HealthScience Cooperative Network

  • Peer to peer

  • Cooperative

  • Decentralized

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    Project Mobile & Sensors
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    Decentralized Machine Learning
Health Science Projects

The community is working on individual projects that all come together to provide the best health science. Each project is highly challenging work from mobile app development to decentralzied Machine Learning to simulations and visualisations. The initial use case is heart science. The goal is to allow individual peers to collection and securely own their own data from a wearable sensor, to scientific consensus on the truthfullness of the heart science put forward in a computational form. The last part is to apply the validated science to real world problems and provide educational simulations and visualisation. With all these activies being co-ordinated on a peer to peer network self governed by the network.

  • Projects
  • Mobile Apps Active
  • Sensors Active
  • D-machine learningActive
  • ResolutionHealthActive
  • SimulationsActive
  • VisualisationsActive
  • LKN-contributorActive

Community Projects

The current use case is focused on hearth science with data from wearable devices. Each project provides a summary and links to thinking and code.
Mobile Apps

Mobile apps are used to communicate with wearable and sensor devices to collect data and to secure into personal data stores.GitHub IOS


The main task is to re-engineer the GATT and bluetooth standards to give data ownership back to their owners. GitHub

Decentralized Machine Learning

How to enable machine learning on a peer to peer network. A new 'super smart' contract, own and governed by the network takes collective ownership of the algorithm. GitHub

Resolution Health

A graphical interface onto the Health Science Network and manage mobile apps, sensor and controls over data and computations. A secure place for knowledge tokens. GitHub


Current project is building a proof of concept computational simulation of a human heart. GitHub


Graphical visualisations of the science for use in apps, education or communication of the evidence.

© 2017 Medical. Made by M_ADNAN