An oral medical big data storage platform and a data storage method

Abstract

The application provides an oral medical big data storage platform and a data storage method, relates to the technical field of oral medical data processing, and comprises a data acquisition access module, a data processing and standardization module, a hierarchical distributed storage module, a data management and traceability module and a data interface and application service module. The multi-source data compatible adaptation of the application supports the data access of mainstream oral equipment and denture design / production software, adapts to STL, DCM and other oral exclusive formats, is matched with precision verification and abnormal filtering, solves the problems of multi-source data islands and insufficient precision, accurately adapts to the oral cavities of Chinese people through a built-in Mongolian ethnic group oral cavity feature extraction engine, establishes a classification indexing standard suitable for the oral cavities of Chinese people, and meets the needs of the clinical treatment, denture research and development and production of Chinese people. The application is cross-terminal and efficient, the standardized API interface is used to connect diagnosis and treatment, AI design, production and teaching platforms, the full-link data is shared on demand, the data barriers are broken, and the collaborative efficiency of the industrial chain is improved.

Description

Technical Field

[0001] This invention relates to the field of oral medical data processing technology, and in particular to an oral medical big data storage platform and data storage method. Background Technology

[0002] With the rapid development of digital technology in oral healthcare, the entire process of oral diagnosis and treatment, denture design and production has been digitally upgraded. In this process, a large amount of heterogeneous oral healthcare data from multiple sources is generated, covering various types such as patient oral 3D scan data, CBCT image data, clinical diagnosis and treatment records, denture design documents, production and processing data, and postoperative follow-up data. The data formats include oral-specific formats such as STL, DCM, InLab, and htl.

[0003] Existing oral healthcare data storage solutions mostly adopt a single storage architecture, failing to be customized to address the specific characteristics, diversity, and end-to-end usage needs of oral data. This results in numerous technical shortcomings, making it difficult to meet the compliance and practicality requirements of the oral healthcare industry: First, poor compatibility of multi-source data; different brands of intraoral scanners, CBCT devices, denture design software, and 3D printing equipment output inconsistent data formats, hindering efficient and unified access and leading to severe data silos. Second, the lack of a standardized processing system; the absence of classification, coding, and indexing standards adapted to the oral health of Chinese patients results in insufficient targeted data processing and an inability to achieve precise standardized processing. Third, the lack of data management and cross-platform sharing; chaotic data management; a lack of standardized management mechanisms and cross-platform integration capabilities; different roles cannot access authorized data as needed; and the entire oral clinical-design-production data chain cannot be accessed and shared on demand.

[0004] In view of the shortcomings of the existing technologies, there is an urgent need for a big data storage platform and data storage method for oral medical care. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a big data storage platform and method for oral healthcare. It specifically addresses core technical deficiencies in existing technologies, such as incompatibility of multi-source data access, lack of standardized processing systems, and deficiencies in data management and cross-platform sharing. This invention further improves the oral healthcare data storage architecture, strengthens data security, optimizes privacy protection strategies, and enhances end-to-end traceability capabilities. It achieves standardized storage, secure traceability, and cross-platform sharing of data throughout the entire oral healthcare process, accurately adapting to the data management needs of the entire oral clinical-design-production chain. This effectively improves the efficiency and security of oral healthcare data management, while also considering industry compliance and practical application.

