Streamlining solutions for common issues

Reduced development time and costs

Seamless inclusion of up-to-date domain knowledge

Increased robustness for new settings

Mitigation of small or low-quality data for AI/ML training

Causality priors from clinical studies

Reduced bias, discrimination, inequity

Synthesis of novel interventions from known trials

Improved explainability and trustworthiness

Learning from data and knowledge

Seamless integration and API access

Streamlined R&D in AI/ML for health

MedAI pipeline and API

MedAITM combines learning from data with learning from medical knowledge for rapid innovation in digital and precision health. It uses natural language processing and information retrieval to convert scientific biomedical articles, clinical trials, and systematic reviews into predictive models accessible via an API. By providing informative priors and enabling transfer learning based on worldwide domain knowledge, MedAITM reduces bias and improves robustness and trustworthiness of medical AI for big and small datasets. This reduces time to market and improves quality of personalized AI-powered health-related products and services.