163 results about "Research data" patented technology

The invention discloses a project performance evaluation and risk early warning method for multi-source heterogeneous scientific research data, and relates to the technical field of scientific research project management, and the method comprises the steps: collecting the multi-source heterogeneous scientific research data, cleaning, converting, filling missing values, and storing in a unified format; extracting performance and risk features, and fusing to obtain a fused feature set; combining an analytic hierarchy process, an entropy weight method and the like to construct a dynamic weight performance evaluation model; constructing a multi-modal risk early warning model by adopting multiple algorithms and optimizing a threshold value; collecting data in real time to update a feature set, and dynamically adjusting the model; and visually outputting a result, generating an improvement suggestion, and forming closed-loop feedback. According to the method, the multi-source data processing efficiency and evaluation accuracy are improved, the risk early warning timeliness and adaptability are enhanced, a management closed loop is formed, and the problems of difficult data integration, evaluation lagging, insufficient early warning and the like of a traditional method are solved.

The invention belongs to the technical field of computer software, and particularly relates to a data lake and warehouse management deployment method applied to a domestic operating system, which comprises the following steps: establishing a heterogeneous server cluster, deploying various domestic operating systems in the server cluster, and completing configuration of a network architecture and a basic software environment; the method comprises the following steps: carrying out localization adaptation on a software component source code, synchronously modifying package management logic of a self-research data lake and warehouse management platform, and further implementing intelligent compiling to generate a program package for different instruction set architecture and domestic operating system combination; automatically generating and executing a deployment script by utilizing a self-developed data lake and warehouse management platform to complete installation and configuration of each software component on a target node; and after deployment of each software component is completed, systematic deep tuning and component-level accurate tuning are automatically performed on the deployed system and each software component, and automatic verification is executed. The invention provides an efficient, stable, safe and controllable data lake and warehouse integrated solution for users, wherein the data lake and warehouse integrated solution can be used immediately after being opened.

The invention belongs to the technical field of ecological restoration evaluation, and provides a geological ecological restoration evaluation method and system for geological disaster prevention and control, electronic equipment and a storage medium. The method comprises the steps of research data acquisition, geological disaster type setting, initial evaluation, data preprocessing, model construction and training, risk determination before restoration, information acquisition after restoration, geological disaster risk prediction and geological ecological restoration evaluation. According to the method, the model is trained by using the remote sensing image, the sound wave data and the initial evaluation data, the evaluation result is predicted through the remote sensing image and the sound wave data, the risk evaluation difficulty and time are reduced, in addition, remote sensing and sound waves are combined, meanwhile, surface features and structural features are extracted, and the prediction effect of the model is optimized; through a multi-mode proximity perception model, the perception capability of the surrounding environment is improved, and the prediction precision of a single block is improved; and through the repair effect evaluation rule, a repair effect evaluation mechanism is optimized.

The invention provides a teaching document anti-copy protection method and system based on OCR interference resistance, and belongs to the technical field of information security and digital copyright protection. According to the method, anti-OCR font processing is applied to document characters, invisible disturbance symbols are inserted between characters or paragraphs, watermark information is embedded in document typesetting or font strokes, and finally a standard PDF or DOCX file is compiled. Watermark information is embedded through stroke thickness change, paragraph row spacing indentation perturbation and other modes. The system comprises a font disturbance module, a character disturbance module, a watermark embedding module, a compiling output module and a verification module. According to the method, the human eyes can normally read the document, but messy codes or disorder can occur when the OCR tool extracts the document, and the document cannot be directly reused; meanwhile, watermark information cannot be stripped, so that leakage tracking is facilitated; and the output file keeps a standard format and is compatible with the existing office teaching process. The method is suitable for anti-copying protection of teaching documents, scientific research data, test papers, contract files and the like.

An early screening system for chronic obstructive pulmonary disease based on blood routine test data. It belongs to the technical field of digital medical treatment, and specifically relates to the technical field of intelligent early screening of chronic obstructive pulmonary disease. It solves the technical problem that the generalization ability of a COPD prediction model is limited due to differences between different research data sets. The system comprises a data collection module that collects blood routine test data of a plurality of chronic obstructive pulmonary disease patients and blood routine test data of a plurality of normal personnel; a data preprocessing module that performs standardization processing on the blood routine test data to obtain a standardized data set; a screening model training module that trains N classification models using the standardized data set and calculates the prediction accuracy of each classification model; and a screening model application module that obtains the fusion weight of each model by using a normalization processing method based on the prediction accuracy of each classification model, fuses the risk scores predicted by the multiple models, and obtains a final screening result.

