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Medical record document identification
Structured identification of medical record related documents involved in the insurance claim scenario, including 7 common documents such as medical record homepage, discharge summary, admission summary, outpatient medical record, diagnosis certificate, prescription note and surgical record, is applied to the intelligent claim underwriting scenario to effectively reduce the cost of labor review and improve the efficiency of business processing
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Technical Documentation
Product List
Application scenarios
Characteristic advantages
Usage
Support communication
Related recommendations
Product List
Identification of the first page of medical record
Identify the home page of medical records across the country, including 15 key fields such as name, ID card number, admission/admission department, and number of hospitalizations
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Discharge summary identification
Key fields such as department, name, date of discharge/admission, diagnosis of discharge/admission, and discharge doctor's order can be identified in the national discharge summary
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Admission summary identification
It can identify admission summary of each format, including name, admission time, current medical history, past history and other key field information
Technical Documentation
Outpatient medical record recognition
Identify outpatient medical records of hospitals nationwide and return key fields such as name, diagnosis, examination, chief complaint and current medical history
Technical Documentation
Identification of diagnosis certificate
Structurally identify 9 key fields of various diagnosis certificates, including name, admission/discharge time, discharge diagnosis, etc
Technical Documentation
Prescription label identification
It supports the identification of key fields such as name, department, and prescription item information in various formats of prescription notes
Technical Documentation
Surgical record recognition
Structurally identify the operation records of hospitals nationwide, and return the fields such as name, department, operation date, operation name, etc
Technical Documentation
Application scenarios
Intelligent claim settlement
Health label management
Intelligent claim settlement
Based on the identification technology of medical record related documents such as medical record home page, discharge summary, outpatient medical record, automatically identify the patient's medical information and personal information, help claim settlement staff quickly confirm the insured's information, reimbursable payments and amounts, effectively reduce the cost of manual review, and improve the efficiency of business processing
Cooperation cases
Taikang Insurance
Characteristic advantages
Wide coverage
Covering various formats of medical record documents issued by different provinces, cities, regions and medical systems across the country, to meet the global application needs
High accuracy
Special optimization was carried out for common overlapping words, seal blocking, printing offset and other situations in medical record related documents, with high recognition accuracy
Usage
Public cloud service
Provide various cloud PaaS interfaces for text recognition. You can directly call the API or use the HTTP SDK to identify the text in the picture. You can go to the console to try it for free
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API documentation
Privatization deployment
Deploy to the local server, realize the character recognition function in the LAN/intranet, without connecting to the public network, ensure data privacy, and provide two privatization schemes of all-in-one machine and software deployment package
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Scheme introduction
Support communication
Novice Guide
Basic introduction of access to AI services, including account authentication, application creation and management, authentication mechanism, FAQs, etc
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Technical Documentation
For developers using API or HTTP SDK, provide development documents of Baidu character recognition service
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SDK download
Support multiple programming languages such as Android, iOS, Java, PHP, Python, C++, C #, Node.js
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Support the identification of key fields such as name, date, patient ID, and total amount of national medical expense details, and support the identification of expense detailed item list
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