A data source management and processing system for a medical cognitive intelligent scientific research platform

Abstract

The present invention discloses a data source management and processing system for a medical cognitive intelligent scientific research platform, which relates to the technical field of medical scientific research platforms, and includes a client, a character recognition module and a data management module. The output end of the client is connected to a data extraction module, and the character recognition module is connected to the output end of the data extraction module. The character recognition module includes a language editing analyzer, an abnormal prompt module, a translation module and an upload module. The present invention uses a data extraction module to read data from different sources and uniformly converts them into specified characters and texts, and uses a character recognition module to identify and translate texts, and uses a data storage cloud to encrypt and classify texts, which can ensure that the system can normalize multi-source heterogeneous data sources. At the same time, through normalization processing, it can effectively ensure that users can quickly and accurately query corresponding data when querying related data.

Description

Technical Field

[0001] The present invention relates to the technical field of medical scientific research platforms, and in particular to a data source management and processing system for a medical cognitive intelligent scientific research platform. Background Art

[0002] A medical research platform is a network platform where multiple hospitals or pharmaceutical companies upload real medical data to the cloud for medical research and clinical treatment learning. The use of the medical research platform can greatly reduce the difficulty of treating difficult and complicated diseases. At the same time, by uploading medical data, the content depth of the medical research platform can be further expanded, providing further convenience for medical staff.

[0003] The content uploaded by common medical research platforms on the market is usually messy, and it is usually impossible to normalize multi-source heterogeneous data sources. When medical staff need to query relevant information, it is usually difficult to quickly find the corresponding information. Summary of the invention

[0004] The purpose of the present invention is to provide a data source management and processing system for a medical cognitive intelligent scientific research platform to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a data source management and processing system of a medical cognitive intelligent scientific research platform, comprising a client, a character recognition module and a data management module, wherein the output end of the client is connected to a data extraction module, the character recognition module is connected to the output end of the data extraction module, the character recognition module comprises a language editing analyzer, an abnormal prompt module, a translation module and an upload module, one output end of the language editing analyzer is connected to the abnormal prompt module, and the other output end of the language editing analyzer is connected to the translation module, the output end of the translation module is connected to the upload module, the output end of the character recognition module is connected to a data storage cloud, the data management module is placed at the input end of the data storage cloud, and the output end of the data storage cloud is connected to a data reading module.

[0006] Furthermore, the data extraction module includes an optical spectrum scanner, a photo scanner, a character reading module, an intelligent comparison and recognition module and a character generation module.

[0007] Furthermore, the output ends of the optical spectrum scanner and the photo scanner are connected to a character reading module, and the output end of the character reading module is connected to an intelligent comparison and recognition module, and the output end of the intelligent comparison and recognition module is connected to a character generation module.

[0008] Furthermore, the character reading module is used to read character data scanned by the optical spectrum scanner and the photo scanner, and the intelligent comparison and recognition module is used to compare the characters scanned by the optical spectrum scanner and the photo scanner.

[0009] Furthermore, the language editing and analyzing unit is used to identify the text content of characters, and the translation module is used to convert the text language of characters.

[0010] Furthermore, the data storage cloud includes an encryption compression module, a prefix generation module, a prefix reading module, an intelligent classification module, a cloud storage and a log generation module. The output end of the encryption compression module is connected to the prefix generation module, and the output end of the prefix generation module is connected to the prefix reading module, the output end of the prefix reading module is connected to the intelligent classification module, and the output end of the intelligent classification module is connected to the cloud storage, and the other output ends of the prefix generation module and the intelligent classification module are connected to the log generation module.

[0011] Furthermore, the log generation module is electrically connected in parallel with the prefix generation module and the intelligent classification module, and the log generation module is used to generate processing data of the prefix generation module and the intelligent classification module.

[0012] Furthermore, the data management module includes a data monitoring module, a data transfer module and a data updating module. One output end of the data monitoring module is connected to the data transfer module, and the other output end of the data monitoring module is connected to the data updating module.

