330 results about "Clinical trial" patented technology

Provided is a method, including obtaining data associated with clinical trials, storing the obtained data into a repository by preprocessing the data to standardize diverse input formats into unified data model and organizing the stored data into a schema designed to integrate data of diverse input formats, indexing the stored data and analyses performed on the stored data, selecting one or more visualizations responsive to the query by selecting one or more visualizations as being responsive to the query based on metadata associated with each of the one or more visualizations, determining whether the stored data is associated with a plurality of metadata requirements of each of the one or more visualizations, dynamically generating executable code configured to generate the one or more visualizations responsive to the query, executing the generated executable code, and providing a response to the query.

The invention relates to the technical field of medical information, in particular to a medical data conjoint analysis system based on medical knowledge graph driving. The system comprises a medical knowledge graph construction module, a medical data quality evaluation module, a medical feature engineering module and a medical knowledge driven analysis module, and heterogeneous knowledge graph modeling can be performed by integrating medical clinical guidelines, biomedical literatures, a drug database and historical medical data so as to generate a medical heterogeneous knowledge graph; obtaining new medical clinical test information and carrying out delayed contradictory learning update to generate a medical dynamic update knowledge graph; the method comprises the following steps: obtaining multi-modal medical data, carrying out quality verification evaluation and medical feature engineering analysis, carrying out knowledge path joint driving analysis at the same time, generating a decision support reasoning path corresponding to medical clinical knowledge, and outputting a corresponding medical knowledge path confidence coefficient. According to the method, fusion reasoning among cross-source data can be realized by constructing the multi-modal medical knowledge graph.

The invention relates to the technical field of clinical experiment data processing, and discloses a clinical experiment data analysis method based on reinforcement learning, and the method comprises the steps: obtaining time sequence physiological parameters and treatment scheme execution state parameters; performing hierarchical feature extraction on the time sequence physiological parameters, constructing a dynamic response feature model, and generating an initial treatment response evaluation model in combination with the execution state parameters; loading risk constraints and curative effect indexes to generate a comprehensive evaluation model, and simulating to obtain strategy regulation and control data; constructing and training a reinforcement learning decision model, and generating a treatment path correction model and initial treatment parameters; obtaining dynamic strategy adjustment information, and constructing a multi-stage optimization model for iterative optimization to obtain optimal treatment path parameters; reasoning a curative effect standard reaching probability based on a real-time model, and adjusting a strategy to realize dynamic curative effect matching. According to the method, the clinical data dynamic analysis and treatment scheme optimization capability is improved, and the method is suitable for precise medical scenes.

The invention relates to the technical field of data analysis, in particular to a diabetes clinical test data intelligent clustering analysis system and method based on federal learning. Comprising a data acquisition and preprocessing unit; a federal privacy protection unit; the dynamic clustering modeling unit is used for constructing a clustering model of self-adaptive diabetes data features, and realizing joint clustering analysis of multi-source heterogeneous data by adopting a hierarchical federal architecture and a dynamic parameter aggregation algorithm and combining a diabetes course time decay factor and a clinical feature weight adjustment strategy; a double-track verification optimization unit; and an intelligent decision support unit. According to the method, the incidence matrix of the diabetes disease course time decay factor and the clinical characteristics is introduced, the dynamic weight vector is constructed and applied to clustering distance calculation, so that the model can adapt to dynamic changes of the clinical characteristics in different disease course stages, the adaptability to multi-center heterogeneous data is improved, and the stability of a clustering result is enhanced.

The invention relates to a block chain-based clinical trial subject management system and method, and relates to the technical field of clinical trials, and the system comprises a management system constructed based on a block chain network and a plurality of edge computing nodes deployed in a medical institution. The edge computing node processes and encrypts the case information of the subject and then transmits the case information to the block chain network for storage, also can generate a feature query condition to screen a target subject, obtains index data of the target subject to determine test information, follow-up questionnaires and nursing information, and predicts follow-up time to generate a follow-up plan; the block chain network can start the smart contract template to screen the target subject based on the feature query condition. According to the method, the technical effects that the data security of the subjects is guaranteed by utilizing the block chain technology, and the clinical test subjects are efficiently screened, precisely supervised and scientifically managed in a follow-up visit manner are achieved.

