Tieto > Case Studies > Accelerating Rare Disease Diagnosis and Treatment with AI and Data Analytics

Accelerating Rare Disease Diagnosis and Treatment with AI and Data Analytics

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 Accelerating Rare Disease Diagnosis and Treatment with AI and Data Analytics - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Machine Learning
  • Sensors - Temperature Sensors
Applicable Industries
  • Education
  • Healthcare & Hospitals
Applicable Functions
  • Product Research & Development
Use Cases
  • Clinical Image Analysis
  • Root Cause Analysis & Diagnosis
  • Data Science Services
  • System Integration
The Challenge
To build a certified trusted Research Environment that is compliant with the EU General Data Protection Regulation (GDPR) and the Findata legislation on the secondary use of national social and health data. To accelerate medical research with a modern, high-security digital environment with the latest analytics capabilities.
The Customer

Helsinki University Hospital (HUS)

About The Customer
Helsinki University Hospital (HUS) and Tietoevry have co-developed the data lake service that enables development of advanced treatments and optimized care pathways in healthcare while also accelerating HUS’ world-class medical research. The Rare Diseases eCare for Me project utilizes HUS’s data lake service and its new HUS Acamedic research environment. In the project, that is a part of the CleverHealth Network ecosystem, real world data and machine learning fuels the development of an AI solution that can be used to provide more effective and faster treatment for patients with rare diseases. The project has been funded with the support of Business Finland.
The Solution
The data lake service and its HUS Acamedic analytics workspace provide doctors and researchers with access to large data masses, comprehensive analytics tooling and the latest AI technology. The eCare for Me project enables faster access to impactful care for patients with rare diseases, which has a significant positive impact on patient’s health and wellbeing but significantly cuts public health care costs by reducing the use of diagnostic services and ineffective treatments.
Quantitative Benefit
  • The service can save significant costs on medical care when a diagnosis and the right treatment are found as soon as possible after seeking treatment. The cost for the public healthcare sector can be as much as 40 times greater before the diagnosis is found. A faster diagnosis saves not only costs but also lives, especially in cases where a targeted treatment for the disease exists. The most tragic cases are when the diagnosis takes too long to reach and the patient’s disease progresses in a harmful way. These cases can be prevented if the diagnosis is reached faster.

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