The invention discloses a tumor medical record time axis generation method based on multi-modal recognition and dynamic cue words, which thoroughly solves the problem of disordered stage division of a traditional method by introducing a dynamic cue word mechanism into an operation discrimination node. Through a multi-mode OCR + NLP fusion strategy, the accuracy of medical record information extraction is greatly improved; the medical compliance of the time axis is ensured through time sequence verification and field completion driven by the knowledge graph; and through front-end mind map or medical history outline visualization, the complex medical record can be clearly displayed. Practice shows that compared with manual arrangement, the time consumption of sequential output of the complete medical record is reduced by more than 90%, the item missing rate is reduced by more than 80%, and the method can be widely applied to scenes such as clinical decision support, follow-up visit management, scientific research data integration and medical insurance quality control.

The invention relates to the field of multi-currency quotation, in particular to a multi-currency quotation calculation method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining an original data set related to quotation; acquiring instant and historical exchange rate data of the transaction currency to form a market data set; calculating a cost currency estimated value of each cost composition item and summarizing to obtain a direct cost total amount; analyzing the research data to obtain a risk level, and providing a corresponding insurance cover scheme; calculating a cash flow estimated value under the influence of the exchange rate by combining the cash flow, the historical exchange rate and the insurance cover scheme, generating and sorting a contract quotation amount sample set according to a preset gross profit rate, determining the minimum contract quotation by combining the confidence coefficient, and obtaining the final contract quotation amount according to the premium parameter. According to the method for calculating the multi-currency quotation, the problems that the traditional quotation exchange rate has no standardized calculation logic and the decision is lack of quantitative support are effectively solved, accurate cost accounting and risk management and control are realized, and enterprise profit and market competitiveness are balanced.

The embodiment of the invention provides an e-commerce product market research method and system based on artificial intelligence, and the method comprises the steps: S1, analyzing user input information, converting the information into structured data, and decomposing the structured data into a plurality of subtasks; s2, analyzing the requirements of the sub-tasks and the dependency relationship between the sub-tasks by using the large language model, and generating an investigation strategy; s3, calling the MCP tool according to the investigation strategy to generate preliminary investigation data; s4, evaluating the preliminary investigation and survey data, judging whether each subtask reaches an expected investigation and survey requirement or not, and obtaining an evaluation result; s5, judging whether the preliminary investigation data is sufficient or not according to the evaluation result; and S6, calling a special statistical MCP tool according to the research result, and generating a research report. According to the method, data sufficiency is guaranteed through dynamic evaluation and supplementary investigation through a large language model and an MCP tool, an investigation report is finally generated, the whole investigation process is intelligent, and efficiency and conclusion credibility are improved.

The invention provides an electroencephalogram synchronous acquisition system compatible with nuclear magnetic resonance. The problem of interference of traditional equipment in a strong magnetic field environment is solved through innovative material selection and structural design. According to the system, a platinum-iridium alloy multi-contact implantable electrode probe is adopted and is matched with a nuclear magnetism compatible electrode wire formed by a silver-plated copper wire core body and a silver-plated nylon shielding layer, so that indoor and outdoor long-distance signal transmission of MRI (Magnetic Resonance Imaging) is realized. The signal acquisition and processing unit integrates a non-magnetic ceramic packaging pre-amplifier and an optical fiber isolation transmission data acquisition card, and is matched with a fan-free design computer, so that the influence of a magnetic field on signal processing is thoroughly avoided. According to the scheme, real-time electroencephalogram monitoring in experimental animal task state functional nuclear magnetism is supported, experiments prove that the signal-to-noise ratio is reduced by 30% or above, the distortion rate is controlled to be 2% or below, the advantages of high biocompatibility, low cost and operability are achieved, and the accuracy and reliability of scientific research data collection are remarkably improved.