The invention provides a clinical test data security sharing method and device based on a block chain. The method is applied to the technical field of data processing, and comprises the following steps: extracting feature dimensions corresponding to various types of data, and calculating corresponding data sensitivity coefficients; determining a data sensitivity level of the corresponding data category; extracting corresponding associated metadata; selecting a corresponding encryption algorithm to encrypt the data, and generating corresponding encrypted data and a data abstract; uploading the associated metadata, the encrypted data and the data abstract to a block chain node, constructing a clinical test data sharing account book, and recording a timestamp and a node signature of data operation; extracting identity authentication information and historical access records of visitors, and calculating access credibility; judging whether the visitor is allowed to acquire the decryption key or not; after the visitor obtains the encrypted data, the integrity in the data transmission process is verified based on the non-tampering property of the block chain. Therefore, the security of clinical test data sharing based on the block chain is improved.

The disclosure relates to methods and kits for detecting tau, e.g., tau that is phosphorylated at amino acid position T181 (pTau181), tau that is phosphorylated at amino acid position T217 (pTau217), and / or total tau. The disclosure further provides methods for distinguishing between individuals whose cognitive condition will remain stable and whose cognitive condition will decline during their lifetime. The disclosure also provides methods for determining the eligibility of individuals for participation in clinical trials for Alzheimer's disease treatments. Also provided are methods for distinguishing between individuals with Alzheimer's disease and non-Alzheimer's dementia, and for monitoring response to treatment for Alzheimer's disease.

The invention discloses a clinical test resource scheduling collaborative management system based on risk assessment, and relates to the technical field of clinical test management, the clinical test resource scheduling collaborative management system comprises a clinical test collaborative management platform, and the clinical test collaborative management platform is in communication connection with the following modules: a data integration module, a resource scheduling module and a resource scheduling module. The data collection module is used for collecting clinical test related data from different systems, preprocessing the collected data and integrating the data into a multi-source data set in a unified format. According to the method, the physical world is mapped to the virtual space in real time through the digital twinning technology, and the risk probability is dynamically updated in combination with the association rule of the knowledge graph, so that the system can accurately evaluate the possibility of occurrence of the current risk, a timely and accurate decision basis is provided for risk management of a clinical test, and the risk management efficiency is improved. The problems of hysteresis and subjectivity caused by the fact that a traditional risk assessment method depends on historical data or expert experience are effectively avoided, and therefore the constantly changing risk situation in a clinical test can be better coped with.

The invention belongs to the technical field of clinical test management and artificial intelligence application, and discloses a clinical test subject intelligent recruitment and safety monitoring system and method based on artificial intelligence. Aiming at the problems of low clinical test subject recruitment matching degree, dynamic data quality control lagging and bad event early warning response slowing in the prior art, four invention points of a subject intelligent matching algorithm, a dynamic data quality control model, a bad event real-time early warning mechanism and a global collaborative management framework are provided. The method comprises two innovative algorithm formulas of subject matching degree calculation and data anomaly risk assessment. By constructing a recruitment-quality control-early warning global collaborative closed loop, the testee recruitment matching degree is remarkably improved, the dynamic data quality control timeliness is greatly enhanced, the adverse event early warning response speed is obviously improved, the method is suitable for various medicine and medical instrument clinical test scenes, and the efficiency and safety of clinical tests are comprehensively improved.

Methods and systems including computer programs encoded on computer storage media, for a method for detecting signals related to subjects participating in a clinical trial. In some implementations, a computer collects clinical data from multiple sources. The computer standardizes and redacts personally identifiable information and determines predictive features that correspond to characteristics of the data that correlate with efficacy and safety signals. The computer obtains training data and trains machine learning models to predict one or both of a predicted efficacy signal and a predicted safety signal for a subject. The computer receives clinical data for a particular clinical trial subject enrolled in an ongoing clinical trial and predicts one or more signals and receives a review of the signals through a user interface. The computer updates the predictive components of the system based on the review.

The invention relates to the technical field of medical information, in particular to a clinical test patient screening and dynamic follow-up visit management method based on artificial intelligence, and the method comprises the following steps: collecting and standardizing admission, examination, medication and image data, mapping test items to form associated health data, comparing the group entering standard, screening qualified patients, and performing dynamic follow-up visit management. And extracting distribution mark difference crowds of medical units and patients, analyzing a physiological data fluctuation trend, and adjusting a follow-up visit sequence to generate a dynamic management plan. According to the method, by collecting structured health information and mapping test items, accurate screening and synchronous rhythm control are achieved, distribution of patients and medical units is analyzed, differential groups are recognized, resource allocation is optimized, a time sequence is constructed through physiological data, the difference value is calculated, and the health fluctuation trend is captured. The follow-up visit node is combined to adjust time arrangement, the execution efficiency is improved, and the patient management response speed and the data processing integrity are enhanced through multi-link cooperation.

