A Complete Solution for Improving Diagnostic Medical Imaging Efficiency with HealthGPT
HealthGPT offers the following solutions to the problem of inefficient medical imaging diagnosis:
- Integrated Multi-Function Processing: Supports 7 comprehension tasks and 5 generation tasks, eliminating time lost switching between multiple specialized tools
- Utilizes advanced visual perception architectureLayered visual perception system can quickly recognize image features, saving more than 30% processing time compared to traditional methods.
- Use of standardized processing::
- Installation environment (conda create -n HealthGPT python=3.10)
- Download pre-training weights (ViT model + base model)
- Configure the inference script (modify the path parameter in com_infer.sh)
- Execute the batch quiz (bash com_infer.sh)
Two model configurations are available for different scenarios: HealthGPT-M3 for routine diagnosis and HealthGPT-L14 for complex cases. Clinical testing of the method has shown that it can reduce the time to analyze a single image from an average of 15 minutes to less than 3 minutes.
This answer comes from the articleHealthGPT: A Medical Big Model to Support Medical Image Analysis and Diagnostic Q&AThe
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