Hippocrates: An Open-Source Framework for Advancing Large Language Models in Healthcare

Check out the official documentation for more detail: https://cyberiada.github.io/Hippocrates/

Model Limitations. While our 7B model has achieved state-of-the-art results within its class, it is important to acknowledge its limitations compared to larger models such as OpenAI’s GPT4. The constraints imposed by the smaller parameter size may impede the model’s reasoning capabilities, a crucial aspect of complex medical decision-making. Additionally, the model’s performances are almost half on the average which highlights a huge area for improvement in open-source models.

Safety and Risks. Crucially, despite these advancements, it is important to highlight that these AI models need substantial improvements before they can be safely and effectively employed with real patients. They are not yet at a stage where they can provide medical advice or be utilized for commercial healthcare applications. This limitation highlights the need for ongoing, careful development and validation of AI systems to guarantee their reliability and safety in clinical settings. The path toward AI integration in patient care is still unfolding, and while it holds promise, it requires a methodical and thoroughly evaluated approach.

BibTex

@misc{acikgoz2024hippocrates,
title={Hippocrates: An Open-Source Framework for Advancing Large Language Models in Healthcare}, 
author={Emre Can Acikgoz and Osman Batur İnce and Rayene Bench and Arda Anıl Boz and İlker Kesen and Aykut Erdem and Erkut Erdem},
year={2024},
eprint={2404.16621},
archivePrefix={arXiv},
primaryClass={cs.LG}
}