[0006] In a first aspect, this invention provides a big data storage platform and method for oral healthcare, specifically comprising: a data acquisition and access module, a data processing and standardization module, a hierarchical distributed storage module, a data management and traceability module, and a data interface and application service module. These modules work together to achieve standardized storage, secure traceability, and cross-platform sharing of data throughout the entire oral healthcare process; wherein: The data acquisition and access module supports multi-source data access from 3Shape TRIOS intraoral scanner, iTero intraoral scanner, CBCT equipment, exocad denture design software, and 3D printing production equipment. It is compatible with oral-specific data in STL, DCM, InLab, and htl formats and has accuracy verification and abnormal data filtering functions for oral data. It can detect oral-specific data anomalies such as intraoral scan data point deviation and CBCT image blurring. The data processing and standardization module has a built-in extraction engine based on the oral data characteristics of the Mongoloid race. It establishes classification, coding, and indexing standards adapted to the oral cavity of Chinese people, performs double-layer desensitization processing, lightweight compression, and extraction of core features of oral diagnosis and treatment / prosthetic production on oral data. The core features include three-dimensional tooth morphology, alveolar bone parameters, occlusal relationship, etc. The hierarchical distributed storage module adopts a local + cloud-based drawer-style hierarchical architecture, including a hot data storage unit, a warm data storage unit, and a cold data storage unit. It also achieves dual backup across different locations and machines, adapting to the data storage needs of the entire chain from clinical practice to design and production in the dental field. The data management and traceability module assigns a unique identifier to each piece of oral data. The unique identifier integrates patient ID, oral data type, collection time, and denture production order number information to establish a hierarchical index library and an oral-specific multi-level permission system, realizing full-chain traceability from oral data collection, processing, storage to clinical / production applications. The data interface and application service module provides a standardized API interface, supporting cross-platform integration with digital oral diagnosis and treatment platforms, oral AI design software, intelligent denture manufacturing systems, and oral teaching platforms, enabling on-demand retrieval and sharing of oral data.

[0007] Furthermore, in the hierarchical distributed storage module: The hot data storage unit is deployed in a local high-speed cache, prioritizing the storage of frequently accessed oral clinical diagnosis and treatment data and real-time production design data of dentures within one year. It uses a high-speed solid-state drive to achieve millisecond-level retrieval, adapting to the doctor's need for rapid retrieval during follow-up visits. The warm data storage unit is deployed on a general-purpose cloud storage node to store 1-5 years of regularly accessed oral history treatment and denture mass production data, balancing storage cost and oral data access speed. The cold data storage unit is deployed on a cloud disaster recovery node using the IPFS distributed cloud storage protocol. It stores low-frequency access but permanent oral archive data and scientific research and teaching data, ensuring that oral data is tamper-proof and meeting the compliance requirements for oral medical traceability.

[0008] Furthermore, the two-layer desensitization process of the data processing and standardization module is as follows: the first layer removes sensitive information such as patient name, ID number, and mobile phone number and assigns a unique anonymous identifier to the platform; the second layer performs partial masking on key information of oral diagnosis and treatment, while fully retaining core clinical data of oral cavity such as tooth position, disease, and treatment plan, taking into account both privacy protection and clinical practice.

[0009] Furthermore, the data management and traceability module has a multi-level permission system corresponding to the role settings of the entire oral medical process, including dentists, dental technicians, oral R&D personnel, and platform administrators. Different roles can only access oral data within the authorized scope. Among them, dentists can only access the treatment-related data of the patients they have treated, and dental technicians can only access the denture design and production data of the corresponding production orders.

[0010] A data storage method for an oral medical big data storage platform includes the following steps: S1: Standardized collection and access of multi-source heterogeneous oral data. It receives raw oral data in multiple formats from the oral clinical end, the denture design end, and the denture production end. After the oral data undergoes a dedicated accuracy verification, it is converted into a unified oral data standard format on the platform. S2: Oral data desensitization and feature processing provides double-layer privacy protection for the original oral data. At the same time, it uses the Mongolian oral feature extraction engine to extract core oral feature data such as tooth morphology, alveolar bone parameters, and occlusal relationship. The original full oral data and feature extraction data are stored separately to adapt to different needs of clinical diagnosis and treatment and denture development. S3: Oral data classification and coding indexing, which is divided into three levels according to oral data type, oral specific use scenario, and access frequency. A unique standardized code is assigned to each piece of data and a multi-dimensional index is established. The multi-dimensional indexing information includes patient age, patient gender, tooth position, denture restoration method, and manufacturer. S4: Drawer-style hierarchical distributed storage and off-site disaster recovery automatically schedules the classified data to the corresponding storage unit. Related data of the same patient / denture production order / oral research project are grouped into oral data drawers, while completing off-site and off-machine dual backup to ensure the security of oral data storage. S5: Hierarchical index establishment and full-chain traceability. A hierarchical index library is established based on standardized coding. The entire life cycle of oral data is linked through a unique identifier, enabling full traceability of oral data from oral scanning and collection, data processing, denture design and modeling, 3D printing / cutting production, clinical diagnosis and treatment applications to postoperative follow-up. All operations are traceable. S6: Data security protection and dynamic scheduling. It adopts the AES-256 encryption algorithm to ensure the security of oral data storage and transmission. It controls oral data access through permission verification and has a built-in dynamic data scheduling engine to realize the automatic migration of oral data between different storage units and adapt to the changing needs of oral data access frequency.