The invention discloses a data modeling system based on research data, which relates to the technical field of data modeling and comprises a research data acquisition module, a research data cleaning and conversion module, a research data encryption module, a model building, screening and optimizing module and a modeling algorithm library. According to the method, dynamic model construction algorithm selection can be carried out according to research data, model construction processing is carried out, the flexibility and diversity of research data modeling attachment forms are improved, the research data are finely analyzed, reasonable screening of the model construction algorithms can be carried out according to specific data characteristics, and the model construction efficiency is improved. According to the method, the intelligence and coordination of model optimization processing are powerfully supported and guaranteed, higher convenience is also provided for calling and checking of subsequent models, encryption processing is performed on the structured data set by using the AES symmetric encryption algorithm, the attention on data transmission and storage security is improved, and the method is suitable for being used in the field of data transmission and storage. And reliable guarantee can be provided for safe storage of data.

The invention discloses a multi-modal clinical scientific research data processing method and system based on neural symbol hybrid reasoning, and belongs to the field of medical informatization and artificial intelligence. The method comprises the steps of receiving a natural language analysis instruction; analyzing the instruction into a structured formal problem description data object through a language understanding unit by utilizing a nerve-symbol hybrid inference engine, and selecting a data analysis algorithm according to an expert rule base through a symbol inference unit; then, generating a directed acyclic graph analysis flow based on the selected algorithm; and finally, according to the directed acyclic graph analysis flow, processing the multi-modal clinical scientific research data stored in the database, and generating an analysis report containing quantitative indexes. The technical problems that in the prior art, a clinical scientific research data analysis process is split, efficiency is low, and a semantic gap exists in man-machine interaction are solved, automation and intelligence of scientific research analysis are achieved, and the efficiency, depth and scientificity of data processing are remarkably improved.

This application discloses a method, equipment, medium, and product for comprehensive evaluation of equalization of basic medical services, relating to the field of medical geography. The method includes: spatial processing of research data to construct a unified geospatial database; calculating multiple evaluation index values ​​representing the spatial allocation level of medical resources and the spatial convenience of residents' access to medical care through spatial analysis to form an original decision matrix; using the entropy weight method, calculating the objective weights of each evaluation index based on the degree of variation of the multiple evaluation index values ​​across different evaluation areas; processing the original decision matrix using the objective weights based on the TOPSIS model to calculate the comprehensive evaluation index of equalization of basic medical services for each evaluation area; and performing spatial hierarchical mapping based on the comprehensive evaluation index of equalization of basic medical services to generate a multidimensional diagnostic report, thereby avoiding evaluation distortion, accurately reflecting residents' comprehensive employment opportunities in accessing medical services, and enhancing public credibility.

The invention discloses a hospital performance evaluation system based on multi-source scientific research data collaboration, and the system comprises a multi-source data collection module which is used for collecting scientific research performance original data from an internal information system of a hospital and an external scientific research database; the data collaborative processing module is connected to the multi-source data acquisition module and is used for cleaning, integrating and standardizing the scientific research performance original data to generate high-quality collaborative data; the performance indicator modeling module is connected to the data collaborative processing module and is used for calculating the high-quality collaborative data based on a data envelope analysis model and a radial basis function neural network to generate a performance evaluation result; and the performance management platform is connected to the performance indicator modeling module and is used for displaying the performance evaluation result. According to the invention, automatic acquisition, cooperative processing, intelligent modeling and visual management of scientific research data can be realized, and accurate, efficient and dynamic evaluation can be carried out on scientific research performance of hospitals, departments and individuals.

The invention provides a power dispatching strategy making method and device based on demand response, terminal equipment and a storage medium, and relates to the technical field of power dispatching. According to the method, historical operation data of a plurality of types of operation indexes of a power distribution network and behavior investigation and survey data of a plurality of users in a plurality of power utilization behavior indexes are obtained; constructing a standard evaluation matrix, quantifying the response potential of users participating in power dispatching through a foreground theory, calculating the comprehensive foreground value of each user, comprehensively evaluating the comprehensive capability of each user participating in power dispatching according to the deviation value and the comprehensive foreground value, generating a comprehensive evaluation result, and finally, determining the comprehensive capability of each user participating in power dispatching according to the comprehensive evaluation result. And grading the users, and formulating a power dispatching strategy. Therefore, the method can solve the problem that the formulated power dispatching strategy is separated from the actual condition of the user and is difficult to implement due to the fact that the response potential of the user side resources participating in power dispatching cannot be comprehensively reflected in the prior art.