[0013] Furthermore, the data monitoring module is electrically connected in parallel with the language editing analyzer, and the data monitoring module is electrically connected in parallel with the log generating module.

[0014] Furthermore, the data transfer module is used to transfer expired data, and the data update module is used to update data content in the data storage cloud.

[0015] The present invention provides a data source management and processing system for a medical cognitive intelligent scientific research platform, which has the following beneficial effects: after scanning character images, the optical spectrum scanner and the photo scanner can upload the obtained characters and images to the character reading module, and the character reading module can upload the two read characters and images to the intelligent comparison and recognition module. After obtaining the characters scanned by the optical spectrum scanner and the photo scanner, the intelligent comparison and recognition module can compare the two texts. Through text comparison, the deviation in the two scanned texts can be checked, and then the intelligent comparison and recognition module can intelligently identify the text with deviations and replace it with the correct characters. By using two different types of scanners for text comparison at the same time, the text scanning error caused by external factors can be greatly reduced. The data extraction module reads data from different sources and uniformly converts them into specified characters and texts, and the character recognition module is used to identify and translate the texts, and the data storage cloud is used to encrypt and classify the texts, which can ensure that the system can normalize multi-source heterogeneous data sources. At the same time, through normalization, it can effectively ensure that users can quickly and accurately query corresponding data when querying related data.

[0016] 1. After receiving the source file, the data extraction module of the present invention can distribute and transfer the data to the optical spectrum scanner and the photo scanner for scanning and reading the character images. After scanning the character images, the optical spectrum scanner and the photo scanner can upload the obtained characters and images to the character reading module. The character reading module can upload the two read characters and images to the intelligent comparison and recognition module. After obtaining the characters scanned by the optical spectrum scanner and the photo scanner, the intelligent comparison and recognition module can compare the two texts. Through text comparison, the deviation in the two scanned texts can be checked, and then the intelligent comparison and recognition module can intelligently identify the text with deviations and replace it with the correct characters. By using two different types of scanners for text comparison at the same time, the text scanning error caused by external factors can be greatly reduced. In addition, through the comparison and recognition of the intelligent comparison and recognition module, the erroneous text can be quickly found and replaced, which can greatly improve the content accuracy of the uploaded data.

[0017] 2. The language editor analyzer of the present invention can identify text content. Through the content identification of the language editor analyzer, the specific content of the information in the text can be known. In addition, if the language editor analyzer finds any illegal content during the text reading process, it will stop subsequent text operations and delete the document. At the same time, the language editor analyzer can also remind the client through the abnormal prompt module that the content in the text is illegal and cannot be uploaded. This can effectively ensure the authority and text quality of the medical information in the medical research platform. In addition, after the language editor analyzer completes the reading of the text data, it can also automatically convert the text content into the text of the area where the current server of the system is located through the translation module. This can ensure that the content of all the information in the medical research platform can be provided to medical staff for reference without obstacles, which can effectively reduce the difficulty of text reference.

[0018] 3. During the process of encrypting and compressing text, the encryption and compression module of the present invention can read the data reading record from the language editing and analyzing device, so that the encryption and compression module can know the specific content of the text. After the text compression is completed, the encryption and compression module can upload the compressed file and the content information of the file to the prefix generation module. The prefix generation module can generate a data code that can only be read by the system in the name of the compressed package according to the content information of the text. After the prefix reading module reads the generated data code, the intelligent classification module can automatically upload the compressed package to the designated folder in the cloud storage for storage according to the content recognized by the prefix reading module. This can ensure that the files can be stored in a regular and orderly manner. At the same time, by storing the compressed package in the form of data code names, the occurrence of illegal retrieval and theft of data in the medical research platform can be effectively reduced.

