The Universal Health Data Schemas for Privacy-Preserving AI Community Group has been proposed by Amir Hameed Mir:<\/p>\n\n\n\n
The mission of this group is to define a universal, modular, and interoperable set of data schemas for health information. Our goal is to enable the aggregation and utilization of data for medical research and AI training through privacy-enhancing technologies (PETs) like Zero-Knowledge Proofs (ZKPs), while ensuring patient control and consent via Verifiable Credentials (VCs).<\/p>\n\n
Scope and Problem Statement<\/p>\n\n
The development of robust medical AI is hampered by siloed, non-standardized, and sensitive health data. Current data formats are incompatible across institutions, and privacy regulations prevent the sharing of raw data, creating a significant barrier to collaborative research. This group will address this by creating schemas that transform health data into standardized, verifiable, and privacy-preserving assets.<\/p>\n\n
Key Deliverables<\/p>\n\n
\n You are invited to support the creation of this group<\/a>.\n Once the group has a total of 5 supporters, it will be launched and people can join to begin work. In order to support the group, you will need a W3C account<\/a>.\n<\/p>\n\n\n\n Once launched, the group will no longer be listed as “proposed”; it will be in the list of current groups<\/a>.<\/p>\n\n\n\n \n If you believe that there is an issue with this group that requires the attention of the W3C staff, please send us email on site-comments@w3.org<\/a>\n<\/p>\n\n\n\n Thank you, The Universal Health Data Schemas for Privacy-Preserving AI Community Group has been proposed by Amir Hameed Mir: The mission of this group is to define a universal, modular, and interoperable set of data schemas for health information. Our goal is … Continue reading
\nW3C Community Development Team<\/p>\n\n","protected":false},"excerpt":{"rendered":"