未明确提及

本论文介绍了一个旨在生成高质量多模态医疗数据集的平台，该平台由ITMO大学的«数字公共卫生技术»实验室开发。该平台通过集成多种外部数据源，使用特殊服务进行数据协调和匿名化处理，以及数据标注，旨在提高医疗数据质量，支持机器学习应用。平台主要处理医疗图像、电子健康记录等数据，支持多种数据格式，如DICOM、XML、CSV等。该平台的目标是解决医疗数据互操作性问题，提高数据集的质量和可靠性，以支持医疗领域的机器学习应用。

This paper presents a platform for generating high-quality multimodal medical datasets, developed by the "Digital Public Health Technology" Lab of ITMO University. By integrating multiple external data sources and utilizing specialized services for data harmonization, anonymization, and annotation, this platform aims to improve the quality of medical data and support machine learning applications. The platform primarily processes data such as medical images and electronic health records (EHRs), and supports various data formats including DICOM, XML, CSV, and others. The platform aims to address the interoperability issues of medical data, enhance the quality and reliability of datasets, and support machine learning applications in the healthcare field.