[0019] 4. During the storage of the document of the present invention in the cloud storage, the data monitoring module can monitor the storage information of the cloud storage in real time by reading the content recorded by the log generation module. When the data monitoring module detects that there is a compressed package in the cloud storage that has not been used for more than three years, the data monitoring module can communicate with the client that uploaded the file at that time, and transfer the file to the client for storage through the data transfer module. This can not only ensure that expired data is not lost, but also reduce the pressure on the system during the retrieval process. In addition, when the same client uploads updated and iterative medical data, the data update module can replace the old data with the new medical data, and transmit the old data back to the client through the data transfer module. This can avoid useless data remaining in the cloud storage and affecting the storage capacity of the cloud storage.

[0020] 5. The present invention uses a data extraction module to read data from different sources and uniformly convert them into specified characters and texts, and uses a character recognition module to identify and translate texts, as well as encrypting and classifying texts through data storage in the cloud. This ensures that the system can normalize multi-source heterogeneous data sources. At the same time, through normalization, it can effectively ensure that users can quickly and accurately query corresponding data when querying related data. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a schematic diagram of the overall process of a data source management and processing system of a medical cognitive intelligent scientific research platform of the present invention;

[0022] Figure 2 A schematic diagram of the workflow of a data extraction module of a data source management and processing system of a medical cognitive intelligent scientific research platform of the present invention;

[0023] Figure 3 A schematic diagram of the workflow of a character recognition module of a data source management and processing system of a medical cognitive intelligent scientific research platform of the present invention;

[0024] Figure 4 A schematic diagram of a workflow of a data storage cloud of a data source management and processing system of a medical cognitive intelligent scientific research platform of the present invention;

[0025] Figure 5 This is a schematic diagram of the workflow of the data management module of the data source management and processing system of the medical cognitive intelligent scientific research platform of the present invention.

[0026] In the figure: 1. Client; 2. Data extraction module; 201. Optical spectrum scanner; 202. Photo scanner; 203. Character reading module; 204. Intelligent comparison and recognition module; 205. Character generation module; 3. Character recognition module; 301. Language editing and analyzing device; 302. Abnormal prompt module; 303. Translation module; 304. Upload module; 4. Data storage in the cloud; 401. Encryption and compression module; 402. Prefix generation module; 403. Prefix reading module; 404. Intelligent classification module; 405. Cloud storage; 406. Log generation module; 5. Data management module; 501. Data monitoring module; 502. Data transfer module; 503. Data update module; 6. Data reading module. DETAILED DESCRIPTION

[0027] See also Figure 1-5The present invention provides a technical solution: a data source management and processing system of a medical cognitive intelligent scientific research platform, comprising a client 1, a character recognition module 3 and a data management module 5, wherein the output end of the client 1 is connected to the data extraction module 2, the character recognition module 3 is connected to the output end of the data extraction module 2, the character recognition module 3 comprises a language editing analyzer 301, an abnormal prompt module 302, a translation module 303 and an upload module 304, an output end of the language editing analyzer 301 is connected to the abnormal prompt module 302, and another output end of the language editing analyzer 301 is connected to the translation module 303, the output end of the translation module 303 is connected to the upload module 304, the output end of the character recognition module 3 is connected to the data storage cloud 4, the data management module 5 is arranged at the input end of the data storage cloud 4, and the output end of the data storage cloud 4 is connected to the data reading module 6.

[0028] See also Figure 1-3 The data extraction module 2 includes an optical spectrum scanner 201, a photo scanner 202, a character reading module 203, an intelligent comparison and recognition module 204 and a character generation module 205. The output ends of the optical spectrum scanner 201 and the photo scanner 202 are connected to the character reading module 203, and the output end of the character reading module 203 is connected to the intelligent comparison and recognition module 204. The output end of the intelligent comparison and recognition module 204 is connected to the character generation module 205. The character reading module 203 is used to read the character data scanned by the optical spectrum scanner 201 and the photo scanner 202. The intelligent comparison and recognition module 204 is used to compare the characters scanned by the optical spectrum scanner 201 and the photo scanner 202. The language editing and analyzing device 301 is used to identify the text content of the characters. The translation module 303 is used to convert the text language of the characters.

