
Clinical Panda
This project developed a large language model (LLM) to generate explanations for diagnoses based on patient interactions and aimed to improve model robustness with real-world data.
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This project developed a large language model (LLM) to generate explanations for diagnoses based on patient interactions and aimed to improve model robustness with real-world data.
This project focused on enhancing data privacy with advanced masking techniques for LLMs and involved curating a specialized dataset for model optimization.
This project built a multi-modal LLM specifically for the medical field by combining different data types and employed distributed training for efficiency.
This project created a novel method to explain visual outputs of convolutional neural networks and validated its effectiveness compared to existing techniques.
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