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AI Revolutionizes Diagnostics of Rare Diseases: A Case Study on Helsinki University Hospital
技术
- 分析与建模 - 机器学习
- 传感器 - 温度传感器
适用行业
- 教育
- 医疗保健和医院
适用功能
- 产品研发
用例
- 临床图像分析
- 根因分析与诊断
服务
- 数据科学服务
- 系统集成
挑战
建立一个经过认证的可信研究环境，该环境符合欧盟通用数据保护条例 (GDPR) 和关于二次使用国家社会和健康数据的 Findata 立法。通过具有最新分析功能的现代、高安全性数字环境加速医学研究。
客户
赫尔辛基大学医院 (HUS)
关于客户
赫尔辛基大学医院 (HUS) 和 Tietoevry 共同开发了数据湖服务，可在医疗保健领域开发先进的治疗方法和优化护理路径，同时加速 HUS 的世界级医学研究。
Rare Diseases eCare for Me 项目利用了 HUS 的数据湖服务及其新的 HUS Acamedic 研究环境。该项目是 CleverHealth Network 生态系统的一部分，现实世界的数据和机器学习推动了人工智能解决方案的开发，该解决方案可用于为罕见病患者提供更有效和更快的治疗。该项目得到了芬兰商业协会的资助。
解决方案
数据湖服务及其 HUS Acamedic 分析工作区为医生和研究人员提供了访问大量数据、综合分析工具和最新 AI 技术的途径。 eCare for Me 项目使罕见病患者能够更快地获得有效的护理，这对患者的健康和福祉产生了重大的积极影响，但通过减少诊断服务和无效治疗的使用显着降低了公共医疗保健成本。
运营影响
数量效益
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