[0029] The specific operation is as follows: after the uploader at the client 1 takes a photo of the paper document and uploads it to the system, the system can pass the photo to the data extraction module 2. After receiving the source file, the data extraction module 2 can pass the document to the optical spectrum scanner 201 and the photo scanner 202 for scanning and reading the character image. After the optical spectrum scanner 201 and the photo scanner 202 have finished scanning the character image, they can upload the obtained characters and images to the character reading module 203. The character reading module 203 can upload the two copies of the read characters and images to the intelligent comparison and recognition module 204. The intelligent comparison and recognition module 204 obtains the optical spectrum scanning. After the characters scanned by the scanner 201 and the photo scanner 202 are scanned, the two texts can be compared. Through text comparison, the deviation in the two scanned texts can be checked, and then the intelligent comparison and recognition module 204 can intelligently recognize the text with deviation and replace it with the correct character. By using two different types of scanners for text comparison at the same time, the text scanning error caused by external factors can be greatly reduced. In addition, through the comparison and recognition of the intelligent comparison and recognition module 204, the error text can be quickly found and replaced, which can greatly improve the accuracy of the content of the uploaded data. After the intelligent comparison and recognition module 204 completes the character comparison and replacement, the character generation module 205 can The characters and pictures on the client end are converted into text that conforms to the text used by the medical research platform, and the text is uploaded to the character recognition module 3. After the character recognition module 3 obtains the text from the character generation module 205, the language editing analyzer 301 can perform content recognition on the text. Through the content recognition of the language editing analyzer 301, the specific content of the information in the text can be known. In addition, if the language editing analyzer 301 finds illegal content (illegal drugs, false propaganda, etc.) during the text reading process, it will stop subsequent text operations and delete the document. At the same time, the language editing analyzer 301 can also remind the client 1 that the content in the text is illegal through the abnormal prompt module 302. , cannot be uploaded, which can effectively ensure the authority and text quality of the medical information in the medical research platform. In addition, after the language editing and analyzing device 301 completes the reading of the text information, it can also automatically convert the text content into the text of the area where the current server of the system is located through the translation module 303. This can ensure that the content of all the information in the medical research platform can be provided to medical staff for barrier-free reference, which can effectively reduce the difficulty of text reference. When the upload module 304 uploads the processed text to the data storage cloud 4, the untranslated text can also be uploaded together. When the reference has questions about the translation, the reference can refer to the original paragraph for comparison, so as to improve the text reference experience.

[0030] See also Figure 1 , Figure 4 and Figure 5The data storage cloud 4 includes an encryption compression module 401, a prefix generation module 402, a prefix reading module 403, an intelligent classification module 404, a cloud storage 405 and a log generation module 406. The output end of the encryption compression module 401 is connected to the prefix generation module 402, and the output end of the prefix generation module 402 is connected to the prefix reading module 403. The output end of the prefix reading module 403 is connected to the intelligent classification module 404, and the output end of the intelligent classification module 404 is connected to the cloud storage 405. The other output ends of the prefix generation module 402 and the intelligent classification module 404 are connected to the log generation module 406. The log generation module 406 is connected to the prefix generation module 402 and the intelligent classification module 404. The data management module 5 includes a data monitoring module 501, a data transfer module 502 and a data update module 503. One output end of the data monitoring module 501 is connected to the data transfer module 502, and the other output end of the data monitoring module 501 is connected to the data update module 503. The data monitoring module 501 is electrically connected in parallel with the language editing analyzer 301, and the data monitoring module 501 is electrically connected in parallel with the log generation module 406. The data transfer module 502 is used to transfer expired data, and the data update module 503 is used to update the data content of the data storage cloud 4.

