.png){kind=icon}
.png){kind=icon}
Return
An integrated platform for high-quality data-driven research
.png){kind=icon}
OA
AI
DOI：10.1093/ehjdh/ztaf143.021.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The digital transformation of healthcare has led to an unprecedented growth in the volume and heterogeneity of clinical data. At the same time, aging populations and rising demands on healthcare systems require cost-effective, scalable solutions. Artificial intelligence (AI) has emerged as a powerful tool in clinical research, enabling the extraction of complex diagnostic features from data that are otherwise imperceptible. However, the development and deployment of AI models demand structured, large-scale, high-quality datasets. The extensive preparation required before data can be used for AI training (collection, transfer, cleaning, translation, standardization, etc.) poses a significant bottleneck between data acquisition and algorithm development.
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
E
IF:
4.4
Papers:
840
Citations:
949