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The future of medicine hinges on artificial intelligence (AI) development, particularly the emergence of Large Language Models (LLMs) like ChatGPT. These LLMs, trained on vast text data, have enormous potential in healthcare. While they are poised to assist due to the global healthcare workforce shortage, regulatory frameworks are still evolving. Multimodal systems, capable of processing diverse data types simultaneously, are crucial for medicine. Unlike current unimodal AI, medicine involves listening, reading health records, interpreting images, and lab results. Multimodal LLMs (M-LLMs) are the future, empowering AI to significantly aid healthcare professionals without replacing them. This marks a transformative era in healthcare support.
Medical AI's limitations in handling complex cases will soon be addressed by multimodal Large Language Models (LLMs), heralding a transformative era in healthcare. LLMs like ChatGPT, trained on extensive text data, have already made a substantial impact. These models, capable of understanding and generating human-like text, are transitioning from labs to everyday use. As AI integrates into clinical settings due to a shortage of healthcare personnel, regulatory frameworks will evolve. Multimodal LLMs, capable of processing various data types, are the future, allowing AI to significantly assist healthcare professionals without replacing them, enhancing patient care across modalities.
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