Vydiant was founded by a group of science and business leaders experienced in biomedicine and predictive analytics, to tackle chronic diseases and unwanted health conditions confronting themselves, their families, and society as a whole.
Our vision is to provide a whole person approach to healthcare. It starts with OneHealth, the unique patented technology ecosystem we built.
OneHealth is simply the most advanced healthware ecosystem for predictive, preventive, personalized wellness. It integrates the complete array of physical, mental, nutritional, environmental, geographic, and social factors that affect an individual’s health and disease susceptibility. This holistic approach to data collection and integration is combined with proprietary algorithms, machine learning and other processes to formulate very precise conclusions on an ongoing basis.
OneHealth’s medical science-based insights as to what you can do, or avoid, to improve your health and lengthen the "quality years" of your life are accessible anywhere, anytime, and at a cost anyone can afford.
Through our social giving platform, we also donate the same access to our communities’ most vulnerable.
This is a formidable quest which others have tried, but no one ever achieved – until Vydiant.
Vydiant leads. Others will follow.
Our OneHealth machine reading pipeline extracts and consolidates health information from vast libraries of trusted, peer-reviewed scientific, clinical, and biomedical research, including the entire National Library of Medicine. The number of reports is immense, and growing by more than a million per year. This is way more than a human brain can integrate and analyze. The OneHealth Knowledge Base is a clear and succinct database of lifestyle factors that positively or negatively affect human health.
OneHealth also regularly integrates new (i.e., non-literature) datasets to increase the value of and improve recommendations delivered by our platform.
For a more detailed explanation of our machine reading and holistic knowledgebase.
"A Comprehensive and Holistic Health Database," 2022 IEEE International Conference on Digital Health (ICDH), 2022, pp. 202-207 (2022). https://www.computer.org/csdl/proceedings-article/icdh/2022/814900a202/1G6jIJur4NG
“Identifying and Analyzing Topic Clusters in a Nutri-, Food-, and Diet-Proteomic Corpus Using Machine Reading.” Nutrients 15, 270 (2023). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9863309/