August 20, 2024Journal of Medical Internet ResearchOpen Access

Multimodal Large Language Models in Healthcare: Applications, Challenges, and Future Outlook (Preprint)

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Authors

RARawan AlSaadWeill Cornell Medical College in Qatar AAAlaa Abd‐AlrazaqWeill Cornell Medical College in Qatar SBSabri BoughorbelQatar Airways (Qatar)

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Implication

Review uncovers integration pathways for multimodal large language models across diverse health data modalities, highlighting technical and ethical frameworks for clinical practice.

Key Points

Multimodal large language models can integrate diverse healthcare data such as medical images, electronic health records, and omics data to improve complex clinical decision-making.
Assessment of multimodal large language models examines sensor time-series data, clinical notes, and surgical video, establishing a unified foundation for modern healthcare systems.
Framework highlights solutions for ethical and technical implementation hurdles, guiding future knowledge retrieval and clinical integration for next-generation medical practice.

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AlSaad et al. (2024) studied this question.

synapsesocial.com/papers/68e5b89bb6db643587551097 https://doi.org/10.2196/59505

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Implication

Review uncovers integration pathways for multimodal large language models across diverse health data modalities, highlighting technical and ethical frameworks for clinical practice.

Multimodal Large Language Models in Healthcare: Applications, Challenges, and Future Outlook (Preprint)

Discussion

Member takes

Implication

Key Points

Cite This Study

Multimodal Large Language Models in Healthcare: Applications, Challenges, and Future Outlook (Preprint)

Discussion

Member takes

Implication

Key Points

Cite This Study

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