The application relates to the technical field of data mining, and discloses an intelligent mining system for research data, which comprises a heterogeneous data acquisition module, a semantic association analysis module, a decision graph generation module, a time sequence feature correction module and a knowledge distillation optimization module. The heterogeneous data acquisition module captures data features and constructs a multi-layer topology through a multi-source data perception node and a dynamic dimension fusion network; the semantic association analysis module analyzes semantic association by using a concept topology modeling unit, a knowledge vector clustering unit and a multi-modal switching link; the decision graph generation module generates a core decision benchmark framework based on a strategy optimization node and a rule reasoning engine; the time sequence feature correction module performs time sequence correction and noise compensation on semantic association; and the knowledge distillation optimization module detects deviation through an entity relationship evaluation network and feeds back an optimized decision framework. The system realizes intelligent acquisition of multi-source data, dynamic analysis of semantics and adaptive generation of a decision graph, and improves the precision and efficiency of research data mining.

The application relates to a blockchain data collection method and device based on a multi-architecture NLP pre-training model, and relates to the technical field of artificial intelligence. The method comprises the following steps: training preset demand information by using a first pre-training model and a second pre-training model respectively to obtain two design schemes; analyzing the two design schemes to obtain a first analysis result, generating a first positive sample data set, and obtaining a final design scheme according to the first positive sample data set; analyzing market research data by using the first pre-training model and the second pre-training model respectively to obtain two preliminary data results; analyzing the two preliminary data results to obtain a second analysis result, generating a second positive sample data set, and obtaining a final data result according to the second positive sample data set; and generating a new block according to the first positive sample data set and the second positive sample data set, and responding to and authenticating the new block. The application has the effects of improving data processing efficiency and data accuracy.

The invention relates to the technical field of artificial intelligence, and discloses a national region traditional settlement and building knowledge base construction method based on a large language model and a knowledge graph technology and a question answering system. The method comprises the following steps: converting building surveying and mapping data into semantic ontology data, splitting the structured data into a plurality of entity tables and relation tables, and importing the entity tables and the relation tables into a graph database; unstructured data such as interview records and historical literatures are sorted into an entity and relation structure, and the entity and relation structure is imported into a graph database; extracting an entity type, and creating an AI prompt word; constructing a query module, and converting a question proposed by a user by using a natural language into a graph database query statement as a first output item through a large language model; the query result serves as a second output item; and converting the second output item into a natural language by using a large language model, and returning the natural language to the user as a third output item in an agreed format. According to the system, the settlement and building research data query efficiency is improved, multi-level data is associated, and the knowledge reasoning ability is provided.

The application discloses an Alzheimer's disease classification method based on channel residual attention. The method classifies Alzheimer's disease by fusing the characteristics of residual modules and channel attention mechanisms. The network is composed of an input module, a channel separation residual module, a channel attention module and an output module. Firstly, aiming at the problems existing in the current research data set, a scientific division strategy of the data set is formulated under the guidance of a clinician; then the processed data are sent into the channel separation residual module to extract the shallow and deep features of the network and prevent repeated gradient information; then the extracted features are sent into the channel attention module to adjust the weight between channels and obtain more accurate classification features; finally, the feature matrix is sent into a linear classification layer to output a classification result. The method has broad application prospects in the field of medical images and Alzheimer's disease classification.

The invention discloses an automobile suspension system adjustment and calibration method, which comprises the following steps: S1, forming market investigation and survey data through market investigation and survey; s2, making a vehicle simulation model, and performing vehicle dynamics simulation to obtain vehicle simulation result data; the vehicle simulation model comprises a suspension system, a steering system and a tire system; s3, setting a control and comfort target to form a subjective evaluation target data set; s4, making a suspension system adjustment plan, and forming a suspension adjustment strategy document; s5, performing a suspension system test to obtain suspension system performance test data; s6, according to the suspension system performance test data, formulating an adjustment sample list including key parts needing to be adjusted, and forming an adjustment sample document; s7, adjusting key parts of the suspension system, and forming a part adjusting strategy document; s8, organizing acceptance, and evaluating an adjustment result; s9, after the acceptance passes, carrying out objective test to obtain objective test data of the suspension system; s10, performing a final state test on the adjusted suspension system to obtain final state test data of the suspension system; and S11, issuing a suspension system adjustment parameter data set. According to the automobile suspension system adjustment method, performance adjustment of the automobile suspension system can be achieved, the adjustment work efficiency is improved, and the vehicle driving performance is improved. The invention further discloses an automobile suspension system adjusting device.

