M42 Introduces Med42: An Open-Access Clinical Large Language Model (LLM) to Expand Access to Medical Knowledge

M42 Health, based in Abu Dhabi, UAE, has just published Med42, a promising new open-access clinical large language model. The release of this 70 billion parameter model is a watershed moment in the effort to increase public access to advanced AI capabilities that can revolutionize healthcare.

Med42, fine-tuned from Meta’s Llama-2 – 70B model, outperforms its predecessors in open-source medical AI by a wide margin. The model surpasses OpenAI’s ChatGPT 3.5 across many medical question-answering datasets, achieving up to 72% accuracy in a zero-shot evaluation on the USMLE. This demonstrates Med42’s ability to help with clinical decision-making by giving doctors easy access to medical knowledge that has been synthesized.

The M42 Health AI team built Med42 using their massive, human-curated medical literature and patient information dataset. M42, Cerebras, and Core42 (an M42 subsidiary) worked together to fine-tune the Condor Galaxy 1 supercomputer. The model’s efficacy was also assessed by experts at the Mohamed bin Zayed University for Artificial Intelligence (MBZUAI).

M42’s Med42 is a free, publicly available clinical large language model (LLM) created to make more medical information open to the public. Based on LLaMA-2 and has 70 billion parameters, this generative AI system offers accurate responses to medical inquiries.

One of Med42’s strongest points is its adaptability. As an AI helper, it has the potential to alter medical judgment significantly. It may be used for everything from generating personalized treatment plans based on medical records to speeding up the process of combing through mountains of medical material.

As an AI helper with the potential to improve clinical decision-making and expand access to an LLM for healthcare use, Med42 is now available for testing and evaluation. Examples of possible applications are:

Answering Health-Related Questions

Synopsis of Medical History

In support of medical diagnosis

Common Health Questions

The code and weights of Med42 have been released to Hugging Face, encouraging a broad range of scientific examination and input to foster collaboration and continuing growth. Med42’s licensing terms are modeled after those of Meta’s Llama 2 model, making it available for free research and non-commercial usage yet imposing appropriate constraints to account for the risks and obligations associated with using AI in healthcare.

Key indicators of performance:

Med42 outperforms the competition with an accuracy of 72% on a sample exam of USMLE compared to other publicly available medical LLMs.

MedQA dataset results in 61.5% accuracy (GPT-3.5 is at 50%).

Results on MMLU clinical issues are consistently better than those on GPT-3.5.

Limitations:

The therapeutic application of Med42 is still in its early stages. Extensive human testing is currently underway to assure safety.

The risk of creating misleading or dangerous data.

Possible danger of using biased data for training.

Though the findings are encouraging, the researchers warn that further real-world validation of Med42 is necessary before it can be used in clinical practice. Problems may arise from producing inaccurate or harmful results or failing to address existing training data biases. As Med42 moves beyond baselines and toward potentially substantial patient benefits, M42 emphasizes the importance of responsible testing.

Med42 showcases the remarkable development of medical AI while stressing the importance of ethics and safety in research and development. Researchers all over the world will be able to benefit from its open-access publication because of this. Models like Med42 can improve healthcare decision-making and expand access to treatment on a global scale if subjected to thorough validation. Its release is a significant step forward in healthcare AI, but realizing its full potential will require continued openness and teamwork.

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