[0031] The specific operation is as follows. After the text is uploaded to the data storage cloud 4, the encryption and compression module 401 can encrypt and compress the text. During the process of encrypting and compressing the text, the encryption and compression module 401 can read the data reading record from the language editing analyzer 301, so that the encryption and compression module 401 can know the specific content of the text. After the text compression is completed, the encryption and compression module 401 can upload the compressed file and the content information of the file to the prefix generation module 402. The prefix generation module 402 can generate a data code that can only be read by the system in the name of the compressed package according to the content information of the text. After the prefix reading module 403 reads the generated data code, the intelligent classification module 404 can automatically upload the compressed package to the specified folder in the cloud storage 405 for storage according to the content recognized by the prefix reading module 403. This can ensure that the file can be stored in a regular and orderly manner. At the same time, by storing the compressed package in the form of a data code name, the occurrence of illegal retrieval and theft of data in the medical research platform can be effectively reduced. The prefix generation module 402 and the intelligent classification module 404 are working. The operation records in the process will be recorded by the log generation module 406, and when the document is stored in the cloud storage 405, the data monitoring module 501 can monitor the storage information of the cloud storage 405 in real time by reading the content recorded by the log generation module 406. When the data monitoring module 501 detects that there is a compressed package in the cloud storage 405 that has not been used for more than three years, the data monitoring module 501 can communicate with the client 1 that uploaded it at that time, and transfer the file to the client 1 for storage through the data transfer module 502, which can not only ensure that the expired data is not lost, but also reduce the pressure of the system during the retrieval process. In addition, when the same client 1 uploads updated and iterated medical data, the data update module 503 can replace the previous old data with the new medical data, and transmit the old data back to the client 1 through the data transfer module 502, which can avoid useless data from being retained in the cloud storage 405 and affecting the storage capacity of the cloud storage 405. When the user uses the data reading module 6 to refer to the text, he only needs to search according to the keyword, and the system can retrieve the text that meets the requirements for the user's reference based on the keyword.

[0032] In summary, when the data source management and processing system of the medical cognitive intelligent scientific research platform is used, first, the uploader at the client 1 takes a photo of the paper document and uploads it to the system, and the system can pass the photo to the data extraction module 2. After receiving the source file, the data extraction module 2 can distribute and pass the document to the optical spectrum scanner 201 and the photo scanner 202 for scanning and reading the character image. After the optical spectrum scanner 201 and the photo scanner 202 complete scanning the character image, they can upload the obtained characters and images to the character reading module 203.

[0033] Then the character reading module 203 can upload the two characters and pictures read to the intelligent comparison and recognition module 204. After obtaining the characters scanned by the optical spectrum scanner 201 and the photo scanner 202, the intelligent comparison and recognition module 204 can compare the two texts. Through text comparison, the deviation in the two scanned texts can be checked. Then the intelligent comparison and recognition module 204 can intelligently recognize the text with deviation and replace it with the correct character. By using two different types of scanners for text comparison at the same time, the text scanning error caused by external factors can be greatly reduced. In addition, through the comparison and recognition of the intelligent comparison and recognition module 204, the error text can be quickly found and replaced, which can greatly improve the content accuracy of the uploaded data;

[0034] Then, after the intelligent comparison and recognition module 204 completes the character comparison and replacement, the character generation module 205 can convert the characters and pictures on the terminal into texts that meet the requirements of the medical research platform, and upload the texts to the character recognition module 3. After the character recognition module 3 obtains the texts from the character generation module 205, the language editing and analyzing device 301 can perform content recognition on the text. Through the content recognition of the language editing and analyzing device 301, the specific content of the information in the text can be known. In addition, if the language editing and analyzing device 301 finds any illegal content during the text reading process, it will stop the subsequent text operations and delete the document. At the same time, the language editing and analyzing device 301 can also remind the client 1 through the abnormal prompt module 302 that the content in the text is illegal and cannot be uploaded. This can effectively ensure the authority and text quality of the medical information in the medical research platform.