A system (100) for automated data review and discrepancy management in Medidata Rave using advanced visualization, comprising: a) a data integration module configured to extract clinical trial data and discrepancy logs from Medidata Rave in real time; b) a discrepancy detection module capable of automatically identifying data inconsistencies, missing entries, or log deviations based on predefined rules and algorithms; c) an advanced visualization module configured to display the identified discrepancies through interactive dashboards with heat maps, trend charts, and status indicators; d) a workflow management module configured to assign, track, and escalate discrepancies to specific users based on priority and role;e) a reporting and analytics module configured to generate comprehensive reports summarizing discrepancy trends, resolution status, and key performance indicators; and f) a user access and security module that provides role-based access control and ensures data confidentiality in accordance with regulatory standards.

The application relates to the technical field of computers and discloses an integrated information system for clinical trial archives and a data processing method thereof, the method comprising the following steps: constructing a standardized data model covering the whole process; dynamically structuring and inputting multi-source data and checking the integrity; performing multi-dimensional semantic correlation analysis based on a Bayesian network and a correlation coefficient; performing block chain version tracing and difference comparison; performing four-dimensional access control of roles-sensitivity-operations-context; and performing task-driven collaborative sharing and audit logging. The system comprises six modules, namely, unified modeling, data input, semantic analysis, version tracing, access control and collaborative audit. The application solves the problems of data islands, semantic fragmentation, poor dynamic adaptability and weak security protection in the prior art, realizes intelligent management, semantic interconnection, safe controllability and efficient collaboration of the whole life cycle of clinical trial archives, and significantly improves data quality, audit compliance and multi-role collaboration efficiency.

A site distribution model identifies a set of sites to satisfy operational requirements of a clinical trial. An objective function is defined as: a first element indicating whether a site is included in the clinical trial; and a second element indicating whether a country is included in the clinical trial. There is a set of constraints including that an estimated total enrollment reaches a defined target enrollment. Computer code is generated to implement a site distribution model, using an optimization modeling language, based on the objective function and the primary set of constraints. The site distribution model is solved, if possible, to produce values of the site decision variable and the country decision variable. Otherwise, it is indicated to a user that a solution is not possible. If solving the site distribution model is possible, a list of clinical trial sites is produced from the site decision variable.

The invention relates to the field of quality management optimization, and discloses a vaccine clinical test quality management system optimization method and system, and the method comprises the steps: obtaining vaccine clinical test data of a target test group, building an interaction information network according to the extracted case sharing test information, carrying out the node graph convolution propagation of the interaction information network, and obtaining a target test group; a structural information embedding vector is obtained, a structural outlier center of vaccine clinical test data is identified, abnormal type hierarchical analysis is performed on the structural outlier center to obtain a quality deviation classification result, and a local structural abnormal cluster is identified according to an acquired abnormal propagation path. And generating a local quality control strategy according to the quality deviation classification result and the local structural anomaly cluster, and optimizing the vaccine clinical test quality management system. According to the method, the structural outlier center in the vaccine clinical test data can be effectively captured and the test data interaction diagram structure can be constructed in the vaccine clinical test data lacking a natural interaction network.

According to the intelligent real-time blood detection system based on the intravascular indwelling sensors, through an intravascular indwelling multi-sensor integrated system (electrochemical / optical coaxial layered design), continuous monitoring of one-time puncture for more than or equal to 7 days is achieved, in a clinical test, puncture within 7 days can be reduced from 28 times to 3 times, an improved Kalman filtering algorithm eliminates signal crosstalk, and the detection accuracy is improved. The D-S evidence theory is combined to dynamically fuse multi-modal data, so that the blood glucose detection MARD is reduced to 4.1%, the blood potassium error is less than 0.08 mM, and the motion artifact residual error is 1t; and 0.5%. A real-time data transmission and intelligent alarm system significantly improves clinical response efficiency, self-adaptively calibrates individual differences, and realizes high-precision long-acting monitoring.

A method of pre-screening a human subject for a clinical trial for treatment of tauopathy or an amyloidogenic disease. The method comprises obtaining a plasma sample from the subject and determining a concentration of p217+tau present in the plasma sample. The method further comprises indicating the subject for further screening for the clinical trial when the concentration of p217+tau present in the plasma sample is greater than or equal to a minimum threshold and less than or equal to a maximum threshold. The minimum threshold corresponds to an amount of p217+tau in plasma over which subjects present with mild cognitive impairment (MCI) and an increased accumulation of tau tangles in the brain as compared to a cognitively normal patient. The maximum threshold corresponds to an amount of p217+tau present in plasma over which subjects present with pathology of widespread accumulation of tau tangles in multiple regions of the brain.