[0011] Furthermore, the three-level classification in step S3 is as follows: According to data type, it is divided into oral clinical diagnosis and treatment data, oral medical imaging data, denture design and development data, denture production and processing data, and oral teaching and experimental data. Based on usage scenarios, they are divided into: real-time oral diagnosis and treatment, denture production and design, oral scientific research and development, and oral data archiving and traceability. Oral data is categorized by access frequency into oral thermal data, oral temperature data, and oral cold data.

[0012] Furthermore, the off-site disaster recovery strategy in step S4 is as follows: hot data is backed up on at least two independent local servers to meet the emergency retrieval needs of dental clinics without network access; warm / cold data is backed up on at least two storage nodes in different provincial administrative regions in the cloud to avoid the loss of dental archive data and research data.

[0013] Furthermore, the data dynamic scheduling rules in step S6 are as follows: if oral cold data is accessed 5 times within 30 days, it will be automatically migrated to the hot data storage unit; if oral hot data has not been accessed frequently for more than 1 year, it will be automatically migrated to the warm data storage unit to optimize the allocation of oral data storage resources.

[0014] Furthermore, the multi-source oral data in step S1 includes patient oral 3D scan data, CBCT imaging data, oral clinical diagnosis and treatment records, doctor's medical records, denture design documents, denture production and processing order data, and postoperative follow-up data.

[0015] Furthermore, the full-chain traceability in step S5 allows for one-click retrieval of the complete operation record of the corresponding oral data through a unique identifier, including data collection personnel, processing time, designers, production processes, treating physicians, and operation content, thus meeting the requirements for compliance traceability and quality control in oral healthcare.

[0016] Compared with the prior art, the present invention has the following significant advantages: Multi-source data compatibility and adaptation: Supports data access from mainstream dental devices (3Shape TRIOS / iTero intraoral scanners, CBCT, etc.) and denture design / production software, adapts to dental-specific formats such as STL and DCM, and is equipped with accuracy verification and anomaly filtering to solve the problems of multi-source data silos and insufficient accuracy, and achieve standardized and unified access.

[0017] Precise Adaptation to Chinese Oral Health: It incorporates an oral feature extraction engine for the Mongoloid race, establishes classification indexing standards adapted to the oral health of Chinese people, and accurately extracts core features such as tooth morphology and alveolar bone parameters to meet the personalized needs of Chinese oral clinical practice and denture research and development.

[0018] Cross-platform collaboration and high efficiency: Standardized API interfaces connect oral diagnosis and treatment, AI design, denture production, and teaching platforms, enabling on-demand data retrieval and sharing, breaking down data barriers across the entire chain, and improving the collaborative efficiency of the oral healthcare industry chain.

[0019] Storage security and compliance, while balancing efficiency and cost: Local + cloud drawer-style tiered storage (hot / warm / cold data partitions), coupled with off-site and off-machine dual backup (hot data on local dual machines, warm / cold data across provincial cloud dual nodes), and the IPFS protocol for cold data to ensure immutability, which not only meets the compliance requirements for medical data traceability, but also optimizes storage resources and reduces costs.

[0020] Refined privacy protection and access control: Double-layer desensitization (identity unbinding + privacy masking) balances privacy and clinical use, and a multi-level access control system allocates authorization according to roles such as doctors and dental technicians to accurately prevent patient privacy leaks and comply with medical data security standards.

[0021] Full-chain traceability, adapted to quality control: unique identification code + hierarchical index, realizes full-process traceability of data from collection, processing, denture production to clinical application and postoperative follow-up, and one-click access to operation records, meeting the needs of oral medical compliance traceability and quality control. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments will be briefly described below.

[0023] The accompanying drawings described below are only related to some embodiments of the invention and are not intended to limit the invention.

[0024] In the attached diagram: Figure 1 This is an overall architecture diagram of the oral medical big data storage platform of the present invention.

[0025] Figure 2 This is a hierarchical architecture diagram of the layered distributed storage module of the present invention.

