Foundation Models for General Medical AI
Produktnummer:
18b420b751e44a4628bfe3ca5ae8d98cd4
| Themengebiete: | artificial general intelligence computer vision general medical artificial intelligence large language/vision models machine learning medical foundation models medical image analysis medical vision-language models |
|---|---|
| Veröffentlichungsdatum: | 03.10.2024 |
| EAN: | 9783031734700 |
| Sprache: | Englisch |
| Seitenzahl: | 174 |
| Produktart: | Kartoniert / Broschiert |
| Herausgeber: | Aviles-Rivero, Angelica I. Deng, Zhongying He, Junjun Jeong, Won-Ki Kim, Hyunwoo J. Shen, Yiqing Zhang, Shaoting |
| Verlag: | Springer International Publishing |
| Untertitel: | Second International Workshop, MedAGI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings |
Produktinformationen "Foundation Models for General Medical AI"
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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