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

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...

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Gorde:
Xehetasun bibliografikoak
Erakunde egilea: SpringerLink (Online service)
Beste egile batzuk: Deng, Zhongying (Argitaratzailea), Shen, Yiqing (Argitaratzailea), Kim, Hyunwoo J. (Argitaratzailea), Jeong, Won-Ki (Argitaratzailea), Aviles-Rivero, Angelica I. (Argitaratzailea), He, Junjun (Argitaratzailea), Zhang, Shaoting (Argitaratzailea)
Formatua: Baliabide elektronikoa eBook
Hizkuntza:ingelesa
Argitaratua: Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Edizioa:1st ed. 2025.
Saila:Lecture Notes in Computer Science, 15184
Gaiak:
Image processing > Digital techniques.
Computer vision.
Imaging systems in biology.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Biological Imaging.
Sarrera elektronikoa:https://doi.org/10.1007/978-3-031-73471-7
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Deskribapena
Gaia: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.
Deskribapen fisikoa:X, 174 p. 56 illus., 52 illus. in color. online resource.
ISBN:9783031734717
ISSN:1611-3349 ;
DOI:10.1007/978-3-031-73471-7

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