Erkang-Diagnosis-1.1 Technical Report
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | |
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| _version_ | 1866915692845989888 |
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| author | Ma, Jianbing Feng, Ao Gao, Zhenjie Song, Xinyu Su, Li Chen, Bin Wang, Wei Wu, Jiamin |
| author_facet | Ma, Jianbing Feng, Ao Gao, Zhenjie Song, Xinyu Su, Li Chen, Bin Wang, Wei Wu, Jiamin |
| contents | This report provides a detailed introduction to Erkang-Diagnosis-1.1 model, our AI healthcare consulting assistant developed using Alibaba Qwen-3 model. The Erkang model integrates approximately 500GB of high-quality structured medical knowledge, employing a hybrid approach combining enhanced pre-training and retrieval-enhanced generation to create a secure, reliable, and professional AI health advisor. Through 3-5 efficient interaction rounds, Erkang Diagnosis can accurately understand user symptoms, conduct preliminary analysis, and provide valuable diagnostic suggestions and health guidance. Designed to become users intelligent health companions, it empowers primary healthcare and health management. To validate, Erkang-Diagnosis-1.1 leads GPT-4 in terms of comprehensive medical exams. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_20632 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Erkang-Diagnosis-1.1 Technical Report Ma, Jianbing Feng, Ao Gao, Zhenjie Song, Xinyu Su, Li Chen, Bin Wang, Wei Wu, Jiamin Artificial Intelligence This report provides a detailed introduction to Erkang-Diagnosis-1.1 model, our AI healthcare consulting assistant developed using Alibaba Qwen-3 model. The Erkang model integrates approximately 500GB of high-quality structured medical knowledge, employing a hybrid approach combining enhanced pre-training and retrieval-enhanced generation to create a secure, reliable, and professional AI health advisor. Through 3-5 efficient interaction rounds, Erkang Diagnosis can accurately understand user symptoms, conduct preliminary analysis, and provide valuable diagnostic suggestions and health guidance. Designed to become users intelligent health companions, it empowers primary healthcare and health management. To validate, Erkang-Diagnosis-1.1 leads GPT-4 in terms of comprehensive medical exams. |
| title | Erkang-Diagnosis-1.1 Technical Report |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2512.20632 |