[0026] Figure 3This is the interaction logic diagram of the data management and traceability module of the present invention.

[0027] Figure 4 This is a flowchart of the oral medical big data storage method of the present invention.

[0028] Figure 5 This is an internal flowchart of the data processing and standardization module of the present invention. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the described embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] Please refer to Figures 1 to 5 Example 1: This invention proposes a big data storage platform and method for oral healthcare, comprising: a data acquisition and access module, a data processing and standardization module, a hierarchical distributed storage module, a data management and traceability module, and a data interface and application service module. These modules work together to achieve standardized storage, secure traceability, and cross-platform sharing of data throughout the entire oral healthcare process. The data acquisition and access module supports wired or wireless data access from 3Shape TRIOS intraoral scanners, iTero intraoral scanners, CBCT equipment, exocad denture design software, and 3D printing production equipment. It has a built-in dedicated format parsing engine that can directly parse STL format intraoral 3D data, DCM format CBCT image data, InLab format denture design intermediate data, and HTL format denture production data, achieving seamless access to multi-source heterogeneous data. Simultaneously, this module has a dedicated accuracy verification function for oral data. Using a preset oral data accuracy threshold, it performs point deviation detection on the accessed intraoral scan data (e.g., a deviation threshold of 0.05mm is set; data exceeding this threshold is considered abnormal), and performs blur detection on CBCT image data (determined by pixel clarity threshold). Abnormal data is marked and alerted to staff for review, and invalid data is filtered to ensure the accuracy and validity of the accessed data, providing a reliable foundation for subsequent data processing. The data processing and standardization module incorporates an extraction engine based on oral data features of the Mongoloid race. It uses machine learning algorithms to extract core features from oral data, including three-dimensional tooth morphology (crown height, arch curvature, tooth arrangement), alveolar bone parameters (alveolar bone height, width, bone density), and occlusal relationships (maxillary and mandibular occlusal gaps, occlusal angles, and occlusal contact points). This fully adapts to the oral anatomy characteristics of the Chinese population, enhancing the relevance of data processing. It establishes classification, coding, and indexing standards suitable for the Chinese oral cavity and performs a two-layer desensitization process on the oral data: the first layer removes core sensitive information such as patient name, ID number, and mobile phone number. Each patient is assigned a unique anonymous identifier on the platform to decouple their identity from their data, preventing the leakage of identity information. The second layer partially masks key privacy information in oral diagnosis and treatment (such as special medical history, family medical history, etc.), retaining only core clinical data such as tooth position, symptoms, treatment plan, and treatment time. This balances privacy protection with clinical practical use, ensuring that the anonymized data still meets the needs of clinical diagnosis and treatment, denture design and production. In addition, this module uses a lossless compression algorithm to perform lightweight compression processing on oral data, compressing the data volume by 30%-50% without sacrificing data accuracy, effectively improving data transmission and storage efficiency and reducing storage costs. The hierarchical distributed storage module adopts a local + cloud-based drawer-style hierarchical architecture, divided into hot data storage unit, warm data storage unit, and cold data storage unit, while simultaneously achieving off-site and off-machine dual backup. The specific configuration is as follows: (1) Hot data storage unit: Deployed in the local high-speed cache of the dental medical institution, using high-speed solid-state drive (SSD), prioritizing the storage of frequently accessed oral clinical diagnosis and treatment data within one year (such as patient follow-up data, real-time diagnosis and treatment records, recent treatment plans) and denture real-time production design data, realizing millisecond-level retrieval, adapting to the needs of dentists to quickly retrieve patient data during follow-up visits, and improving clinical diagnosis and treatment efficiency; (2) Warm data storage unit: Deployed on a general storage node in the cloud (such as cloud servers of Alibaba Cloud and Tencent Cloud) to store oral history treatment data, denture batch production data and patient mid-term follow-up data that are regularly accessed for 1-5 years. It takes into account both storage cost and data access speed, supports staff to retrieve data as needed, and meets the needs of routine treatment and production review. (3) Cold data storage unit: The IPFS distributed cloud storage protocol is deployed on the cloud disaster recovery node to store oral archive data that is accessed infrequently but needs to be permanently retained (such as long-term follow-up data of patients and data of difficult cases), oral scientific research and teaching data. The decentralized characteristics of the IPFS protocol are used to realize the immutability of data, meet the compliance requirements for long-term traceability of oral medical data, and ensure the long-term safe storage of data. The data management and traceability module assigns a unique identifier to each piece of oral data. This unique identifier adopts a combination format of patient anonymity identifier-data type-collection time-association number to achieve unique identification of each piece of data and ensure that the data can be accurately located. A hierarchical index library was established, with multi-level indexes created based on data type, usage scenario, and access frequency, significantly improving data retrieval efficiency. Staff can quickly retrieve the data they need through the index. Simultaneously, a multi-level permission system specifically for the dental field was established, with permissions set for roles throughout the entire dental care process, as detailed below: (1) Dentists: They can only access the treatment-related data of the patients they have treated and cannot access the data of patients treated by other doctors, thus ensuring the precise matching of patient data privacy and doctor work permissions; (2) Dental technicians: can only access the denture design and production data of the corresponding production order, and cannot access the patient's private information, to ensure the relevance and security of the production data; (3) Oral research and development personnel: can only access desensitized oral research data for the research and development of oral medical technology and denture products, taking into account both research needs and privacy protection; (4) Platform Administrator: Has full access and management rights to all data, and can perform operations such as permission allocation, data maintenance, and anomaly handling to ensure the normal operation of the platform; By linking oral data to a unique identifier throughout its entire lifecycle, the system enables full-chain traceability from data collection, processing, and storage to clinical application, denture production, and postoperative follow-up, ensuring that the entire data flow is traceable and controllable.

