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Foundation Models for General Medical AI: Second International Workshop, MedAGI 2024, Held Conjunction with MICCAI Marrakesh, Morocco, October 6, ProceedingsFoundation Models for General Medical AI: Second International Workshop, MedAGI 2024, Held Conjunction with MICCAI Marrakesh, Morocco, October 6, Proceedings

Foundation Models for General Medical AI: Second International Workshop, MedAGI 2024, Held Conjunction with MICCAI Marrakesh, Morocco, October 6, Proceedings in Grande Prairie, AB

Current price: $70.99
Original price: $88.68
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Foundation Models for General Medical AI: Second International Workshop, MedAGI 2024, Held Conjunction with MICCAI Marrakesh, Morocco, October 6, Proceedings

Coles

Foundation Models for General Medical AI: Second International Workshop, MedAGI 2024, Held Conjunction with MICCAI Marrakesh, Morocco, October 6, Proceedings in Grande Prairie, AB

Current price: $70.99
Original price: $88.68
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Size: Kobo eBook

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This book constitutes the refereed proceedings from the Second International Workshop on Foundation Models for General Medical AI, MedAGI 2024, held in conjunction with the 27th International conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024, in Marrakesh, Morocco in October 2024. The 17 papers included in this book were carefully reviewed and selected from 26 submissions. These papers provide insights into the current landscape of medical AI and foundation models, that can pave the way for the evolution of task-specific medical AI systems into more generalized frameworks capable of tackling a diverse range of tasks, datasets, and domains.
This book constitutes the refereed proceedings from the Second International Workshop on Foundation Models for General Medical AI, MedAGI 2024, held in conjunction with the 27th International conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024, in Marrakesh, Morocco in October 2024. The 17 papers included in this book were carefully reviewed and selected from 26 submissions. These papers provide insights into the current landscape of medical AI and foundation models, that can pave the way for the evolution of task-specific medical AI systems into more generalized frameworks capable of tackling a diverse range of tasks, datasets, and domains.

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