A Multi-centric Clinical Trial in China for Skin Diseases Intelligent Diagnosis and Treatment System
Study Details
Study Description
Brief Summary
In response to clinical needs, infrared multi-spectral images are combined with traditional clinical images and other multi-modal data to build a more efficient intelligent auxiliary diagnosis system and intelligent equipment for skin health and diseases.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
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N/A |
Detailed Description
Database: Relying on the preliminary foundation, build the first standardized infrared multispectral image database of skin diseases, and further integrate other medical images and medical history texts to iterate into a large multimodal skin disease database.
Model: Design a deep learning network based on multi-scale and multi-level. The collaborative attention learning network realizes the collaborative representation of multi-modal data at the feature level, builds a multi-modal skin disease auxiliary diagnosis model, and realizes breakthroughs in algorithms.
System: proposes a hybrid learning framework under the condition of sample imbalance, and develops a hybrid multi modal auxiliary diagnosis system enhances the ability to diagnose small samples of diseases; establishes an incremental learning system under the condition of adding new samples, develops an incremental multi-modal auxiliary diagnosis system, and realizes accurate diagnosis of newly added samples. Equipment: Based on the self-developed high-performance system, construct and assemble infrared multi-spectral skin disease auxiliary diagnosis equipment.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Experimental: Digital camera A Real-time Augmented Reality Device with Artificial Intelligence Integration, acquisition of patient skin lesion images as data |
Device: A Real-time Augmented Reality Device with Artificial Intelligence Integration
Patients are diagnosed and treated with the assistance of artificial intelligence, augmented reality and new optical imaging technology, which is different from traditional model.
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Outcome Measures
Primary Outcome Measures
- Diagnosis accuracy [up to 12 months]
Comparing AI with human diagnosis accuracy
- Dermatology Life Quality Index(DLQI) [up to 12 months]
The evaluation of prognosis, the minimum values 0 and the maximum values 30, and a higher score mean a worse outcome.
Eligibility Criteria
Criteria
Inclusion Criteria:
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Informed consented.
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With a diagnosis of skin disease made by at least 3 dermatologists.
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Without life-threatening risk to intervention.
Exclusion Criteria:
- Having difficulties to follow-up.
Contacts and Locations
Locations
No locations specified.Sponsors and Collaborators
- Xiangya Hospital of Central South University
Investigators
None specified.Study Documents (Full-Text)
None provided.More Information
Publications
None provided.- XiangyaH001