Machine Learning in Health Science is a Web3 non-profit platform for promoting Artificial Intelligence (AI) and Machine Learning (ML) innovations that are human-centered, safe, and compliant with current healthcare standards:
- “Web3 Journal: ML in Health Science”. This journal reviews and publishes AI and ML research that is sustainable in enhancing human wellbeing and aligns with current health science standards. Utilizing a Web3 approach, it offers open access publication without any Article Processing Charges (APC), rewarding contributing authors with the governance blockchain token MLHS for their valuable work. The journal continually gathers evidence-based information that may significantly influence human well-being. This data is utilized for the human-centered assessment of AI and ML projects:
- “Web3 Certificate: Human-centered Project” is a blockchain certificate founded on evidence-based, human-centered principles. The certificate does not aim to replace official regulators. It serves to prove human-centered settings in AI and ML projects, facilitating sustainable human-AI collaboration. The evaluation will be carried out utilizing the specific, Evidence-based Recommendations which are regularly reviewed and updated for improvement:
- Web3 Governance Token MLHS: Built on the fast and robust BNB Blockchain, the MLHS token secures decentralized identification for human-centered AI and ML projects and acts as a Web3 reward mechanism for contributing authors.
- “Web3 Society”. A self-financing entity, facilitated by Web3 liquidity, enables the regulation of investments and rewards contributing authors and researchers for their efforts in enhancing human wellbeing within the AI & ML health sciences domain.
- “Web3 Board”. The Web3 Board primarily consists of healthcare practitioners and is responsible for regulating publication, promotion, and awarding processes. It ensures that the content aligns with our human-centered ethos and adheres to current healthcare standards.