[0031] The data interface and application service module provides standardized API interfaces, supporting cross-platform integration with digital oral diagnosis and treatment platforms, oral AI design software, intelligent denture manufacturing systems, and oral teaching platforms, enabling on-demand retrieval and sharing of oral data. For example, denture manufacturers can directly access denture design data via the API interface, eliminating the need for manual import and improving production efficiency; oral teaching platforms can access anonymized oral case data for teaching demonstrations and practical instruction; and oral AI design software can access core oral feature data to assist in intelligent denture design, improving design accuracy and efficiency.

[0032] Example 2: This example provides a data storage method based on the oral medical big data storage platform described in Example 1, including the following steps: S1: Standardized Acquisition and Access of Multi-Source Heterogeneous Oral Data At the clinical level, 3D oral data (STL format) of patients is acquired using the 3Shape TRIOS intraoral scanner and the iTero intraoral scanner, and oral imaging data (DCM format) is acquired using CBCT equipment. Simultaneously, patient clinical treatment records and physician medical records are recorded. At the prosthesis design level, prosthesis design files (InLab format) are generated using exocad prosthesis design software. At the prosthesis production level, prosthesis production and processing data (HTL format) is output using 3D printing equipment, and prosthesis production and processing order data is recorded. Staff simultaneously input postoperative follow-up data from patients.

[0033] The data acquisition and access module receives the above-mentioned multi-format raw oral data, performs oral-specific accuracy verification on the data, detects abnormal data such as deviation of intraoral scan data points and blurry CBCT images, marks abnormal data and reminds staff to review it, filters invalid data, and converts all raw data into the platform's unified oral data standard format to achieve unified compatibility of multi-source data and lay the foundation for subsequent data processing.

[0034] The multi-source oral data in this step includes patient oral 3D scan data, CBCT imaging data, oral clinical diagnosis and treatment records, doctor's medical records, denture design documents, denture production and processing order data, and postoperative follow-up data, comprehensively covering all data types in the entire oral medical process.

[0035] S2: Dental Data Desensitization and Characterization The data processing and standardization module provides dual-layer privacy protection for the raw oral data collected in step S1: The first layer removes core sensitive information such as patient name, ID number, and mobile phone number, and assigns a unique anonymous identifier to each patient to decouple patient identity from data; the second layer partially masks key privacy information in oral diagnosis and treatment, while retaining core clinical data such as tooth position, symptoms, treatment plan, and treatment time, balancing privacy protection with clinical application.