The present disclosure relates to a microbiome composition for improving muscle strength using a heat-treated fermented culture complex of KM2 Lactiplantibacillus plantarum, wherein the composition according to the present disclosure increased synthesis of myoproteins and showed an effect of inhibiting degradation of myoproteins and animal tests showed an effect of improving muscle strength and increasing leg muscle mass through the increase in grip strength, travel distance, and speed, as well as results in which hamstring muscle strength is improved and muscle mass increases even in a clinical trial. In addition, it was found that the beneficial bacteria increased through an increase in the diversity of intestinal microflora that changed with muscle reduction and improvement in the microflora composition, while the harmful bacteria decreased.

A system for aiding in a medical clinical trial involving one or more pediatric patients includes a patient passport, individual achievement stickers that are awarded to pediatric patients and that are placed within the patient passport, and an interactive companion toy having distinctive patterns thereon. A camera of a mobile device scans the individual achievement stickers in the patient passport and / or the distinctive patterns on the interactive companion toy, and an interactive incentivization application logic section of the mobile device unlocks and display reward content to the pediatric patient. The interactive companion toy, the mobile application, and the physical passport can be customized to match particular protocols of the clinical trial. The pediatric patient is thus incentivized to participate and continue the clinical trial. Virtual medical play associated with the clinical trial can be practiced on the interactive companion toy in an augmented reality environment. Parents are assisted through automatic text message reminders, and electronic patient-reported outcomes are collected, transmitted, processed, and summarized for visualization and insights via a cloud-based clinical trial portal.

The invention relates to the technical field of drug early warning, in particular to a cell drug warning system for clinical research, which comprises an index anomaly marking module, an anomaly isolation cache module, a dynamic hysteresis monitoring module, a progressive risk evolution module and a warning state judgment module. According to the method, the inflammatory factor level index monitoring data of the subject are extracted in real time, anomaly distinguishing is carried out in combination with the preset monitoring interval, rapid identification of potential risk signals is achieved, dynamic tracking of the risk signals is achieved in combination with the intervention intensity grade and multi-time-point offset change sequence analysis in the hysteresis period, and the risk detection accuracy is improved. The real-time quantification of the risk evolution process is realized by calculating the offset characteristic quantity and the trend change, and the timely judgment capability of the high-risk state is improved through the dual comparative analysis of the maximum offset and the recovery time in combination with the linkage mapping of the risk level and the early warning threshold. And the identification, tracing, evaluation and early warning response levels of potential adverse reactions in clinical tests are effectively improved.

Disclosed herein a method for clinical supplies management. The method includes registering a user associated with a clinical trial according to user types, receiving a request for providing clinical supplies related to the clinical trial, receiving providing completion information for the clinical supplies, and updating clinical supplies information corresponding to the providing completion information.

The invention relates to technical development and application of new special medical food on the basis of a new food raw material framework, and belongs to the technical field of special medical purpose formula food (FSMP). According to the series of foods, new food raw materials (euglena, haematococcus pluvialis and ampelopsis grossedentata leaves) are taken as cores, medicinal and edible components (lotus leaves, haws and mulberry leaves) and marine active substances (fucoidan polysaccharides and chitin) are combined, functional factors are extracted through a prehydrolysis SBE technology and a biological enzymolysis technology, and the bioavailability is improved by adopting a nano-carrier technology. The product comprises a total nutrient base material (20-30% of protein and 15-25% of dietary fiber), functional components (10-15% of a new food raw material extract and 8-12% of a traditional Chinese medicine extract) and a metabolism regulator (conjugated linoleic acid and L-carnitine). Clinical tests show that after an obese patient takes 400 kcal of the replacement meal every day, the weight of the obese patient is reduced by 10.2 kg on average (4.8 kg of a control group) 12 weeks later, and the body fat rate is reduced by 16.3%. The product supports line iteration (such as powder, tablets and liquid food) through modular formula design, and fills the application blank of new food raw materials in special medical food.

As described below, the present invention features compositions, panels of biomarkers, and methods for selecting a subject with chronic lymphocytic leukemia (CLL) for treatment using an agent and / or for inclusion in a clinical trial using the agent to treat CLL.

