ISBN: 9783031734700 - foundation models for general medical ai: second international workshop, medagi 2024, held in conjunction with miccai 2024, marrakesh, morocco, ... notes in computer science, band 15184) (5 Ergebnisse)

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings from theSecond International Workshop on Foundation Models for General Medical AI, MedAGI 2024, held in conjunction with the 27th International conference onMedical Image Computing and Computer Assisted Intervention, MICCAI 2024, inMarrakesh, 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 andfoundation 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.…

Taschenbuch. Zustand: Neu. Foundation Models for General Medical AI | Second International Workshop, MedAGI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings | Zhongying Deng (u. a.) | Taschenbuch | Lecture Notes in Computer Science | x | Englisch | 2024 | Springer | EAN 9783031734700 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | 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.…