Synthetic multimodal data modelling for data imputation

IF 26.8 1区医学 Q1 ENGINEERING, BIOMEDICAL

Nature Biomedical Engineering Pub Date : 2024-12-23 DOI:10.1038/s41551-024-01324-1

Francisco Carrillo-Perez, Marija Pizurica, Kathleen Marchal, Olivier Gevaert

引用次数: 0

Abstract

Foundation models can be advantageously harnessed to estimate missing data in multimodal biomedical datasets and to generate realistic synthetic samples.

Abstract Image

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

Nature Biomedical Engineering Medicine-Medicine (miscellaneous)

CiteScore

45.30

自引率

1.10%

发文量

138

期刊介绍： Nature Biomedical Engineering is an online-only monthly journal that was launched in January 2017. It aims to publish original research, reviews, and commentary focusing on applied biomedicine and health technology. The journal targets a diverse audience, including life scientists who are involved in developing experimental or computational systems and methods to enhance our understanding of human physiology. It also covers biomedical researchers and engineers who are engaged in designing or optimizing therapies, assays, devices, or procedures for diagnosing or treating diseases. Additionally, clinicians, who make use of research outputs to evaluate patient health or administer therapy in various clinical settings and healthcare contexts, are also part of the target audience.