The invention relates to the technical field of clinical data detection, and relates to a clinical test data anomaly detection method and system based on machine learning, and the method comprises the steps: constructing a clinical test heterogeneous graph; inputting the original multi-modal feature of each node into a preset mixed feature encoder to obtain an initial vector of each node; training a space-time atlas auto-encoder and a Bayesian network according to a group of normal clinical test data; calculating a reconstruction error vector and spatio-temporal context embedding of an initial vector of each node at the current moment through a trained spatio-temporal atlas auto-encoder; and judging whether the node is abnormal or not. According to the method, tiny deviation hidden in a complex background can be accurately identified, the accuracy rate of anomaly detection is improved, false alarm and missing alarm caused by normal fluctuation of data are effectively reduced, and the reliability and efficiency of clinical test data quality monitoring are integrally enhanced.

Methods and systems for retrieving data from at least one database based on a query input related to a clinical trial. A system processes a received query input related to a clinical trial using a pre-trained language model neural network. The neural network generates a structured representation of the query input. The system maps a first data field of the structured representation to a first column name and maps a second data field of the structured representation to a second column name. The system generates a database query based on (i) a database schema, (ii) the first column name, (iii) the second column name, (iv) data values associated with the first data field, and (v) data values associated with the second data field. The database query specifies an operation for joining data associated with the first column name with data associated with the second column name.

Provided herein are methods for manufacturing and using engineered tissues. The methods and compositions described herein may be useful for biocomputing, regenerative medicine, non-clinical trials, or cellular agriculture.

The invention belongs to the technical field of medical diagnosis, and discloses a marker for evaluating the curative effect of treating hepatocellular carcinoma by combining TACE with Czodili monoclonal antibody and bevacizumab, and a construction method and application of an FAAP prognostic scoring model. The invention develops and verifies an FAAP prognostic scoring system, and a novel composite model integrates four indexes of fibrin degradation product / cholinesterase ratio * 1000 (FCR), aspartate aminotransferase (AST), alpha fetoprotein (AFP) and portal vein tumor thrombus (PVTT), and is used for predicting the survival condition of uHCC patients subjected to TACE-Czodimab-bevacizumab triple therapy. The tool has an instant clinical value, can optimize patient selection, guides adaptive treatment upgrading, and provides a standardized curative effect evaluation basis for a clinical test for exploring a TACE-immunotherapy-anti-angiogenesis combined scheme.

The invention discloses a traditional Chinese medicine composition for treating depression and insomnia and application thereof, and belongs to the field of traditional Chinese medicines. The traditional Chinese medicine composition comprises the following raw material components in parts by weight: 10-15 parts of fermented soybean, 10-30 parts of lily, 10-15 parts of red wolfberry, 10-15 parts of radix puerariae, 10-30 parts of cistanche, 10-15 parts of longan aril, 10-30 parts of jujube, 9-30 parts of oyster, 10-15 parts of pawpaw, 3-10 parts of fingered citron, 5-15 parts of dogwood, 6-10 parts of fried gardenia, 15-30 parts of light wheat and 3-10 parts of honey-fried licorice root. Animal experiments and clinical tests prove that the traditional Chinese medicine composition can improve insomnia and depression symptoms at the same time. The traditional Chinese medicine composition has the overall regulation advantage of traditional Chinese medicine and the controllability of a modern preparation, and a safe and efficient treatment scheme is provided for depression and insomnia.

The invention relates to the technical field of clinical test data acquisition and intelligent quality control, in particular to a clinical test data real-time acquisition and quality control management platform, which is characterized in that an operation starting time recording unit acquires a subject disinfection operation starting timestamp, an operation sequence delay calculation unit calculates actual operation delay based on standard consumed time, and a quality control unit calculates the actual operation delay based on the standard consumed time. The transmission delay processing unit separates transmission and operation delay through double timestamps, the actual collection time determining unit subtracts pure transmission delay time data and operation delay time data from the timestamps uploaded by the device through a reverse time restoration algorithm to obtain actual blood collection completion time, and the time window dynamic judging unit judges whether the time window dynamic judging unit is in real blood collection completion time or not through a dynamic offset boundary. The real time is compared with a preset time window to judge qualification, the physiological index correction unit corrects blood glucose and insulin values in real time through a layered framework and a correction rule base, and the dynamic association logic verification unit adjusts association rules and verifies index logic in combination with a three-dimensional decision matrix, so that support is provided for clinical tests.

Methods and systems for retrieving data from at least one database based on a query input related to a clinical trial. A system processes a received query input related to a clinical trial using a pre-trained language model neural network. The neural network generates a structured representation of the query input. The system maps a first data field of the structured representation to a first column name and maps a second data field of the structured representation to a second column name. The system generates a database query based on (i) a database schema, (ii) the first column name, (iii) the second column name, (iv) data values associated with the first data field, and (v) data values associated with the second data field. The database query specifies an operation for joining data associated with the first column name with data associated with the second column name.