CrowdDoing citizen science data science of medicinal foods effectiveness volunteer

CrowdDoing citizen science data science of medicinal foods effectiveness volunteer help us to review data science pathways for medicinal foods evidence assessment. A poster about these opportunities can be seen here:

https://drive.google.com/file/d/19AU7IyozDSjdwi5XZoQ3FxPRzhSJNtis/view?usp=sharing

outcome effectiveness from peer to peer randomized RCTs medicinal foods development arc. CrowdDoing medicinal foods data science team aim to leverage public data to analyze co-variates with stress, anxiety, sleep and medicinal foods. We are also working towards a HIPPA compliant phase 2 that will let people test medicinal foods for themselves.

You can see an overview of our medicinal foods application here (https://docs.google.com/presentation/d/12aEqwiRctIx3QcvK6HNFy4uJ5TgRffxQ7xPLEINNyJw/edit?usp=sharing). You can see a data science collection roadmap for how we can match million of recipe reviews to co-variates like stress and anxiety here: https://drive.google.com/file/d/1gF951Q7-XHFblTG-znjW3xXA8XAkPslB/view?usp=sharing. You can see a brake-down of human capital requirements for this project here: https://docs.google.com/document/d/1Kf3mIHQ9_YilBk9kBCvCFXaTj2AbA07SFAX_hv55Cik/edit?usp=sharing.