parallel amplification data analysis method and system, the abnormal modes are detected in a classified mode in combination with the feature confidence coefficient, the actual detection spectrum is marked, the technical problems that multi-PCR multi-target parallel amplification data analysis is complex, errors are prone to occurring, and automatic and accurate analysis is difficult are solved, automatic and precise analysis of the multi-PCR multi-target parallel amplification data is achieved, the accuracy and efficiency of data analysis are effectively improved, and the data analysis efficiency is improved. Detection abnormity can be found in time, and the reliability and accuracy of clinical research are improved.

The invention discloses an intelligent respiratory disease detection system based on lung function measurement indexes, and relates to the technical field of intelligent medical detection. The problems that diagnosis standards are not uniform and depend on experience, primary doctors are prone to missed diagnosis or misdiagnosis due to insufficient experience, and the efficiency of the detection process is low are solved. According to the method, a machine learning model is constructed based on lung function indexes, parameters are optimized through five-fold cross validation, automatic classification of asthma, COPD and ILD / DPLD is achieved, the overall diagnosis accuracy rate reaches 81.3%, the limitation that traditional diagnosis depends on doctor experience is broken through, and the basic medical diagnosis capacity is especially improved. Healthy people are rapidly eliminated through the FVC / FEV1 ratio, invalid calculation is reduced, meanwhile, multi-model weighted fusion is adopted for complex cases, diagnosis robustness is improved, it is ensured that diagnosis results conform to medical logic, the recognition degree of doctors is enhanced, a data basis is provided for clinical research and curative effect tracking, and respiratory disease diagnosis is promoted to develop towards the direction of automation and precision.

The embodiment of the invention relates to the technical field of computers, and discloses an intelligent entry and exit method and device based on clinical research, a medium and a product. The method is realized based on a large model, and comprises the following steps: determining research design elements according to a received research scheme; determining an inference rule according to the research design elements; according to the inference rule, generating a discrimination code of each research design element; and according to the discrimination code, determining a patient list conforming to the research scheme. The technical problems that in the prior art, the automation degree is low, manual intervention is still needed in the links of data mapping, code debugging and the like, real end-to-end intelligence cannot be achieved, and generalization adaptability to different research types, multi-source heterogeneous data and medical knowledge updating is lacked can be at least solved.