[0035] After the language editing and analyzing device 301 finishes reading the text data, the translation module 303 can also automatically convert the text content into the language of the region where the current server of the system is located. This can ensure that the content of all the data in the medical research platform can be easily referenced by medical staff, which can effectively reduce the difficulty of text reference. When the upload module 304 uploads the processed text to the data storage cloud 4, the untranslated text can also be uploaded together. When the reader has questions about the translation, he can compare the questionable paragraphs with the original version, so as to improve the text reference experience;

[0036] After the text is uploaded to the data storage cloud 4, the encryption and compression module 401 can encrypt and compress the text. During the encryption and compression of the text, the encryption and compression module 401 can read the data reading record from the language editing analyzer 301, so that the encryption and compression module 401 can know the specific content of the text. After the text compression is completed, the encryption and compression module 401 can upload the compressed file and the content information of the file to the prefix generation module 402. The prefix generation module 402 can generate a data code that can only be read by the system in the name of the compressed package according to the content information of the text. After the prefix reading module 403 reads the generated data code, the intelligent classification module 404 can automatically upload the compressed package to the specified folder in the cloud storage 405 for storage according to the content recognized by the prefix reading module 403. This can ensure that the file can be stored in a regular and orderly manner. At the same time, by storing the compressed package in the form of a data code name, the occurrence of illegal retrieval and theft of data in the medical research platform can be effectively reduced. The operation records of the prefix generation module 402 and the intelligent classification module 404 during the working process will be recorded by the log generation module 406;

[0037] During the storage of the final document in the cloud storage 405, the data monitoring module 501 can monitor the storage information of the cloud storage 405 in real time by reading the content recorded by the log generation module 406. When the data monitoring module 501 detects that there is a compressed package in the cloud storage 405 that has not been used for more than three years, the data monitoring module 501 can communicate with the client 1 that uploaded it at that time, and transfer the file to the client 1 for storage through the data transfer module 502. This can not only ensure that the expired data is not lost, but also reduce the pressure of the system during the retrieval process. In addition, when the same client 1 uploads updated and iterative medical data, the data update module 503 can replace the previous old data with the new medical data, and transmit the old data back to the client 1 through the data transfer module 502. This can avoid useless data from being retained in the cloud storage 405 and affecting the storage capacity of the cloud storage 405. When the user uses the data reading module 6 to refer to the text, he only needs to search according to the keywords, and the system can retrieve the text that meets the requirements for the user's reference based on the keywords.

