Welcome to the Decentralized Insurance Solution section of our repository. This section explains the innovative approach to insurance in the context of healthcare and AI development.
In this section, we detail the process of how patients are rewarded for allowing AI systems to access their health data for machine learning purposes. This reward is in the form of a fungible store of value, such as DAI, which is deposited directly into patients' digital wallets without the need for a third-party mediator.
Here's an overview of how the decentralized insurance solution works:
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Patient and Doctor Setup: A patient and doctor establish the healthcare setup. The doctor records health data in a patient-owned Personal Health Record (PHR).
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Reward with ERC-20 Tokens: Patients are rewarded with ERC-20 tokens (e.g., DAI) for allowing AI systems to access Federated Learning (FL) protocols on-chain to train models on their health data, thus contributing to the development of AI tools in healthcare.
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Direct Deposit 💰: Tokens are deposited directly into patients’ decentralized identity wallets (e.g., Tally Ho, etc.) upon successfully submitting a model update to a Federated Learning round.
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Decentralized Insurance Premiums 🏥: Patients can use these rewards to purchase decentralized insurance premiums, which fund and/or subsidize the provision of healthcare services.
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Continuous Cycle 🔄: The cycle continues, with patients being rewarded for their contributions to AI development and healthcare improvement.
In Federated Learning (FL), data quantity is crucial for training machine learning algorithms effectively. Patients with ongoing healthcare conditions tend to have more health data in their records because they require more healthcare services. As a result, they are more likely to receive greater rewards in the learning process. This aligns well with the mechanism outlined above, where they can use their rewards to cover more expensive insurance premiums.
If you're interested in learning more about our decentralized insurance solution and its role in the future of healthcare, feel free to explore the contents of this section.
For more information, you can reach out to Abraham Nash or connect on LinkedIn.
Happy exploring! 🚀