AI-POWERED INSIGHTS
Research on Intelligent Image Feature Accurate Recognition Technology
Executive Summary
This study addresses the challenges in medical insurance claims, such as inconsistent image quality, diverse formats, and low recognition efficiency of medical documents. It proposes a solution based on intelligent image feature recognition technology. The study focuses on the core methodology, key technical indicators, and practical application outcomes of this technology. By designing four components-image preprocessing, document classification, OCR text recognition, and structural analysis-and utilizing deep learning algorithms and multimodal technologies, the system automates the extraction and verification of key texts, table structures, and anti-counterfeiting features of seals in medical invoices and diagnostic certificates. Experimental results show that This technology can support the scenarios of rapid settlement of outpatient expenses, intelligent audit of hospitalization expenses, and immediate settlement of medical treatment across regions, promote the transformation of medical insurance services to intelligence and precision, and provide key technical support for the construction of efficient medical insurance ecology.
0
Claims Processed < 5 min
0
Reduction in Manual Review Costs
0
Financial Sharing Efficiency Increase
0
Day Claim Settlement Cycle
Deep Analysis & Enterprise Applications
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98.7%
Overall Recognition Precision
Enterprise Process Flow
Image Preprocessing
→
Bill Classification
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OCR Text Recognition
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Structural Analysis
| Feature | Traditional Methods | Deep Learning Methods |
|---|---|---|
| Core Methodology |
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| Accuracy & Generalization |
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| Adaptability to Documents |
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Automated Outpatient Expense Settlement
Patients can upload medical bills via app, and the system automatically extracts key information like patient name, visit time, costs, and total amount. This info is then compared with the medical insurance directory to calculate the reimbursable amount. This enables identification in minutes, reduces manual errors, and improves patient satisfaction.
Intelligent Hospitalization Expense Audit
The system analyzes inpatient settlement statements and expense lists, calculating reimbursement based on policies (deductible, ratio) and marking abnormal expenses. This leads to automated detection of illegal expenses (e.g., fraud), reduced loss of medical insurance funds, and uniform policy implementation.
Seamless Cross-Regional Medical Treatment
For cross-province medical treatment, the model analyzes uploaded invoices, converts them to a standardized format, verifies patient identity and insurance status in real-time. This means patients don't pay expenses in advance or return for reimbursement, reducing economic pressure.
70%
Reduced Manual Review Costs
110%
Increased Financial Sharing Efficiency
| Stakeholder | AI-Powered Solution Benefits |
|---|---|
| Patients |
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| Insurance Providers |
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| Overall Healthcare Ecosystem |
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Annual Savings
$0
Hours Reclaimed Annually
0
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