[0036] Meanwhile, through the Mongolian oral feature extraction engine, core oral feature data such as tooth morphology, alveolar bone parameters, and occlusal relationship are extracted. The original full oral data and feature extraction data are stored separately. The original full data is used for clinical traceability and case review, while the feature extraction data is used for denture research and development and AI design, adapting to the different needs of clinical diagnosis and treatment and denture research and development.

[0037] S3: Oral Data Classification and Coding Indexing The oral cavity data processed in step S2 is divided into three categories based on the type of oral cavity data, the specific usage scenario of oral cavity, and the access frequency. The specific categories are as follows: (1) By data type: oral clinical diagnosis and treatment data, oral medical imaging data, denture design and development data, denture production and processing data, and oral teaching and experimental data; (2) By usage scenario: for real-time oral diagnosis and treatment, for denture production and design, for oral scientific research and development, and for oral data archiving and tracing; (3) By access frequency: oral thermal data (high-frequency access within 1 year), oral temperature data (routine access within 1-5 years), and oral cold data (low-frequency access that needs to be permanently retained).

[0038] Each piece of data is assigned a unique standardized code, with the coding format consistent with the unique identifier. At the same time, multi-dimensional indexing is established, and the indexing information covers core information such as data type, usage scenario, and access frequency, so as to achieve accurate data classification and efficient retrieval.

[0039] S4: Drawer-type hierarchical distributed storage and off-site disaster recovery Based on the classification results of step S3, the oral data is automatically scheduled to the corresponding storage units of the hierarchical distributed storage module: hot data is stored in the local hot data storage unit, warm data is stored in the cloud warm data storage unit, and cold data is stored in the cloud cold data storage unit.

[0040] Data related to the same patient, the same denture production order, or the same oral research project is grouped into independent oral data drawers to achieve centralized data management. This allows staff to access all data of the same associated entity as needed, while implementing an off-site disaster recovery strategy: hot data is backed up on at least two independent local servers to meet the emergency access needs of oral clinics without network access, ensuring normal clinical work can continue in a network-free environment; warm / cold data is backed up on at least two storage nodes in different provincial administrative regions in the cloud to prevent the loss of oral archive data and research data, thereby improving the security and reliability of data storage.

[0041] S5: Hierarchical Indexing and Full-Chain Traceability A hierarchical index library is established based on the standardized coding assigned in step S3. Multi-level indexes are established according to data type, usage scenario, and access frequency, which greatly improves data retrieval efficiency. The entire life cycle of oral data is linked through a unique identifier, enabling full traceability of oral data from oral scanning and acquisition, data processing, denture design and modeling, 3D printing / cutting production, clinical diagnosis and treatment applications to postoperative follow-up. All operational behaviors are traceable.

[0042] Staff can retrieve the entire process record of corresponding oral data with one click using a unique identification code. This includes data collection personnel, processing time, designers, production procedures, treating physicians, and the operation content of each step, meeting the requirements for compliance traceability and quality control in oral healthcare and enabling full control over data flow.

[0043] S6: Data Security Protection and Dynamic Scheduling The AES-256 encryption algorithm is used to encrypt the storage and transmission of oral data to prevent data leakage during storage or transmission and ensure data security. A multi-level access control mechanism is used to control access to oral data. Staff members must pass identity verification and access control before they can access data within the authorized scope, further preventing data leakage.

[0044] The built-in dynamic data scheduling engine executes the following scheduling rules: If oral cold data is accessed 5 times within 30 days, it will be automatically migrated to the hot data storage unit to ensure the retrieval efficiency of high-frequency access data; if oral hot data has not been accessed frequently for more than 1 year, it will be automatically migrated to the warm data storage unit to optimize the configuration of oral data storage resources, reduce storage costs, and achieve efficient utilization of storage resources.