The present application relates to the technical field of biological research data analysis, and discloses a kind of computing biology research data analysis display method, including extracting total RNA from biological tissue or cell, RNA reverse transcription is cDNA, constructs library, and utilizes high-throughput sequencing platform to sequence library, to obtain a large number of short sequences.The present application can effectively identify abnormal repeat regions by comparing and threshold judging the number of short sequences mapped to the same genomic coordinate interval, so as to determine whether the gene expression difference result is reliable, when the number of abnormal sequences exceeds the preset repeat sequence threshold, by eliminating the influence of repeat sequence operation, i.e. for the case of high FPKM value, remove the completely same and overlapping short sequences, and re-align the updated results, the expression distortion problem caused by repeat counting can be corrected.

The invention provides a scientific research data sharing method and system and a storage medium, and belongs to the technical field of data encryption, and the method comprises the steps: generating an original key pair when a request for uploading scientific research data is received, and obtaining encrypted scientific research data; requesting a cloud to upload the encrypted scientific research data to obtain a public key; encrypting the original key pair through the public key to obtain an encrypted original key pair; when a request for acquiring the scientific research data is received, acquiring the encrypted scientific research data with an encrypted original key pair from the cloud; after a main password input by a user is received, decrypting an encrypted private key pre-stored in the client based on the main password to obtain a plaintext private key; decrypting the encrypted original key pair through the plaintext private key to obtain the original key pair; and decrypting the encrypted scientific research data through the original secret key pair to obtain the scientific research data. According to the invention, the confidentiality of scientific research data is enhanced.

The invention provides a cardiovascular and cerebrovascular disease knowledge graph construction method and related equipment. The method comprises the following steps: analyzing multi-modal scientific research data, and extracting candidate entities and relation information; based on the first ontology and the second ontology, constructing a dual-drive unified knowledge ontology structure through semantic association; performing cross-modal semantic alignment and fusion to form entity nodes and relation edges; calculating prior credibility based on the evidence source attribute, and fusing the prior credibility and the likelihood information by using a probability graph model to obtain posterior credibility; sorting and rule induction are carried out on paths in the knowledge graph based on posterior credibility, a high-confidence rule is used as structured prior information to be fed back to the calculation process of a probability graph model according to a stability evaluation mechanism, and the weight is dynamically adjusted according to time information. The accuracy and robustness of the cardiovascular and cerebrovascular disease mapping knowledge domain can be improved.

The utility model provides a belt type roasting machine system for a ball cage test. The belt type roasting machine system comprises a belt type roasting machine; the test cage is arranged on a trolley of the belt type roasting machine; an open hole and a movable cover plate covering the open hole are arranged on a sealing protective cover between a cooling section furnace cover and a tail rack of the belt type roasting machine; a test cage grabbing device is fixed on the tail rack; and the test cage grabbing device is positioned above the open hole. The utility model designs the belt type roasting machine process test system suitable for the actual production, the provided test research condition is more suitable for the actual production, and the obtained research data and recommended process system can be used as the basis for the design, production and operation of a belt type roasting machine pelletizing plant.

The invention belongs to the technical field of biological model construction, and particularly relates to a method for constructing a vasculitis model in zebra fish. The compound is obtained by inducing a Candida albicans water soluble substance (CAWS), and the specific method is micro-injection or soaking. According to the method, whether modeling succeeds or not can be judged in the living body state of the model animal, the method is more suitable for visually observing the inflammation occurrence position, a research method for vasculitis (including Kawasaki disease) is developed, follow-up scientific research data can be richer and more accurate, and a more solid theoretical basis is laid for clinical transformation of targeted therapy of vasculitis (including Kawasaki disease).

The invention relates to a configuration-constrained thin reservoir oil-gas-water distribution prediction method, and belongs to the technical field of oil exploration and development. The invention discloses a configuration-constrained thin reservoir oil-gas-water distribution prediction method, which comprises the following steps of: acquiring previous research data, seismic data, logging data and core data of a target work area, and investigating a sedimentary background and modern sedimentary mode data of the target work area; determining a river type; evaluating and analyzing the connectivity of the narrow strip sand body; evaluating and analyzing the connectivity of the flaky river channel sand body; delineating a sand body range, and determining an oil-gas-containing sand body area in the work area; and finally obtaining the oil-gas-water distribution rule of the thin reservoir under the constraint of the configuration level. According to the method, configuration level division and configuration unit and configuration interface recognition are carried out, forward modeling is combined, the sand body superposition relation of an actual seismic section is verified, and under the constraints of various conditions, the thin reservoir oil-gas-water distribution rule under the configuration constraints is finally obtained.

