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 helps to integrate learning from data with learning from medical knowledge to accelerate innovation in digital health and precision medicine. It uses Large Language Models (LLMs), natural language processing, and information retrieval to transform scientific biomedical articles, clinical trials, and systematic reviews into predictive models accessible through an API. By providing informative priors and enabling transfer learning based on global biomedical research and evidence, MedAITM reduces bias while improving robustness and trustworthiness of predictive and generative AI for both large and small biomedical datasets. This shortens time to market and enhances the quality and reliability of personalized AI-powered health products and services.