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Federated Learning on Vertically Distributed Healthcare Data

Joining complementary data sets creates stronger machine learning capabilities. But valuable data containing intellectual property cannot be shared and must adhere to regulatory frameworks. Healthcare companies can use federated learning to work with decentralized data, allowing secure collaboration without sharing data.


In this white paper, you will learn:


  • About vertically distributed data

  • Workflow of privacy-preserving data science

  • Deep-dive into privacy-preserving record linkage

  • Deep-dive into federated and privacy-preserving analytics

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Privacy-preserving Data Science on QSAR models
This case study shows the effectiveness of Apheris’ platform and services for data science on data that is not directly accessible and distributed. Federated learning decentralizes learning algorithms to access multiple data sets, maintaining privacy. Without pooling sensitive data, new insights can be uncovered securely.


In this white paper, you will learn:


  • How federated learning, privacy testing and other tools that enable data science on not directly accessible and distributed data

  • Sowcase of federated learning, privacy testing and other tools that enable data science practices on not directly accessible and distributed data, at the example of QSAR models.
Privacy-preserving Data Ecosystems in Support of Drug Discovery
In recent years, Deep Learning has gained considerable traction in many fields, but none more so than in the realm of drug discovery. Applications range from generating de novo hit-like molecules, predicting drug-disease associations and activity, toxicology estimation, to the analysis of medical images.


In this white paper, you will learn:


  • How you can preserve intellectual property while generating value from sensitive data

  • Deep dive into federated and secure QSAR models

  • How Apheris prevents uncontrolled data sharing

  • How you can pave the way to precision medicine with federated and secure QSAR model training
How to Choose the Best Federated Learning Platform
How can you evaluate platforms around emerging technologies like federated learning? This article gives you guidance on what your selection criteria should be.