[0045] The working principle of this embodiment is as follows: The core working principle is to achieve a closed-loop flow of data collection, processing, storage, management, and sharing throughout the entire oral healthcare process through the coordinated operation of five core modules. This balances data compatibility, security, compliance, and practicality. Specifically, the principle is as follows: First, the data collection and access module completes unified access and accuracy verification of multi-source heterogeneous oral data, filtering abnormal data and achieving standardized compatibility with different devices and data formats. Second, the data processing and standardization module, based on a Mongolian ethnic oral feature extraction engine, completes data desensitization, feature extraction, and standardized encoding, protecting patient privacy while improving data relevance. Subsequently, the hierarchical distributed storage module implements hierarchical storage of hot, warm, and cold data according to data access frequency, combined with remote... The dual-backup strategy balances access efficiency and data security. Cold data is made immutable via the IPFS protocol, meeting compliance and traceability requirements. Simultaneously, the data management and traceability module utilizes unique identifiers, a hierarchical index library, and a multi-level permission system to achieve end-to-end data traceability and refined access control, ensuring data is traceable, manageable, and leak-proof. Finally, the data interface and application service module enables cross-platform data sharing through standardized API interfaces. The dynamic data scheduling engine automatically adjusts data storage units based on access frequency, optimizing storage resource configuration. The entire workflow forms a closed loop, with all modules working collaboratively to perfectly adapt to the end-to-end data management needs of oral clinical practice, design, and production. This addresses many shortcomings of existing technologies and improves the efficiency and security of oral medical data management.

[0046] The following points should be noted in this article: 1. The accompanying drawings of the embodiments of the present invention only involve the structures involved in the embodiments of the present invention; other structures can refer to general designs.

[0047] 2. Where there is no conflict, the embodiments of the present invention and the features thereof can be combined with each other to obtain new embodiments.

[0048] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A dental medical big data storage platform, characterized in that, include: The system comprises a data acquisition and access module, a data processing and standardization module, a hierarchical distributed storage module, a data management and traceability module, and a data interface and application service module. These modules work together to achieve standardized storage, secure traceability, and cross-platform sharing of data throughout the entire oral healthcare process. The data acquisition and access module supports multi-source data access from 3Shape TRIOS intraoral scanner, iTero intraoral scanner, CBCT equipment, exocad denture design software, and 3D printing production equipment. It is compatible with oral-specific data in STL, DCM, InLab, and htl formats and has accuracy verification and abnormal data filtering functions for oral data. It can detect oral-specific data anomalies such as intraoral scan data point deviation and CBCT image blurring. The data processing and standardization module has a built-in extraction engine based on the oral data characteristics of the Mongoloid race. It establishes classification, coding, and indexing standards adapted to the oral cavity of Chinese people, performs double-layer desensitization processing, lightweight compression, and extraction of core features of oral diagnosis and treatment / prosthetic production on oral data. The core features include three-dimensional tooth morphology, alveolar bone parameters, occlusal relationship, etc. The hierarchical distributed storage module adopts a local + cloud-based drawer-style hierarchical architecture, including a hot data storage unit, a warm data storage unit, and a cold data storage unit. It also achieves dual backup across different locations and machines, adapting to the data storage needs of the entire chain from clinical practice to design and production in the dental field. The data management and traceability module assigns a unique identifier to each piece of oral data, establishes a hierarchical index library and an oral-specific multi-level permission system, and realizes full-chain traceability from oral data collection, processing, storage to clinical / production applications. The data interface and application service module provides a standardized API interface, supporting cross-platform integration with digital oral diagnosis and treatment platforms, oral AI design software, intelligent denture manufacturing systems, and oral teaching platforms, enabling on-demand retrieval and sharing of oral data.

2. The oral medical big data storage platform according to claim 1, characterized in that, In the hierarchical distributed storage module: The hot data storage unit is deployed in a local high-speed cache, prioritizing the storage of frequently accessed oral clinical diagnosis and treatment data and real-time production design data of dentures within one year. It uses a high-speed solid-state drive to achieve millisecond-level retrieval, adapting to the doctor's need for rapid retrieval during follow-up visits. The warm data storage unit is deployed on a general-purpose cloud storage node to store 1-5 years of regularly accessed oral history treatment and denture mass production data, balancing storage cost and oral data access speed. The cold data storage unit is deployed on a cloud disaster recovery node using the IPFS distributed cloud storage protocol. It stores low-frequency access but permanent oral archive data and scientific research and teaching data, ensuring that oral data is tamper-proof and meeting the compliance requirements for oral medical traceability.

3. The oral medical big data storage platform according to claim 1, characterized in that, The data processing and standardization module employs a two-layer desensitization process: the first layer removes sensitive information such as patient name, ID number, and mobile phone number and assigns a unique anonymous identifier to the platform; the second layer partially masks key information related to oral diagnosis and treatment while fully preserving core clinical data such as tooth position, symptoms, and treatment plans, balancing privacy protection with practical clinical use.