Claims

1. A data source management and processing system for a medical cognitive intelligent scientific research platform, characterized in that: The invention comprises a client (1), a character recognition module (3) and a data management module (5), wherein the output end of the client (1) is connected to a data extraction module (2), the character recognition module (3) is connected to the output end of the data extraction module (2), the character recognition module (3) comprises a language editing analyzer (301), an abnormality prompt module (302), a translation module (303) and an upload module (304), one output end of the language editing analyzer (301) is connected to the abnormality prompt module (302), and the other output end of the language editing analyzer (301) is connected to the translation module (303), the output end of the translation module (303) is connected to the upload module (304), the output end of the character recognition module (3) is connected to a data storage cloud (4), the data management module (5) is arranged at the input end of the data storage cloud (4), and the output end of the data storage cloud (4) is connected to a data reading module (6); The data storage cloud (4) comprises an encryption compression module (401), a prefix generation module (402), a prefix reading module (403), an intelligent classification module (404), a cloud storage (405) and a log generation module (406); the output end of the encryption compression module (401) is connected to the prefix generation module (402), the output end of the prefix generation module (402) is connected to the prefix reading module (403), the output end of the prefix reading module (403) is connected to the intelligent classification module (404), the output end of the intelligent classification module (404) is connected to the cloud storage (405), and the other output ends of the prefix generation module (402) and the intelligent classification module (404) are connected to the log generation module (406); The data management module (5) comprises a data monitoring module (501), a data transfer module (502) and a data updating module (503); one output end of the data monitoring module (501) is connected to the data transfer module (502), and the other output end of the data monitoring module (501) is connected to the data updating module (503); The data extraction module (2) comprises an optical spectrum scanner (201), a photo scanner (202), a character reading module (203), an intelligent comparison and recognition module (204) and a character generation module (205); The output ends of the optical spectrum scanner (201) and the photo scanner (202) are connected to a character reading module (203), and the output end of the character reading module (203) is connected to an intelligent comparison and recognition module (204), and the output end of the intelligent comparison and recognition module (204) is connected to a character generation module (205); The character reading module (203) is used to read character data scanned by the optical spectrum scanner (201) and the photo scanner (202), and the intelligent comparison and recognition module (204) is used to compare the characters scanned by the optical spectrum scanner (201) and the photo scanner (202); After the uploader at the client (1) takes a photo of the paper document and uploads it to the system, the system can transfer the photo to the data extraction module (2). After receiving the source file, the data extraction module (2) can transfer the document to the optical spectrum scanner (201) and the photo scanner (202) for scanning and reading the character image. After scanning the character image, the optical spectrum scanner (201) and the photo scanner (202) can upload the obtained characters and images to the character reading module (203). The character reading module (203) can upload the two read characters and images to the intelligent comparison and recognition module (204). After obtaining the characters scanned by the optical spectrum scanner (201) and the photo scanner (202), the intelligent comparison and recognition module (204) compares the two texts. Through text comparison, the deviation in the two scanned texts is detected. Then, the intelligent comparison and recognition module (204) intelligently recognizes the text with deviation and replaces it with the correct character. After the text is uploaded to the data storage cloud (4), the encryption and compression module (401) encrypts and compresses the text. During the encryption and compression process, the encryption and compression module (401) reads the data reading record from the language editing and analyzing device (301). After the text compression is completed, the encryption and compression module (401) uploads the compressed file and the content information of the file to the prefix generation module (402). The prefix generation module (402) generates a data code that can only be read by the system in the name of the compressed package according to the content information of the text. After the prefix reading module (403) reads the generated data code, the intelligent classification module (404) automatically uploads the compressed package to a designated folder in the cloud storage (405) for storage according to the content recognized by the prefix reading module (403). The operation records of the prefix generation module (402) and the intelligent classification module (404) during the working process will be recorded by the log generation module (406), and when the document is stored in the cloud storage (405), the data monitoring module (501) monitors the storage information of the cloud storage (405) in real time by reading the content recorded by the log generation module (406). When the data monitoring module (501) detects that there is a compressed package in the cloud storage (405) that has not been used for more than three years, the data monitoring module (501) communicates with the client (1) that uploaded the file at that time, and transfers the file to the client (1) for storage through the data transfer module (502).

2. According to claim 1, a data source management and processing system for a medical cognitive intelligent scientific research platform is characterized in that: The language editing and analyzing unit (301) is used to identify the text content of characters, and the translation module (303) is used to convert the text language of characters.

3. According to claim 1, a data source management and processing system for a medical cognitive intelligent scientific research platform is characterized in that: The log generation module (406) is electrically connected in parallel with the prefix generation module (402) and the intelligent classification module (404), and the log generation module (406) is used to generate processing data of the prefix generation module (402) and the intelligent classification module (404).

4. According to claim 1, a data source management and processing system for a medical cognitive intelligent scientific research platform is characterized in that: The data monitoring module (501) is electrically connected in parallel with the language editing analyzer (301), and the data monitoring module (501) is electrically connected in parallel with the log generating module (406).

5. According to claim 4, a data source management and processing system for a medical cognitive intelligent scientific research platform is characterized in that: The data transfer module (502) is used to transfer expired data, and the data update module (503) is used to update the data content of the data storage cloud (4).

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