The invention discloses an occupational pneumoconiosis screening and management system based on multi-source data fusion, and relates to the technical field of occupational disease prevention and treatment, the system comprises a multi-source data acquisition module, a data fusion module, a screening diagnosis module, a scheme making module and a follow-up visit management module; image data, physiological data, basic clinical data, biomarker detection data and treatment process data are integrated through the multi-source data acquisition module, the multi-source data are classified, cleaned and standardized through the data fusion module, features are extracted, and a multi-dimensional data model is constructed. A classification diagnosis model is built based on multi-center prospective queue research data, health state and illness state classification of the examinee is completed, so that limitation of a single data dimension is broken, complementarity of multi-source data is utilized to provide a comprehensive basis for diagnosis classification, classification standards are more scientific and universal through queue research data support, and classification accuracy is improved. And a solid foundation is laid for formulating an intervention scheme.

This invention provides a blockchain-based method for sharing scientific research data. This method leverages the decentralized nature of blockchain to break the data monopoly of traditional centralized systems, enabling the free flow of research data among multiple nodes and improving data sharing efficiency. Secondly, the application of encryption technology and hash functions ensures data security and accuracy during transmission, reducing the risk of data leakage. Furthermore, the application of smart contracts and data version control systems enables automated data management and tracking, improving data compliance and quality. Finally, the establishment of a data indexing and retrieval system allows researchers to quickly find the datasets they need, promoting the sharing and collaboration of scientific research data. In conclusion, this blockchain-based method for sharing scientific research data has significant advantages and broad application prospects.

The invention provides a tobacco leaf raw material spectrogram data management method and system and a storage medium. The tobacco leaf raw material spectrogram data management method comprises the steps of S1, obtaining initial spectrogram data of tobacco leaf raw materials; s2, classifying and managing the initial spectrogram data according to preset spectrogram data types to obtain target spectrogram data; and S3, performing data analysis processing on the target spectrogram data to generate an analysis result corresponding to the tobacco leaf raw material. The invention aims to provide core technical support for design and implementation of a tobacco scientific research big data management system. According to the method, spectrogram sources and formats are investigated, spectrogram data are classified, deep analysis mining is performed according to the classified spectrogram data in combination with multiple chemometrics algorithms, a foundation is laid for centralized storage, efficient retrieval, unified management and safe sharing of the spectrogram data and other scientific research data, the tobacco scientific research efficiency can be improved, and the tobacco scientific research efficiency can be improved. And powerful support is provided for industry scientific and technological innovation and decision making.

The application discloses a method for constructing a gene regulation network based on meta-analysis, and aims to solve the problem that a gene regulation network has a large error and a low accuracy because different research data are not completely homogeneous when the gene regulation network is expanded by combining data of multiple studies to enlarge a sample size, and the method comprises the following steps: performing meta-analysis on each transcriptomic gene expression dataset obtained to obtain a significant differential gene list; obtaining a transcription factor gene list according to a species to which the transcriptomic gene expression data belong, and generating a core gene list according to the transcription factor gene list and the significant differential gene; calculating a Pearson correlation coefficient of each core gene and each significant differential gene, and constructing a co-expression network according to the Pearson correlation coefficient; clustering the co-expression network to obtain a plurality of differential gene modules with high correlation of the core genes; and combining biological knowledge and a structural equation model to construct a corresponding gene regulation network according to each module. The application belongs to the field of gene regulation networks.

This invention proposes a method, system, and storage medium for constructing a Rorschach corpus for depression screening. It collects multimodal raw data related to the Rorschach test, and performs editing and preprocessing. A core data model is constructed to store the multimodal data and their relationships. Through a data entry and import module, the multimodal data is stored in the core data model. Through a data association and retrieval module, cross-modal relational queries and a unified view are provided. Through a data export and sharing module, the data is exported in a specified structured format. Through a deep learning model integration module, the multimodal data is used for predictive analysis and stored in the core data model. The method, system, and storage medium for constructing a Rorschach corpus for depression screening provided by this invention avoid the problems existing in current Rorschach test research data management, such as poor multimodal data correlation, difficult version management, low collaboration efficiency, non-standard metadata recording, and difficulty in supporting deep learning model training.