4. The oral medical big data storage platform according to claim 1, characterized in that, The data management and traceability module has a multi-level permission system corresponding to the role settings of the entire oral medical process, including dentists, dental technicians, oral R&D personnel, and platform administrators. Different roles can only access oral data within the authorized scope. Among them, dentists can only access the treatment-related data of the patients they have treated, and dental technicians can only access the denture design and production data of the corresponding production orders.

5. The data storage method of a dental medical big data storage platform according to any one of claims 1-4, characterized in that, Includes the following steps: S1: Standardized collection and access of multi-source heterogeneous oral data. It receives raw oral data in multiple formats from the oral clinical end, the denture design end, and the denture production end. After the oral data undergoes a dedicated accuracy verification, it is converted into a unified oral data standard format on the platform. S2: Oral data desensitization and feature processing provides double-layer privacy protection for the original oral data. At the same time, it uses the Mongolian oral feature extraction engine to extract core oral feature data such as tooth morphology, alveolar bone parameters, and occlusal relationship. The original full oral data and feature extraction data are stored separately to adapt to different needs of clinical diagnosis and treatment and denture development. S3: Oral data classification and coding indexing, which is divided into three levels according to oral data type, oral-specific usage scenario and access frequency. A unique standardized code is assigned to each piece of data and a multi-dimensional index is established. S4: Drawer-style hierarchical distributed storage and off-site disaster recovery automatically schedules the classified data to the corresponding storage unit. Related data of the same patient / denture production order / oral research project are grouped into oral data drawers, while completing off-site and off-machine dual backup to ensure the security of oral data storage. S5: Hierarchical index establishment and full-chain traceability. A hierarchical index library is established based on standardized coding. The entire life cycle of oral data is linked through a unique identifier, enabling full traceability of oral data from oral scanning and collection, data processing, denture design and modeling, 3D printing / cutting production, clinical diagnosis and treatment applications to postoperative follow-up. All operations are traceable. S6: Data security protection and dynamic scheduling. It adopts the AES-256 encryption algorithm to ensure the security of oral data storage and transmission. It controls oral data access through permission verification and has a built-in dynamic data scheduling engine to realize the automatic migration of oral data between different storage units and adapt to the changing needs of oral data access frequency.

6. The data storage method of a dental medical big data storage platform according to claim 5, characterized in that, The three-level classification in step S3 is as follows: According to data type, it is divided into oral clinical diagnosis and treatment data, oral medical imaging data, denture design and development data, denture production and processing data, and oral teaching and experimental data. Based on usage scenarios, they are divided into: real-time oral diagnosis and treatment, denture production and design, oral scientific research and development, and oral data archiving and traceability. Oral data is categorized by access frequency into oral thermal data, oral temperature data, and oral cold data.

7. The data storage method of a dental medical big data storage platform according to claim 5, characterized in that, The off-site disaster recovery strategy in step S4 is as follows: hot data is backed up twice on a local independent server to meet the emergency retrieval needs of dental clinics without network access; warm / cold data is backed up twice on cloud storage nodes to avoid the loss of dental archive data and research data.

8. The data storage method of a dental medical big data storage platform according to claim 5, characterized in that, The data dynamic scheduling rules for step S6 are as follows: If oral cold data is accessed 5 times within 30 days, it will be automatically migrated to the hot data storage unit; if oral hot data has not been accessed frequently for more than 1 year, it will be automatically migrated to the warm data storage unit to optimize the allocation of oral data storage resources.

9. The data storage method of a dental medical big data storage platform according to claim 5, characterized in that, The multi-source oral data in step S1 includes patient oral 3D scan data, CBCT imaging data, oral clinical diagnosis and treatment records, doctor's medical records, denture design documents, denture production and processing order data, and postoperative follow-up data.

10. The data storage method of a dental medical big data storage platform according to claim 5, characterized in that, The full-chain traceability in step S5 allows for one-click retrieval of the complete operation record of the corresponding oral data through a unique identifier, including data collection personnel, processing time, designers, production procedures, treating physicians, and operation content, thus meeting the requirements for compliance traceability and quality control in oral healthcare.

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